2828 lines
90 KiB
Plaintext
2828 lines
90 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "143717cd",
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"metadata": {},
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"outputs": [
|
||
{
|
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"name": "stdout",
|
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"output_type": "stream",
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"text": [
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"/opt/homebrew/anaconda3/bin/python\n"
|
||
]
|
||
}
|
||
],
|
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"source": [
|
||
"import sys\n",
|
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"print(sys.executable)"
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]
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},
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{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"id": "508336f4",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from kg_ocr import get_screenshots, extract_text, create_and_index, query_embedding"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
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||
"id": "11055f85",
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||
"metadata": {},
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||
"outputs": [
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||
{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "e22406e942764e928a8bf58776e96e45",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Loading weights: 0%| | 0/103 [00:00<?, ?it/s]"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"\u001b[1mBertModel LOAD REPORT\u001b[0m from: sentence-transformers/all-MiniLM-L6-v2\n",
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"Key | Status | | \n",
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"------------------------+------------+--+-\n",
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"embeddings.position_ids | UNEXPECTED | | \n",
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"\n",
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||
"\u001b[3mNotes:\n",
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||
"- UNEXPECTED\u001b[3m\t:can be ignored when loading from different task/architecture; not ok if you expect identical arch.\u001b[0m\n",
|
||
"Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"screenshots = get_screenshots(\"/Users/Aman/Pictures\")\n",
|
||
"texts = extract_text(screenshots)\n",
|
||
"embeddings = create_and_index(texts)\n",
|
||
"results = query_embedding(embeddings, \"evolution\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
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||
"id": "ef3b269a",
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||
"metadata": {},
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||
"outputs": [
|
||
{
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||
"name": "stdout",
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"output_type": "stream",
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"text": [
|
||
"doi: 10.1126/science.1181369.\n",
|
||
"\n",
|
||
"This slide explains how rapid fluctuations in population size influence the effective population size\n",
|
||
"(N-), a key parameter in population genetics. Unlike the arithmetic mean, N; reflects the\n",
|
||
"harmonic mean of population sizes over time, which is disproportionately affected by periods of\n",
|
||
"small population size. For example, if the population fluctuates between N and N/4, the effective\n",
|
||
"population size becomes NV, = 2N, significantly smaller than the actual average population size.\n",
|
||
"This occurs because smaller populations have higher probabilities of coalescence, reducing\n",
|
||
"genetic diversity. For general periods (T’), Nz is calculated as the harmonic mean of population\n",
|
||
"sizes over T’ generations, emphasizing that even brief reductions in population size can greatly\n",
|
||
"lower N,. The slide highlights that these fluctuations shape genetic variation by reducing Ne,\n",
|
||
"\n",
|
||
"affecting coalescence rates and increasing the impact of genetic drift.\n",
|
||
"\n",
|
||
"Yes, the statement implies that an advantageous allele is lost most of the time, especially when its,\n",
|
||
"initial frequency is low.\n",
|
||
"\n",
|
||
"Probability of Fixation\n",
|
||
"The fixation probability of an advantageous allele in a population is approximately:\n",
|
||
"Pix © 2hs\n",
|
||
"\n",
|
||
"where:\n",
|
||
"\n",
|
||
"+h: Dominance coeffi\n",
|
||
"\n",
|
||
"ant (h = 0.5 for additive alleles).\n",
|
||
"\n",
|
||
"+ 8: Selection coefficient (strength of selection).\n",
|
||
"\n",
|
||
"This represents the probability that an advantageous allele will reach fixation (frequency = 1) in the\n",
|
||
"population, starting from a single copy.\n",
|
||
"\n",
|
||
"Why is the advantageous allele often lost?\n",
|
||
"\n",
|
||
"+ Infinite populations, genetic drift causes random fluctuations in allele frequencies.\n",
|
||
"\n",
|
||
"+ When an advantageous allele starts at a low frequency (e.g., a single copy), drift dominates\n",
|
||
"selection, leading to a high probability of loss.\n",
|
||
"\n",
|
||
"ial Frequency:\n",
|
||
"\n",
|
||
"+ Ifthe advantageous allele appears as a single mutation, i\n",
|
||
"diploid population of size N)\n",
|
||
"\n",
|
||
"ial frequency is\n",
|
||
"\n",
|
||
"+ Even with selection, the allele can be lost due to random chance.\n",
|
||
"\n",
|
||
"+ Fora strongly advantageous allele (s is large), the fixation probability increases.\n",
|
||
"\n",
|
||
"= However, for most realistic values of s, fixation probabilities are still low, especially in small\n",
|
||
"populations.\n",
|
||
"\n",
|
||
"Key Insight\n",
|
||
"\n",
|
||
"Even though an advantageous allele has a higher chance of fixation compared to a neutral or\n",
|
||
"deleterious allele, it\n",
|
||
"\n",
|
||
"is still more likely to be lost in the early generations due to genetic drift, unless it\n",
|
||
"is strongly favored or the population size is large.\n",
|
||
"\n",
|
||
"Would you like a mathematical or simulated example to demonstrate this?\n",
|
||
"\n",
|
||
"This slide is included to illustrate the complexities of analyzing genetic variation under bottleneck\n",
|
||
"scenarios and their impact on Tajima's D. It highlights two cases of bottlenecks: one where only a\n",
|
||
"single ancestral lineage survives (Case A) and another where multiple lineages persist through the\n",
|
||
"bottleneck (Case B). These scenarios lead to different patterns of genetic diversity and allele\n",
|
||
"frequency distributions. In Case A, the severe reduction in population size results in a loss of\n",
|
||
"genetic diversity, typically leading to 6, < Ow and D < 0, as low-frequency alleles dominate. In\n",
|
||
"Case B, where multiple lineages survive, the patterns can reverse, leading to 0, > Oy and D > 0\n",
|
||
", as intermediate-frequency alleles become more common. The slide emphasizes the challenge of\n",
|
||
"interpreting Tajima's D in bottleneck models due to these variable outcomes and underscores the\n",
|
||
"\n",
|
||
"need for careful consideration of demographic history in genetic analyses.\n",
|
||
"\n",
|
||
"@ Vivaldi\n",
|
||
"\n",
|
||
"at)\n",
|
||
"\n",
|
||
"v Speed Dial\n",
|
||
"\n",
|
||
"File Edit View Bookmarks\n",
|
||
"\n",
|
||
"S\n",
|
||
"\n",
|
||
"&% Workspaces v\n",
|
||
"\n",
|
||
"—- > a U8\n",
|
||
"\n",
|
||
"v Imported From... YY Imported From...\n",
|
||
"\n",
|
||
"© sic all pats\n",
|
||
"\n",
|
||
"Sources\n",
|
||
"\n",
|
||
"+ Add source\n",
|
||
"\n",
|
||
"Select all sources\n",
|
||
"\n",
|
||
"]\n",
|
||
"\n",
|
||
"Formulae.pdf\n",
|
||
"\n",
|
||
"Lecture O.pdf\n",
|
||
"\n",
|
||
"Lecture 1.pdf\n",
|
||
"\n",
|
||
"Lecture 1_1.pdf\n",
|
||
"\n",
|
||
"Lecture 2.pdf\n",
|
||
"\n",
|
||
"Lecture 3.pdf\n",
|
||
"\n",
|
||
"Lecture 4.pdf\n",
|
||
"\n",
|
||
"Lecture 5.pdf\n",
|
||
"\n",
|
||
"Lecture 6.pdf\n",
|
||
"\n",
|
||
"0 @ 0 ®\n",
|
||
"\n",
|
||
"Mail\n",
|
||
"\n",
|
||
"@ Cool Guides\n",
|
||
"\n",
|
||
"google.com\n",
|
||
"\n",
|
||
"Online Bewerbung QGIS API Docume...\n",
|
||
"\n",
|
||
"Oo\n",
|
||
"\n",
|
||
"Tools Window Help\n",
|
||
"\n",
|
||
"Startpage Search Results Kurs: Evolutionsgenetik de § NotebookLM\n",
|
||
"\n",
|
||
"om {fl v\n",
|
||
"\n",
|
||
"qgis - Trying to pe... New Script - Earth...\n",
|
||
"\n",
|
||
"Chat @ Refresh\n",
|
||
"\n",
|
||
"explain more about the following as per the sources\n",
|
||
"- 1. The change in allele frequency due to selection\n",
|
||
"2. The probability of fixation for an allele with\n",
|
||
"selection advantage and the time to fixation 3. The\n",
|
||
"equilibrium frequencies for both alleles in\n",
|
||
"overdominance\n",
|
||
"\n",
|
||
"Here's more information about allele frequency\n",
|
||
"change due to selection, the probability and time to\n",
|
||
"fixation of an allele with a selective advantage, and\n",
|
||
"equilibrium frequencies in overdominance, based on\n",
|
||
"the provided sources:\n",
|
||
"1. The change in allele frequency due to selection\n",
|
||
"* General principle Natural selection causes\n",
|
||
"changes in allele frequencies from one generation\n",
|
||
"to the next 1... . Fitter individuals produce more\n",
|
||
"viable offspring, influencing future generations 3.\n",
|
||
"- Fisher's theorem The fitness of the population is\n",
|
||
"\n",
|
||
"maximized 4\n",
|
||
"\n",
|
||
"14 sources\n",
|
||
"\n",
|
||
"Start typing...\n",
|
||
"\n",
|
||
"°©@\n",
|
||
"\n",
|
||
"Describe Wright-Fisher model assumptions abou >\n",
|
||
"\n",
|
||
"Pastebin.com - #1...\n",
|
||
"\n",
|
||
"So\n",
|
||
"te)\n",
|
||
"\n",
|
||
"$vertr? 6 8B &@ SB FQ\n",
|
||
"\n",
|
||
"® EvolG all pdfs - Notebook BAKSMMaTi ela dale most rel is\n",
|
||
"\n",
|
||
"Q: Search Startpage v @\n",
|
||
"TargetP 2.0-DTU... https://www.mood... OnePlus12R revie... Whois “Indian\"in.. vA\n",
|
||
"«~ Share 3 Settings CO\n",
|
||
"Studio > Note a\n",
|
||
"\n",
|
||
"Genomic Signatures of Natural Selection\n",
|
||
"\n",
|
||
"(Saved responses are view only)\n",
|
||
"\n",
|
||
"a reduction in variation [9].\n",
|
||
"2. Detecting Selection: Neutrality Tests\n",
|
||
"\n",
|
||
"- Neutrality tests compare observed data to theoretical\n",
|
||
"expectations under a neutral model (where alleles are not under\n",
|
||
"selection) to detect if selection has occurred [10].\n",
|
||
"\n",
|
||
"* Comparing multiple loci across the genome: Because selection\n",
|
||
"acts on few genes, loci under selection should be outliers when\n",
|
||
"compared to other parts of the genome [10, 11].\n",
|
||
"\n",
|
||
"* Tajima's D: This test compares two estimators of the population\n",
|
||
"mutation rate, 6 (theta). Tajima's D will be:\n",
|
||
"\n",
|
||
"* Negative when there is an excess of rare alleles, suggesting a\n",
|
||
"recent selective sweep or population expansion [5, 12].\n",
|
||
"\n",
|
||
"+ Positive when there is an excess of intermediate-frequency\n",
|
||
"alleles, suggesting balancing selection, population structure,\n",
|
||
"or a recent bottleneck [8, 9, 12].\n",
|
||
"\n",
|
||
"* Zero when a population is in equilibrium, and evolving\n",
|
||
"neutrally [12].\n",
|
||
"\n",
|
||
"* McDonald-Kreitman (MK) test: Compares the ratio of non-\n",
|
||
"synonymous (amino acid changing) to synonymous (silent)\n",
|
||
"substitutions within a species and between species. A higher ratio\n",
|
||
"between species compared to within species suggests positive\n",
|
||
"selection, and a lower ratio suggests purifying selection [13, 14].\n",
|
||
"\n",
|
||
"* Site Frequency Spectrum (SFS): The distribution of allele\n",
|
||
"frequencies in a sample. Selection leaves specific sianatures in the\n",
|
||
"\n",
|
||
"G) Convert to source\n",
|
||
"\n",
|
||
"NotebookLM can be inaccurate; please double check its responses.\n",
|
||
"\n",
|
||
"+\n",
|
||
"Q\n",
|
||
"\n",
|
||
"QC) Co reset —O—— 100 %\n",
|
||
"\n",
|
||
"c\n",
|
||
"\n",
|
||
"Mon Feb 10 16:00\n",
|
||
"\n",
|
||
"aw\n",
|
||
"\n",
|
||
"v\n",
|
||
"\n",
|
||
"O © HD\n",
|
||
"\n",
|
||
"QD\n",
|
||
"\n",
|
||
"ee\n",
|
||
"\n",
|
||
"Qu qa\n",
|
||
"\n",
|
||
"OH O®e< GO 8W OW A\n",
|
||
"\n",
|
||
"&\n",
|
||
"\n",
|
||
"16:00\n",
|
||
"\n",
|
||
"”\n",
|
||
"\n",
|
||
"@ Vivaldi\n",
|
||
"\n",
|
||
"at)\n",
|
||
"\n",
|
||
"v Speed Dial\n",
|
||
"\n",
|
||
"File Edit View Bookmarks\n",
|
||
"\n",
|
||
"S\n",
|
||
"\n",
|
||
"&% Workspaces v\n",
|
||
"\n",
|
||
"—- > a U8\n",
|
||
"\n",
|
||
"v Imported From... YY Imported From...\n",
|
||
"\n",
|
||
"© sic all pats\n",
|
||
"\n",
|
||
"Sources\n",
|
||
"\n",
|
||
"+ Add source\n",
|
||
"\n",
|
||
"Select all sources\n",
|
||
"\n",
|
||
"]\n",
|
||
"\n",
|
||
"Formulae.pdf\n",
|
||
"\n",
|
||
"Lecture O.pdf\n",
|
||
"\n",
|
||
"Lecture 1.pdf\n",
|
||
"\n",
|
||
"Lecture 1_1.pdf\n",
|
||
"\n",
|
||
"Lecture 2.pdf\n",
|
||
"\n",
|
||
"Lecture 3.pdf\n",
|
||
"\n",
|
||
"Lecture 4.pdf\n",
|
||
"\n",
|
||
"Lecture 5.pdf\n",
|
||
"\n",
|
||
"Lecture 6.pdf\n",
|
||
"\n",
|
||
"0 @ 0 ®\n",
|
||
"\n",
|
||
"Mail\n",
|
||
"\n",
|
||
"@ Cool Guides\n",
|
||
"\n",
|
||
"google.com\n",
|
||
"\n",
|
||
"Online Bewerbung QGIS API Docume...\n",
|
||
"\n",
|
||
"Oo\n",
|
||
"\n",
|
||
"Tools Window Help\n",
|
||
"\n",
|
||
"Startpage Search Results Kurs: Evolutionsgenetik de § NotebookLM\n",
|
||
"\n",
|
||
"om {fl v\n",
|
||
"\n",
|
||
"qgis - Trying to pe... New Script - Earth...\n",
|
||
"\n",
|
||
"Chat @ Refresh\n",
|
||
"\n",
|
||
"explain more about the following as per the sources\n",
|
||
"- 1. The change in allele frequency due to selection\n",
|
||
"2. The probability of fixation for an allele with\n",
|
||
"selection advantage and the time to fixation 3. The\n",
|
||
"equilibrium frequencies for both alleles in\n",
|
||
"overdominance\n",
|
||
"\n",
|
||
"Here's more information about allele frequency\n",
|
||
"change due to selection, the probability and time to\n",
|
||
"fixation of an allele with a selective advantage, and\n",
|
||
"equilibrium frequencies in overdominance, based on\n",
|
||
"the provided sources:\n",
|
||
"1. The change in allele frequency due to selection\n",
|
||
"* General principle Natural selection causes\n",
|
||
"changes in allele frequencies from one generation\n",
|
||
".. . Fitter individuals produce more\n",
|
||
"viable offspring, influencing future generations 3.\n",
|
||
"\n",
|
||
"to the next 1\n",
|
||
"\n",
|
||
"- Fisher's theorem The fitness of the population is\n",
|
||
"\n",
|
||
"maximized 4\n",
|
||
"\n",
|
||
"14 sources\n",
|
||
"\n",
|
||
"Start typing...\n",
|
||
"\n",
|
||
"°©@\n",
|
||
"\n",
|
||
"Describe Wright-Fisher model assumptions abou >\n",
|
||
"\n",
|
||
"Pastebin.com - #1...\n",
|
||
"\n",
|
||
"So\n",
|
||
"te)\n",
|
||
"\n",
|
||
"$vertr? 6 8B &@ SB FQ\n",
|
||
"\n",
|
||
"® EvolG all pdfs - Notebook BAKSMMaTi ela dale most rel is\n",
|
||
"\n",
|
||
"Q: Search Startpage v\n",
|
||
"\n",
|
||
"TargetP 2.0-DTU... https://www.mood... OnePlus 12R revie... Who is “Indian” in ...\n",
|
||
"\n",
|
||
"«~ Share 3 Settings\n",
|
||
"\n",
|
||
"Studio > Note a\n",
|
||
"\n",
|
||
"Genomic Signatures of Natural Selection\n",
|
||
"\n",
|
||
"(Saved responses are view only)\n",
|
||
"\n",
|
||
"a reduction in variation [9].\n",
|
||
"2. Detecting Selection: Neutrality Tests\n",
|
||
"\n",
|
||
"- Neutrality tests compare observed data to theoretical\n",
|
||
"expectations under a neutral model (where alleles are not under\n",
|
||
"selection) to detect if selection has occurred [10].\n",
|
||
"\n",
|
||
"* Comparing multiple loci across the genome: Because selection\n",
|
||
"acts on few genes, loci under selection should be outliers when\n",
|
||
"compared to other parts of the genome [10, 11].\n",
|
||
"\n",
|
||
"* Tajima's D: This test compares two estimators of the population\n",
|
||
"mutation rate, 6 (theta). Tajima's D will be:\n",
|
||
"\n",
|
||
"* Negative when there is an excess of rare alleles, suggesting a\n",
|
||
"recent selective sweep or population expansion [5, 12].\n",
|
||
"\n",
|
||
"+ Positive when there is an excess of intermediate-frequency\n",
|
||
"alleles, suggesting balancing selection, population structure,\n",
|
||
"or a recent bottleneck [8, 9, 12].\n",
|
||
"\n",
|
||
"* Zero when a population is in equilibrium, and evolving\n",
|
||
"neutrally [12].\n",
|
||
"\n",
|
||
"* McDonald-Kreitman (MK) test: Compares the ratio of non-\n",
|
||
"synonymous (amino acid changing) to synonymous (silent)\n",
|
||
"substitutions within a species and between species. A higher ratio\n",
|
||
"between species compared to within species suggests positive\n",
|
||
"selection, and a lower ratio suggests purifying selection [13, 14].\n",
|
||
"\n",
|
||
"* Site Frequency Spectrum (SFS): The distribution of allele\n",
|
||
"frequencies in a sample. Selection leaves specific sianatures in the\n",
|
||
"\n",
|
||
"G) Convert to source\n",
|
||
"\n",
|
||
"NotebookLM can be inaccurate; please double check its responses.\n",
|
||
"\n",
|
||
"+\n",
|
||
"Q\n",
|
||
"\n",
|
||
"QC) Co reset —O—— 100 %\n",
|
||
"\n",
|
||
"c\n",
|
||
"\n",
|
||
"vA\n",
|
||
"\n",
|
||
"Mon Feb 10 16:00\n",
|
||
"\n",
|
||
"aw\n",
|
||
"\n",
|
||
"v\n",
|
||
"\n",
|
||
"QD\n",
|
||
"\n",
|
||
"ee\n",
|
||
"\n",
|
||
"Qu qa\n",
|
||
"\n",
|
||
"OH O®e< GO 8W OW A\n",
|
||
"\n",
|
||
"&\n",
|
||
"\n",
|
||
"16:00\n",
|
||
"\n",
|
||
"O © HD\n",
|
||
"\n",
|
||
"”\n",
|
||
"\n",
|
||
"ioh\n",
|
||
"\n",
|
||
"R\n",
|
||
"\n",
|
||
"i\n",
|
||
"\n",
|
||
"response to selection\n",
|
||
"selection intensity\n",
|
||
"\n",
|
||
"/ genetic variance\n",
|
||
"\n",
|
||
"' heritability\n",
|
||
"\n",
|
||
"Intro\n",
|
||
"\n",
|
||
"¢ Plant Morphogenesis\n",
|
||
"¢ Arabidopsis\n",
|
||
"\n",
|
||
"* Ovule development\n",
|
||
"* Kink & Bend\n",
|
||
"\n",
|
||
"Figure 1: Kink and Bend in Arabidopsis Thaliana\n",
|
||
"\n",
|
||
"Bottleneck models\n",
|
||
"\n",
|
||
"(A) (B)\n",
|
||
"\n",
|
||
"time\n",
|
||
"\n",
|
||
"population size\n",
|
||
"\n",
|
||
"Figure 5.2: Two cases in a bottleneck mode. (A) Only one ancestral line survives the\n",
|
||
"bottleneck. (B) Two or more lines survive which leads to different patterns in observed\n",
|
||
"data.\n",
|
||
"\n",
|
||
"8, 8, < Oy 8, > Ow\n",
|
||
"Tajima‘s D D<0 D>0\n",
|
||
"\n",
|
||
"It is more difficult for bottleneck modell!!\n",
|
||
"\n",
|
||
"Why is important to have an accurate demography?\n",
|
||
"\n",
|
||
"‘ol\n",
|
||
"\n",
|
||
"TY ey\n",
|
||
"\n",
|
||
"® o\n",
|
||
"position along genome\n",
|
||
"\n",
|
||
"\n",
|
||
"‘The difference between orthologs and paralogs lies in their evolutionary origin and functional\n",
|
||
"\n",
|
||
"rgence:\n",
|
||
"\n",
|
||
"1. Orthologs\n",
|
||
"\n",
|
||
"* Def\n",
|
||
"\n",
|
||
"1n: Genes that originate from a common ancestor due to a speci\n",
|
||
"\n",
|
||
"+ Function: Often retain similar functions across different species.\n",
|
||
"\n",
|
||
"+ Example: The hemoglobin gene in humans and mice is orthologous because both species\n",
|
||
"inherited it from a common ancestor.\n",
|
||
"\n",
|
||
"ints:\n",
|
||
"\n",
|
||
"Key\n",
|
||
"\n",
|
||
"V Arise from speciation events\n",
|
||
"V Found in different species\n",
|
||
"\n",
|
||
"V Generally have similar functions\n",
|
||
"\n",
|
||
"2. Paralogs\n",
|
||
"\n",
|
||
"* Def\n",
|
||
"\n",
|
||
"1n: Genes that arise from a gene duplication event within the same species.\n",
|
||
"+ Function: May evolve new or specialized functions.\n",
|
||
"\n",
|
||
"+ Example: Hemoglobin and myoglobin in humans—both originated from a gene duplication event\n",
|
||
"but evolved to serve different functions.\n",
|
||
"\n",
|
||
"Key Points:\n",
|
||
"V Arise from gene duplication events\n",
|
||
"V Found within the same species (or later diverging species)\n",
|
||
"\n",
|
||
"V Can have different functions\n",
|
||
"\n",
|
||
"Summary Table\n",
|
||
"Feature Orthologs Paralogs\n",
|
||
"Origin Speciation Gene duplication\n",
|
||
"Found in Different species ‘Same species (or later divergence)\n",
|
||
"Function Often conserved Can diverge significantly\n",
|
||
"\n",
|
||
"Example Human vs. mouse hemoglobin Human hemoglobin vs. myoglobin\n",
|
||
"\n",
|
||
"Self-fertilization TM\n",
|
||
"\n",
|
||
"Parents AA x aa Hetero- Homo-\n",
|
||
"J zygosity zygosity\n",
|
||
"\n",
|
||
"Aa «Aa\n",
|
||
"\n",
|
||
"— !~ may\n",
|
||
"\n",
|
||
"F, generation 50\n",
|
||
"\n",
|
||
"F, generation\n",
|
||
"\n",
|
||
"F, generation\n",
|
||
"\n",
|
||
"F, generation\n",
|
||
"\n",
|
||
"¢,corerion A ss\n",
|
||
"\n",
|
||
"Prof. Chns-Carolin Schon (TUM) | Plunt Brooding\n",
|
||
"\n",
|
||
"F, versus DH\n",
|
||
"\n",
|
||
"\n",
|
||
"Outcrossing — Panmixia — Hardy-Weinberg-Law TM\n",
|
||
"\n",
|
||
"In the absence of\n",
|
||
"\n",
|
||
"- selection\n",
|
||
"\n",
|
||
"- migration\n",
|
||
"\n",
|
||
"~ mutation\n",
|
||
"\n",
|
||
"we have under panmixia\n",
|
||
"\n",
|
||
"no change in gene frequencies\n",
|
||
"\n",
|
||
"EE recone\n",
|
||
"\n",
|
||
"=P, =p, -...\n",
|
||
"p=P+05H id mene\n",
|
||
"\n",
|
||
"equilibrium genotype\n",
|
||
"AA: Aa: aa=p?:2pq:q?\n",
|
||
"\n",
|
||
"after one generation!\n",
|
||
"\n",
|
||
"\n",
|
||
"Figure 1: Kink and Bend in Arabidopsis Thaliana\n",
|
||
"\n",
|
||
"\n",
|
||
"lf T’ is not significantly smaller than the fluctuation scale, the harmonic mean calculation risks\n",
|
||
"smoothing out critical periods of small population size, underestimating the true effect of genetic\n",
|
||
"drift on N.. For accurate modeling of genetic processes, T < min|[.N;] ensures that the\n",
|
||
"calculation aligns with the biological timescales of population size changes and their genetic\n",
|
||
"\n",
|
||
"consequences.\n",
|
||
"\n",
|
||
"Project 4: Phylogenetic Analysis\n",
|
||
"\n",
|
||
"Phylogenetic analysis is a crucial aspect of evolutionary biology and bioinformatics that\n",
|
||
"involves studying the evolutionary relationships among organisms. This project idea offers\n",
|
||
"opportunities for both undergraduate (UG) and postgraduate (PG) students to engage in\n",
|
||
"phylogenetic analysis, starting with constructing basic phylogenetic trees and progressing\n",
|
||
"to more complex methods.\n",
|
||
"\n",
|
||
"Bioinformatics Project Ideas — Undergraduate Level: Construct a Simple\n",
|
||
"Phylogenetic Tree\n",
|
||
"\n",
|
||
"At the undergraduate level, students can begin by constructing a basic phylogenetic tree\n",
|
||
"based on a gene or protein sequence. This project provides a foundational understanding of\n",
|
||
"phylogenetics and evolutionary relationships.\n",
|
||
"\n",
|
||
"Steps for UG Students:\n",
|
||
"\n",
|
||
"1. Gene or Protein Selection: Choose a gene or protein of interest that is well-\n",
|
||
"documented and has sequences available for multiple organisms.\n",
|
||
"\n",
|
||
"2. Sequence Alignment: Align the sequences of the chosen gene or protein using\n",
|
||
"software like ClustalW or MAFFT to identify conserved regions.\n",
|
||
"\n",
|
||
"3. Phylogenetic Tree Construction: Utilize software such as MEGA or PhyML to construct\n",
|
||
"a phylogenetic tree based on the aligned sequences. Apply methods like neighbor-\n",
|
||
"joining or maximum parsimony.\n",
|
||
"\n",
|
||
"4. Tree Visualization: Visualize the phylogenetic tree, highlighting the evolutionary\n",
|
||
"relationships among the organisms.\n",
|
||
"\n",
|
||
"5. Interpretation: Gain insights into the evolutionary history and relatedness of the\n",
|
||
"organisms based on the tree’s topology. Consider factors like branching patterns and\n",
|
||
"branch lengths.\n",
|
||
"\n",
|
||
"Postgraduate Level: Complex Phylogenetic Analyses and Co-evolutionary Patterns\n",
|
||
"\n",
|
||
"Bioinformatics Project Ideas — For postgraduate students, the project can advance to more\n",
|
||
"complex phylogenetic analyses, incorporating maximum likelihood methods and exploring\n",
|
||
"co-evolutionary patterns among genes or organisms.\n",
|
||
"\n",
|
||
"Additional Steps for PG Students:\n",
|
||
"\n",
|
||
"1. Maximum Likelihood Analysis: Learn and apply maximum likelihood methods for\n",
|
||
"phylogenetic tree reconstruction, which offer more accurate models of sequence\n",
|
||
"evolution. Software packages like RAXML or PhyML can be used.\n",
|
||
"\n",
|
||
"2. Molecular Clock Analysis: Investigate the concept of molecular clocks to estimate\n",
|
||
"divergence times between species. This involves incorporating evolutionary rates into\n",
|
||
"phylogenetic analyses.\n",
|
||
"\n",
|
||
"3. Co-evolutionary Analysis: Explore co-evolutionary patterns between genes, proteins,\n",
|
||
"or organisms using tools like Coevol or CAPS. Understand how changes in one\n",
|
||
"component correlate with changes in another.\n",
|
||
"\n",
|
||
"4. Advanced Tree Visualization: Use advanced tree visualization tools to create\n",
|
||
"informative and publication-quality figures. Highlight key evolutionary events or\n",
|
||
"relationships.\n",
|
||
"\n",
|
||
"5. Biological Interpretation: Analyze the implications of the phylogenetic findings. How\n",
|
||
"do the results contribute to our understanding of evolutionary processes, adaptations, or\n",
|
||
"co-evolutionary dynamics?\n",
|
||
"\n",
|
||
"6. Publication and Presentation: Encourage PG students to disseminate their findings\n",
|
||
"through research publications or presentations at scientific conferences, contributing to\n",
|
||
"the field of evolutionary biology and phylogenetics.\n",
|
||
"\n",
|
||
"In summary, phylogenetic analysis projects offer a captivating journey into the study of\n",
|
||
"evolutionary relationships among organisms. These projects provide valuable insights into\n",
|
||
"the evolutionary history of genes, proteins, and species, and they equip students with\n",
|
||
"essential skills in bioinformatics and computational biology. Additionally, complex\n",
|
||
"phylogenetic analyses enable postgraduate students to explore cutting-edge methods and\n",
|
||
"contribute to our understanding of co-evolutionary dynamics in biology.\n",
|
||
"\n",
|
||
"Project 5: Drug Discovery and Virtual Screening\n",
|
||
"\n",
|
||
"Drug discovery is a multidisciplinary field that combines biology, chemistry, and\n",
|
||
"computational methods to identify and design potential drug candidates. This project idea\n",
|
||
"provides opportunities for both undergraduate (UG) and postgraduate (PG) students to\n",
|
||
"explore the exciting world of drug discovery, starting with basic virtual screening\n",
|
||
"experiments and progressing to advanced structure-based drug design.\n",
|
||
"\n",
|
||
"Undergraduate Level: Basic Virtual Screening\n",
|
||
"\n",
|
||
"At the undergraduate level, students can start by learning about drug databases and\n",
|
||
"conducting basic virtual screening experiments to identify potential drug candidates. This\n",
|
||
"project offers an introduction to the concepts and tools used in drug discovery.\n",
|
||
"\n",
|
||
"Steps for UG Students:\n",
|
||
"\n",
|
||
"1. Drug Database Exploration: Familiarize yourself with drug databases like PubChem or\n",
|
||
"DrugBank. Select a target protein of interest, preferably one with known drug-binding\n",
|
||
"sites.\n",
|
||
"\n",
|
||
"2. Ligand Preparation: Retrieve ligand molecules (small compounds) from the database\n",
|
||
"that may potentially bind to your target protein. Prepare the ligands by removing any\n",
|
||
"irrelevant atoms or functional groups.\n",
|
||
"\n",
|
||
"3. Protein-Ligand Docking: Utilize software tools like AutoDock or PyRx to perform\n",
|
||
"\n",
|
||
"2-IV\n",
|
||
"\n",
|
||
"Figure 1: Kink and Bend in Arabidopsis Thaliana\n",
|
||
"\n",
|
||
"> Science. 2009 Oct 9;326(5950):289-93. doi: 10.1126/science.1181369.\n",
|
||
"\n",
|
||
"Comprehensive mapping of long-range interactions\n",
|
||
"reveals folding principles of the human genome\n",
|
||
"\n",
|
||
"Erez Lieberman-Aiden ’, Nynke L van Berkum, Louise Williams, Maxim Imakaev, Tobias Ragoczy,\n",
|
||
"Agnes Telling, Ido Amit, Bryan R Lajoie, Peter J Sabo, Michael O Dorschner, Richard Sandstrom,\n",
|
||
"Bradley Bernstein, M A Bender, Mark Groudine, Andreas Gnirke, John Stamatoyannopoulos,\n",
|
||
"Leonid A Mirny, Eric S Lander, Job Dekker\n",
|
||
"\n",
|
||
"Affiliations + expand\n",
|
||
"PMID: 19815776 PMCID: PMC2858594 DOI: 10.1126/science.1181369\n",
|
||
"\n",
|
||
"Abstract\n",
|
||
"\n",
|
||
"We describe Hi-C, a method that probes the three-dimensional architecture of whole genomes by\n",
|
||
"coupling proximity-based ligation with massively parallel sequencing. We constructed spatial\n",
|
||
"proximity maps of the human genome with Hi-C at a resolution of 1 megabase. These maps confirm\n",
|
||
"the presence of chromosome territories and the spatial proximity of small, gene-rich chromosomes.\n",
|
||
"We identified an additional level of genome organization that is characterized by the spatial\n",
|
||
"segregation of open and closed chromatin to form two genome-wide compartments. At the\n",
|
||
"megabase scale, the chromatin conformation is consistent with a fractal globule, a knot-free,\n",
|
||
"polymer conformation that enables maximally dense packing while preserving the ability to easily\n",
|
||
"fold and unfold any genomic locus. The fractal globule is distinct from the more commonly used\n",
|
||
"globular equilibrium model. Our results demonstrate the power of Hi-C to map the dynamic\n",
|
||
"conformations of whole genomes.\n",
|
||
"\n",
|
||
"Figure 4 Genetic separation between\n",
|
||
"population pairs. (a) Relative cross\n",
|
||
"coalescence rates in and out of Africa.\n",
|
||
"African-non-African pairs are shown in red,\n",
|
||
"and pairs within Africa are shown in purple.\n",
|
||
"(b) Relative cross coalescence rates between\n",
|
||
"populations outside Africa. European—East\n",
|
||
"Asian pairs are shown in blue, Asian-MXL\n",
|
||
"pairs are shown in green, and other\n",
|
||
"non-African pairs are shown in other\n",
|
||
"\n",
|
||
"colors, as indicated. The pairs that include\n",
|
||
"MXL are masked to include only the putative\n",
|
||
"Native American components. In a and b,\n",
|
||
"the most recent population separations\n",
|
||
"\n",
|
||
"are inferred from eight haplotypes, that is,\n",
|
||
"four haplotypes from each population, and\n",
|
||
"corresponding pairs are indicated by a\n",
|
||
"\n",
|
||
"cross. (c) Comparison of the African—non-\n",
|
||
"African split with simulations of clean splits.\n",
|
||
"We simulated three scenarios, at split times\n",
|
||
"50,000, 100,000 and 150,000 years ago.\n",
|
||
"The comparison demonstrates that the history\n",
|
||
"of relative cross coalescence rate between\n",
|
||
"African and non-African ancestors\n",
|
||
"\n",
|
||
"is incompatible with a clean split model\n",
|
||
"\n",
|
||
"and suggests it progressively decreased from\n",
|
||
"\n",
|
||
"Relative cross coalescence rate\n",
|
||
"\n",
|
||
"Relative cross coalescence rate ©\n",
|
||
"\n",
|
||
"0.8\n",
|
||
"\n",
|
||
"0.6\n",
|
||
"\n",
|
||
"O4\n",
|
||
"\n",
|
||
"0.2\n",
|
||
"\n",
|
||
"— MXL-YRI\n",
|
||
"— CEU-YRI\n",
|
||
"— CHB-YRI\n",
|
||
"— CEU-MKK\n",
|
||
"— CEU-LWK\n",
|
||
"~ YRI-MKKT\n",
|
||
"= LWK-MKKt\n",
|
||
"= YRI-LWkt\n",
|
||
"\n",
|
||
"10°\n",
|
||
"\n",
|
||
"Time (years ago)\n",
|
||
"\n",
|
||
"100\n",
|
||
"\n",
|
||
"Time (x1 o years ago)\n",
|
||
"\n",
|
||
"150\n",
|
||
"\n",
|
||
"a\n",
|
||
"fs 1.0\n",
|
||
"2\n",
|
||
"2 08 — CHB-CEU\n",
|
||
"8 ~ MXL-CEU\n",
|
||
"8 0.6 — CHB-MXL\n",
|
||
"8 — GIH-MXL\n",
|
||
"8 04 = CHB-GIH\n",
|
||
"3 — GIH-CEut\n",
|
||
"2 02 - CHB-UPT!\n",
|
||
"= CEU-TSI\n",
|
||
"2 o CEU-TSI\n",
|
||
"10°\n",
|
||
"200\n",
|
||
"® 100\n",
|
||
"~ CEU-YRI Fy\n",
|
||
"~ 50,000 years ago, %b 50\n",
|
||
"simulation XK\n",
|
||
"— 100,000 years ago, 3 20\n",
|
||
"simulation E\n",
|
||
"= 150,000 years ago, 10\n",
|
||
"\n",
|
||
"200\n",
|
||
"\n",
|
||
"simulation\n",
|
||
"\n",
|
||
"250\n",
|
||
"\n",
|
||
"beyond 150,000 years ago to approximately 50,000 years ago. (d) Schematic of population separations. Timings of splits, population separations,\n",
|
||
"gene flow and bottleneck are shown along a logarithmic axis of time.\n",
|
||
"\n",
|
||
"\n",
|
||
"© aman — nano ./Downloads/assignment/Ecoli_|\n",
|
||
"\n",
|
||
"fi/Ecoli_hifi_genome.gff — 208x63\n",
|
||
"\n",
|
||
"nment/Ecoli_hifi/Ecoli_hifi_genome.gff\n",
|
||
"\n",
|
||
"ile: ./Downloads/as\n",
|
||
"\n",
|
||
"Ww PICO 5.09\n",
|
||
"\n",
|
||
"i#gff-version 3\n",
|
||
"\n",
|
||
"##sequence-region tig@0000001 1\n",
|
||
"\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tige0eee0e1\n",
|
||
"tigeeeee0e1\n",
|
||
"\n",
|
||
"Wie) Get Help\n",
|
||
"Wed Exit\n",
|
||
"\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"minced:@.2.0\n",
|
||
"\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"Prodigal: 002006\n",
|
||
"\n",
|
||
"465\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"CRI\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"cDS\n",
|
||
"\n",
|
||
"7533\n",
|
||
"\n",
|
||
"99\n",
|
||
"1718\n",
|
||
"2811\n",
|
||
"5892\n",
|
||
"7393\n",
|
||
"7888\n",
|
||
"8982\n",
|
||
"9643\n",
|
||
"10258\n",
|
||
"11177\n",
|
||
"11567\n",
|
||
"12412\n",
|
||
"13701\n",
|
||
"14611\n",
|
||
"16038\n",
|
||
"16693\n",
|
||
"17210\n",
|
||
"17540\n",
|
||
"18250\n",
|
||
"18726\n",
|
||
"19756\n",
|
||
"20511\n",
|
||
"21277\n",
|
||
"22479\n",
|
||
"23565\n",
|
||
"25018\n",
|
||
"25799\n",
|
||
"26529\n",
|
||
"26863\n",
|
||
"27693\n",
|
||
"28797\n",
|
||
"29615\n",
|
||
"30377\n",
|
||
"33014\n",
|
||
"33225\n",
|
||
"33615\n",
|
||
"35767\n",
|
||
"36774\n",
|
||
"37895\n",
|
||
"38158\n",
|
||
"39034\n",
|
||
"39596\n",
|
||
"40182\n",
|
||
"40790\n",
|
||
"42619\n",
|
||
"43560\n",
|
||
"45279\n",
|
||
"45821\n",
|
||
"46585\n",
|
||
"46988\n",
|
||
"47617\n",
|
||
"49050\n",
|
||
"50764\n",
|
||
"51926\n",
|
||
"52606\n",
|
||
"54986\n",
|
||
"\n",
|
||
"SPR\n",
|
||
"\n",
|
||
"We) WriteOut\n",
|
||
"We) Justify\n",
|
||
"\n",
|
||
"1643\n",
|
||
"\n",
|
||
"2452\n",
|
||
"\n",
|
||
"5477\n",
|
||
"\n",
|
||
"7400\n",
|
||
"\n",
|
||
"7875\n",
|
||
"\n",
|
||
"8979\n",
|
||
"\n",
|
||
"9656\n",
|
||
"\n",
|
||
"10242\n",
|
||
"11175\n",
|
||
"11461\n",
|
||
"12329\n",
|
||
"13449\n",
|
||
"14609\n",
|
||
"16038\n",
|
||
"16643\n",
|
||
"17016\n",
|
||
"17521\n",
|
||
"18250\n",
|
||
"18729\n",
|
||
"19775\n",
|
||
"20517\n",
|
||
"21137\n",
|
||
"22416\n",
|
||
"23471\n",
|
||
"24929\n",
|
||
"25794\n",
|
||
"26437\n",
|
||
"26900\n",
|
||
"27696\n",
|
||
"28601\n",
|
||
"29564\n",
|
||
"30271\n",
|
||
"32938\n",
|
||
"33148\n",
|
||
"33578\n",
|
||
"35693\n",
|
||
"36777\n",
|
||
"37895\n",
|
||
"38167\n",
|
||
"39030\n",
|
||
"39384\n",
|
||
"40057\n",
|
||
"40793\n",
|
||
"42616\n",
|
||
"43542\n",
|
||
"45269\n",
|
||
"45821\n",
|
||
"46588\n",
|
||
"46995\n",
|
||
"47458\n",
|
||
"49041\n",
|
||
"50507\n",
|
||
"51777\n",
|
||
"52453\n",
|
||
"54858\n",
|
||
"56119\n",
|
||
"\n",
|
||
"tet et eteetse\n",
|
||
"\n",
|
||
"tet et etetetsei\n",
|
||
"\n",
|
||
"i\n",
|
||
"\n",
|
||
"tet etetesti\n",
|
||
"\n",
|
||
"++H1\n",
|
||
"\n",
|
||
"F\n",
|
||
"\n",
|
||
"SPBV2VVDVVVOVVO\n",
|
||
"\n",
|
||
"PBYWDVDDWDD WDD VDD DD VDD VV VDD VDDD DVD VDDVDDVDDVDVDVDVDVDVDVDVDVDVVVVVVOVOQ:\n",
|
||
"\n",
|
||
"Wii Read File\n",
|
||
"Wil) Where is\n",
|
||
"\n",
|
||
"ID=KBOCNLJJ_00001; eC_number=1.8.1.2;Name=cysI_1;db_xref=COG:C0G0155; gene=cysI_1;inference=ab initio prediction:Prodigal:002006,$\n",
|
||
"ID=KBOCNLJJ_00002; eC_number=1.8.4.8;Name=cysH_1;db_xref=COG:C0G0175; gene=cysH_1;inference=ab initio prediction:Prodigal:002006,$\n",
|
||
"ID=KBOCNLJJ_00003; eC_number=3.1.-.-—;Name=ygcB_1;db_xref=COG:C0G1203; gene=ygcB_1;inference=ab initio prediction:Prodigal:002006,$\n",
|
||
"ID=KBOCNLJJ_00004;Name=casA_1;gene=casA_1;inference=ab initio prediction:Prodigal:002006,similar to AA sequence:UniProtKB:Q4690$\n",
|
||
"ID=KBOCNLJJ_@0005 ; Name=casB_1;gene=casB_1;inference=ab initio prediction:Prodigal:002006,similar to AA sequence:UniProtKB:P7663$\n",
|
||
"ID=KBOCNLJJ_00006;Name=casC_1;gene=casC_1;inference=ab initio prediction:Prodigal:002006,similar to AA sequence:UniProtKB:Q4689$\n",
|
||
"ID=KBOCNLJJ_@0007 ; Name=casD_1;gene=casD_1;inference=ab initio prediction:Prodigal:002006,similar to AA sequence:UniProtKB:Q4689$\n",
|
||
"ID=KBOCNLJJ_00008; eC_number=3.1. j;Name=casE_1;gene=casE_1;inference=ab initio prediction:Prodigal:002006,similar to AA sequen$\n",
|
||
"ID=KBOCNLIJJ_00009; eC_number=3.1. j;Name=ygbT_1;db_xref=COG:C0G1518; gene=ygbT_1;inference=ab initio prediction:Prodigal:002006,$\n",
|
||
"ID=KBOCNLJJ_00010; eC_number=3.1.-.-—;Name=ygbF_1;gene=ygbF_1;inference=ab initio prediction:Prodigal:002006,similar to AA sequen$\n",
|
||
"note=CRISPR with 13 repeat units;rpt_family=CRISPR;rpt_type=direct\n",
|
||
"\n",
|
||
"ID=KBOCNLJJ_00011;inference=ab initio prediction: Prodigal : 002006; locus_tag=KBOCNLJJ_00011;product=hypothetical protein\n",
|
||
"ID=KBOCNLJJ_00012; eC_number=2.7.7.4;Name=cysD_1;db_xref=COG:C0G0175; gene=cysD_1;inference=ab initio prediction:Prodigal:002006,$\n",
|
||
"ID=KBOCNLJJ_00013; eC_number=2.7.7.4;Name=cysN; db_xref=COG:C0G2895; gene=cysN;inference=ab initio prediction:Prodigal: 002006, simi$\n",
|
||
"ID=KBOCNLJJ_00014; eC_number=2.7.1.25;Name=cysC; db_xref=COG:C0G@529; gene=cysC;inference=ab initio prediction:Prodigal: 002006, sim$\n",
|
||
"ID=KBOCNLJJ_00015 ; Name=ygbE; gene=ygbE;inference=ab initio prediction:Prodigal:002006,similar to AA sequence:UniProtKB:P46141;1lo$\n",
|
||
"ID=KBOCNLJJ_00016;Name=ftsB; db_xref=COG:C0G2919; gene=ftsB;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_00017; eC_number=2.7.7.60;Name=ispD; db_xref=COG:C0G1211; gene=ispD;inference=ab initio prediction:Prodigal: 002006, sim$\n",
|
||
"ID=KBOCNLJJ_00018; eC_number=4.6.1.12;Name=ispF; db_xref=COG:C0G@245; gene=ispF;inference=ab initio prediction:Prodigal: 002006, sim$\n",
|
||
"ID=KBOCNLJJ_00019; eC_number=5.4.99.27;Name=truD; db_xref=COG:C0G0585; gene=truD; inference=ab initio prediction:Prodigal:002006,si$\n",
|
||
"ID=KBOCNLJJ_00020; eC_number=3.1.3.5;Name=surE; db_xref=COG:C0G0496; gene=surE;inference=ab initio prediction:Prodigal: 002006, simi$\n",
|
||
"ID=KBOCNLJJ_00021; eC_number=2.1.1.77;Name=pcm; db_xref=COG:C0G2518; gene=pcm; inference=ab initio prediction:Prodigal: 002006, simil$\n",
|
||
"ID=KBOCNLJJ_00022;Name=n1pD_1; db_xref=COG:C0G@739; gene=nlpD_1;inference=ab initio prediction:Prodigal:002006,similar to AA sequ$\n",
|
||
"ID=KBOCNLJJ_00023;Name=rpoS; db_xref=COG:C0G0568; gene=rpoS;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_00024;Name=ygbN; db_xref=COG:C0G2610;gene=ygbN; inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_00025; eC_number=5.3.1.35;Name=otnI; db_xref=COG:C0G3622; gene=otnI;inference=ab initio prediction:Prodigal: 002006, sim$\n",
|
||
"ID=KBOCNLJJ_00026; eC_number=4.1.1.104;Name=otnC;gene=otnC;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_0@0027; eC_number=2.7.1.217;Name=otnK_1;db_xref=COG:C0G3395; gene=otnK_1;inference=ab initio prediction:Prodigal:00200$\n",
|
||
"ID=KBOCNLJJ_00028; eC_number=2.7.1.217;Name=otnK_2;db_xref=COG:C0G3395; gene=otnK_2;inference=ab initio prediction:Prodigal:00200$\n",
|
||
"ID=KBOCNLJJ_00029; eC_number=1.1.1.411;Name=1tnD; gene=1tnD;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_00030;Name=g1lcR;db_xref=COG:C0G1349; gene=glcR;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_00031; eC_number=3.1.3.16;Name=pphB; db_xref=COG:C0G@639; gene=pphB; inference=ab initio prediction:Prodigal: 002006, sim$\n",
|
||
"ID=KBOCNLJJ_00032;Name=mutS;db_xref=COG:C0G0249; gene=mutS;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_00033;inference=ab initio prediction: Prodigal: 002006; locus_tag=KBOCNLJJ_00033;product=hypothetical protein\n",
|
||
"ID=KBOCNLJJ_00034;inference=ab initio prediction: Prodigal : 002006; locus_tag=KBOCNLJJ_00034;product=hypothetical protein\n",
|
||
"ID=KBOCNLJJ_00035 ; Name=fh1A; db_xref=COG:C0G3604;gene=fhlA;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLIJJ_00036; eC_number=4.2.1.—;Name=hypE; db_xref=COG:C0G@309; gene=hypE;inference=ab initio prediction:Prodigal: 002006, simi$\n",
|
||
"ID=KBOCNLJJ_00037 ; Name=hypD; db_xref=COG:C0G0409; gene=hypD; inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_00038; Name=hypC; db_xref=COG:C0G0298; gene=hypC;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLIJJ_00039 ; Name=hypB; db_xref=COG:C0G0378; gene=hypB; inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_@0040 ; Name=hypA; db_xref=COG:C0G0375; gene=hypA;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_@0041;Name=hycA;gene=hycA;inference=ab initio prediction:Prodigal:002006,similar to AA sequence:UniProtKB:P@AEV4; 1lo$\n",
|
||
"ID=KBOCNLJJ_00042; eC_number=1.-. j;Name=hyfA_1; db_xref=COG:C0G1142; gene=hyfA_1;inference=ab initio prediction:Prodigal:002006,$\n",
|
||
"ID=KBOCNLJJ_00043; eC_number=7.1.1.—;Name=ndhB_1;gene=ndhB_1;inference=ab initio prediction:Prodigal:002006,protein motif :HAMAP:$\n",
|
||
"ID=KBOCNLJJ_00044;Name=hycD; db_xref=COG:C0G0650;gene=hycD;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_@0045 ; Name=hycE; db_xref=COG:C0G3261; gene=hycE;inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_00046; eC_number=7.1.1.—;Name=ndhI_1;gene=ndhI_1;inference=ab initio prediction:Prodigal:002006,protein motif :HAMAP:$\n",
|
||
"ID=KBOCNLJJ_00047 ; Name=hycG_1; db_xref=COG:C0G3260; gene=hycG_1;inference=ab initio prediction:Prodigal:002006,similar to AA sequ$\n",
|
||
"ID=KBOCNLJJ_00048;inference=ab initio prediction: Prodigal: 002006; locus_tag=KBOCNLJJ_00048;product=hypothetical protein\n",
|
||
"ID=KBOCNLJJ_0@0049; eC_number=3.4.23.51;Name=hycI ;db_xref=COG:C0G0680;gene=hycI;inference=ab initio prediction:Prodigal:002006,si$\n",
|
||
"ID=KBOCNLJJ_@0050; eC_number=3.2.1.86;Name=bg1H_1;db_xref=COG:C0G2723; gene=bg1H_1;inference=ab initio prediction:Prodigal:002006$\n",
|
||
"ID=KBOCNLJJ_00051; Name=bg1F_1;db_xref=COG:C0G1263; gene=bg1F_1;inference=ab initio prediction:Prodigal:002006,similar to AA sequ$\n",
|
||
"ID=KBOCNLJJ_00052;Name=ascG; db_xref=COG:C0G1609; gene=ascG; inference=ab initio prediction:Prodigal:002006,similar to AA sequence$\n",
|
||
"ID=KBOCNLJJ_00053; eC_number=1.-.-.-—;Name=hyfA_2;db_xref=COG:C0G1142;gene=hyfA_2;inference=ab initio prediction:Prodigal:002006,$\n",
|
||
"ID=KBOCNLJJ_00054; eC_number=6.2.-—.—;Name=hypF; db_xref=COG:C0G@068; gene=hypF;inference=ab initio prediction:Prodigal: 002006, simi$\n",
|
||
"ID=KBOCNLJJ_00055; eC_number=1.18.1.-—;Name=norw; db_xref=COG:C0G1251; gene=norW; inference=ab initio prediction:Prodigal: 002006, sim$\n",
|
||
"\n",
|
||
"bad Prev Pg Wag Cut Text wie Cur Pos\n",
|
||
"WA) Next Pg wig) UnCut Text Way To Spell\n",
|
||
"\n",
|
||
"\n",
|
||
"tion divergence as a function of divergence time\n",
|
||
"\n",
|
||
"bt (generators\n",
|
||
"\n",
|
||
"Ot (gene ations\n",
|
||
"\n",
|
||
"\n",
|
||
"© Pupiisn\n",
|
||
"\n",
|
||
"10-\n",
|
||
"\n",
|
||
"group\n",
|
||
"° 1G\n",
|
||
"\n",
|
||
"BOUBUBA %LZ 'ZOd\n",
|
||
"\n",
|
||
"\n",
|
||
"Figure 1 MSMC locally infers branch lengths a Recombination\n",
|
||
"\n",
|
||
"and coalescence times from observed\n",
|
||
"\n",
|
||
"mutations. (a) Schematic of the model. Total branch length T Time\n",
|
||
"Local genealogies change along the sequences (past)\n",
|
||
"by recombination events that rejoin branches of First coalescence t\n",
|
||
"\n",
|
||
"the tree, according to the SMC’ model®®. (hidden state) %\n",
|
||
"The pattern of mutations depends on the %\n",
|
||
"\n",
|
||
"genealogy, with few mutations on branches % a SS\n",
|
||
"with recent coalescences and more mutations\n",
|
||
"in deeper branches. The hidden states of the\n",
|
||
"model are the time to the first coalescence and\n",
|
||
"the identity of the two sequences participating\n",
|
||
"in the first coalescence. (b) MSMC can locally\n",
|
||
"infer its hidden states, shown by the posterior\n",
|
||
"probability with color. In black, we plot the\n",
|
||
"first coalescence time as generated by the\n",
|
||
"simulation. This local inference works well\n",
|
||
"\n",
|
||
"for two, four and eight haplotypes. As more 300\n",
|
||
"haplotypes are used, the typical time to the Position (kb)\n",
|
||
"first coalescence event decreases, whereas the 4 haplotypes\n",
|
||
"typical segment length increases.\n",
|
||
"\n",
|
||
"cs\n",
|
||
"\n",
|
||
"Log\n",
|
||
"\n",
|
||
"First coalescence fy...\n",
|
||
"\n",
|
||
"of the sample size (M), <t> = 2/(M(M — 1)), in\n",
|
||
"units of 2No generations (Fig. 1b and Online\n",
|
||
"Methods), where No is the long-term average\n",
|
||
"effective population size. Here we demonstrate\n",
|
||
"\n",
|
||
"0 200 400 600 800 1,000 1,200 1,400\n",
|
||
"application of our model on up to 8 haplotypes, Position (kb)\n",
|
||
"which allows us to study changes in popula- 8 haplotypes\n",
|
||
"tion size occurring as recently as 70 genera- 0.15\n",
|
||
"tions ago. As a special case of MSMC for two\n",
|
||
"haplotypes, we provide a new implementation\n",
|
||
"of PSMC that we call PSMC’ because it uses\n",
|
||
"the SMC’ model, which accounts for recombi-\n",
|
||
"nation events between segments with the same\n",
|
||
"time to coalescence®. PSMC’ accurately esti- 500 1,000 1,500 2,000 2,500\n",
|
||
"mates the recombination rate (Supplementary Position (kb)\n",
|
||
"Fig. 1), which is not the case for PSMC’.\n",
|
||
"\n",
|
||
"First coalescence tj,.\n",
|
||
"\n",
|
||
"S\n",
|
||
"o\n",
|
||
"\n",
|
||
"0.05\n",
|
||
"\n",
|
||
"First coalescence tj...\n",
|
||
"\n",
|
||
"Ayiqeqosd 10N0}s0q\n",
|
||
"\n",
|
||
"What excites you about doing science?\n",
|
||
"\n",
|
||
"What excites you about doing science?\n",
|
||
"do you have? Please describe a past ex\n",
|
||
"your drive for scientific inquiry. {max 3C\n",
|
||
"\n",
|
||
"COURSEWORK 4 6\n",
|
||
"DL: check the Moodle athe\n",
|
||
"\n",
|
||
"7 >\n",
|
||
"\n",
|
||
"Towards complete and error-free genome assemblies of\n",
|
||
"\n",
|
||
"all vertebrate species\n",
|
||
"1.Pick one of main themes . t Pp\n",
|
||
"\n",
|
||
"MORE VIDEOS\n",
|
||
"[BREE TA\n",
|
||
"\n",
|
||
"TECH\n",
|
||
"Pm i) 35:57/37:42 © @ & Voulube ++\n",
|
||
"\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"—\n",
|
||
"- : =\n",
|
||
". -\n",
|
||
"*\n",
|
||
"ee\n",
|
||
"\n",
|
||
"Effects of Population Size on Genetic Diversity Metrics\n",
|
||
"\n",
|
||
"“To understand how population growth, dactne, and stability influence genetic diversity, we consider\n",
|
||
"ther effects on tres kay mats:\n",
|
||
"\n",
|
||
"+x (Theta n): The average numberof pairwise cifferences between sequences.\n",
|
||
"+ 8W (Theta Watterson}: A measure based on the number af segregating sites.\n",
|
||
"‘+ Tojima's D: A statistical test that compares 8 and 6W to detect deviations from neutral\n",
|
||
"\n",
|
||
"evolution,\n",
|
||
"\n",
|
||
"“These simplified scenarios illustrate how population size changes impact genetic variation.\n",
|
||
"\n",
|
||
"Scenario 1: Population Growth\n",
|
||
"\n",
|
||
"Description:\n",
|
||
"‘When @ population expands rapidly, many rare alleles appear due to the racent increase in inevicuals.\n",
|
||
"\n",
|
||
"‘Assumptions (Hypothetical Values):\n",
|
||
"\n",
|
||
"+ on\n",
|
||
"\n",
|
||
"(Pairwise citferences are low since most sequences are very similar due tothe\n",
|
||
"expansion)\n",
|
||
"\n",
|
||
"+ 8W-=4 (More segregating sites appear due to expansion)\n",
|
||
"+ Tajima’sb Calculation:\n",
|
||
"\n",
|
||
"O, = Ow 2-4\n",
|
||
"” Sandard deviation 1\n",
|
||
"\n",
|
||
"Since 6r < 8W, Tajma’s Dis negative.\n",
|
||
"\n",
|
||
"‘conclusion:\n",
|
||
"Population growth results in 6x < OW and Tajima’s D <0, indicating an excoss of rare variants\n",
|
||
"\n",
|
||
"Scenario 2: Population Deciit\n",
|
||
"\n",
|
||
"Description:\n",
|
||
"\n",
|
||
"e (Bottleneck)\n",
|
||
"\n",
|
||
"‘A population experiences a drastic reduction in size, leacing to the loss of rare alleles and an\n",
|
||
"‘overrpresentation of comman ones.\n",
|
||
"\n",
|
||
"‘Assumptions (Hypothetical Values):\n",
|
||
"+ on\n",
|
||
"\n",
|
||
"(Pairwise citferonces are higher because the remaining sequences are more divergent)\n",
|
||
"+ eW=4 (Fewer segregating sites due tothe bottleneck)\n",
|
||
"+ Tajima’sb Calculation:\n",
|
||
"\n",
|
||
"0, = Ow. on4\n",
|
||
"~ Wandard deviation ~ 1\n",
|
||
"\n",
|
||
"Since 6x > BW, Tajma’s Dis postive\n",
|
||
"\n",
|
||
"D =2\n",
|
||
"\n",
|
||
"‘conclusion:\n",
|
||
"\n",
|
||
"Population dectne results in @x > BW and Taima's D > 0, suggesting a loss of rae aloes.\n",
|
||
"\n",
|
||
"Scenario 3: Constant Population Size\n",
|
||
"\n",
|
||
"Description:\n",
|
||
"[A population remains stable ver time, with alle frequencies evolving neutral\n",
|
||
"\n",
|
||
"‘Assumptions (Hypothetical Values):\n",
|
||
"+ on\n",
|
||
"\n",
|
||
"(Pairwise citferances match the expected diversity level)\n",
|
||
"+ @W=5 (Segregating sites align with a stable population)\n",
|
||
"+ Tajima’sb Calculation:\n",
|
||
"\n",
|
||
"0, — Ow\n",
|
||
"Randard deviation 1\n",
|
||
"\n",
|
||
"Since 6x = BW, Tajima’s Dis zor,\n",
|
||
"\n",
|
||
"D\n",
|
||
"\n",
|
||
"‘conclusion:\n",
|
||
"\n",
|
||
"[A stable population results in 8x = 8W and Taima’s D = 0, indicating neutral evelution.\n",
|
||
"\n",
|
||
"Summary\n",
|
||
"\n",
|
||
"‘Changes in population size affect genetic variation in distinct ways:\n",
|
||
"+ Population Growth > More rave alleles > Negative Tajima’sD.\n",
|
||
"+ Population Decline > Fewer rare alleles > Positive Tajima's .\n",
|
||
"\n",
|
||
"+ Stable Population > Balanced allele frequencies > Tajima’s D= 0.\n",
|
||
"\n",
|
||
"‘These tends help researchers infer historical der raphic changes in populations from genetic data,\n",
|
||
"\n",
|
||
"Fragment\n",
|
||
"\n",
|
||
"= ————\n",
|
||
"\n",
|
||
"=. —,\n",
|
||
"> sequencing *——— a\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"This slide focuses on the effect of slow fluctuations in population size on the effective\n",
|
||
"population size (V.) and emphasizes the conditions under which the harmonic mean formula for\n",
|
||
"N- applies. Slow fluctuations occur when the time period of interest (Z’) is much shorter than the\n",
|
||
"minimum population size (min[N;]) across the fluctuation cycle. In such cases, the population\n",
|
||
"\n",
|
||
"-1\n",
|
||
"size appears relatively stable, and the harmonic mean formula (N. = (4 wh x) ) may not\n",
|
||
"\n",
|
||
"accurately represent the effective population size over longer periods. The diagram illustrates that\n",
|
||
"during slow fluctuations, the coalescent events occur more gradually, and population size changes\n",
|
||
"are less abrupt compared to rapid fluctuations. The key message is that for the harmonic mean\n",
|
||
"calculation to be meaningful, the time scale of observation (Z') must be significantly smaller than\n",
|
||
"the scale of population size changes, ensuring accurate modeling of genetic drift and coalescence\n",
|
||
"\n",
|
||
"processes over generations.\n",
|
||
"\n",
|
||
"= F, compares the average expected heterozygosity of\n",
|
||
"individual subpopulations (S) to the total expected\n",
|
||
"heterozygosity if the subpopulations are combined (T).\n",
|
||
"\n",
|
||
"py, = n= Hs) -\\-(%)\n",
|
||
"H, H,\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"\n",
|
||
"Translate\n",
|
||
"\n",
|
||
"99\n",
|
||
"\n",
|
||
"Citation\n",
|
||
"Generator\n",
|
||
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|
||
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|
||
"\n",
|
||
"QuillBot\n",
|
||
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|
||
"\n",
|
||
"a\n",
|
||
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|
||
"QuillBot for\n",
|
||
"macOS\n",
|
||
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|
||
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|
||
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|
||
"118\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"(4) Perfect your writing in all your favorite apps with QuillBot for macOS\n",
|
||
"\n",
|
||
"Al Detector\n",
|
||
"\n",
|
||
"English French Spanish German Ally\n",
|
||
"\n",
|
||
"factors. Also some of the differential genes were associated with compartment switches too, W\n",
|
||
"especially upregulated ones, but these were not statistically significant. It was seen that\n",
|
||
"upregulated genes had more significant structural links as compared to the downregulated\n",
|
||
"genes. Although the smaller number of downregulated genes may reduce statistical power,\n",
|
||
"\n",
|
||
"the consistent lack of enrichment across architectural levels suggests that their regulation is\n",
|
||
"\n",
|
||
"less connected to architecture reorganization.\n",
|
||
"\n",
|
||
"Taken together, the transcriptional changes in the PRC2 mutant are linked to regions\n",
|
||
"undergoing architectural reorganisation in the form of loops, weak insulation, and\n",
|
||
"compartment switches. It was also noted that not all architectural changes connected to\n",
|
||
"transcriptional changes, and not all DEGs aligned with structural reorganization, implying\n",
|
||
"presence of additional regulatory layers. Chromatin architecture provides a necessary\n",
|
||
"framework for gene regulation, but it may not be sufficient on its own.\n",
|
||
"\n",
|
||
"with many being linked to upregulated genes. These results indicate that the effect of PRC2\n",
|
||
"\n",
|
||
"loss on transcription is not restricted to newly formed contacts but extends across different\n",
|
||
"\n",
|
||
"categories of loop stability. Moreover, genes were often contacted by multiple loops, in some\n",
|
||
"cases over ten, pointing to a high degree of regulatory connectivity. The reason for this\n",
|
||
"multiplicity or redundancy was not explored in terms of log fold change. Some genes had\n",
|
||
"\n",
|
||
"oD\n",
|
||
"\n",
|
||
"2,909 Words @ Analysis complete\n",
|
||
"\n",
|
||
"Want your text to sound more authentic?\n",
|
||
"\n",
|
||
"Model Version: v5.7.1\n",
|
||
"\n",
|
||
"2%\n",
|
||
"\n",
|
||
"of text is likely Al ©\n",
|
||
"© QuillBot\n",
|
||
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|
||
"Al\n",
|
||
"\n",
|
||
"Al-generated @\n",
|
||
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|
||
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|
||
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|
||
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|
||
"\n",
|
||
"¥Y Understanding your results\n",
|
||
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|
||
"Human\n",
|
||
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|
||
"< Share\n",
|
||
"\n",
|
||
"@ Tue 14. Oct 22:33\n",
|
||
"\n",
|
||
"a\n",
|
||
"\n",
|
||
"&} Apps and Extensio...\n",
|
||
"\n",
|
||
"& Download =\n",
|
||
"\n",
|
||
"Feedback\n",
|
||
"\n",
|
||
"D\n",
|
||
"\n",
|
||
"History\n",
|
||
"\n",
|
||
"oO 22%\n",
|
||
"0%\n",
|
||
"0%\n",
|
||
"\n",
|
||
"98%\n",
|
||
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|
||
"Refine with Paraphra\n",
|
||
"\n",
|
||
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|
||
"\n",
|
||
"ae (eG\n",
|
||
"\n",
|
||
"\n",
|
||
"Figure 2 Testing MSMC on simulated data. a b ~ 10,000 years ago. Sees\n",
|
||
"\n",
|
||
"(a) To test the resolution of MSMC applied to = Simulation — 40,000 years ago, 8 haplotypes\n",
|
||
"two, four and eight haplotypes, we simulated — 2 haplotypes +++» 100,000 years ago, simulation\n",
|
||
"a series of exponential population growths and — 4 haplotypes — 100,000 years ago, 4 haplotypes\n",
|
||
"\n",
|
||
"— 100,000 years ago, 8 haplotypes\n",
|
||
"\n",
|
||
"— 8 haplotypes\n",
|
||
"\n",
|
||
"declines, each changing the population size by\n",
|
||
"a factor of ten. MSMC recovers the resulting\n",
|
||
"zigzag pattern (on a double-logarithmic plot)\n",
|
||
"in different times, depending on the number\n",
|
||
"of haplotypes. With two haplotypes, MSMC\n",
|
||
"infers the population history from 40,000 to\n",
|
||
"\n",
|
||
"3 million years ago, whereas, with four and\n",
|
||
"eight haplotypes, it infers the population\n",
|
||
"history from 8,000 to 30,000 years ago ra 7 ;\n",
|
||
"and from 2,000 to 50,000 years ago, 10 10 10 10 10 10\n",
|
||
"respectively. (b) Model estimates from two Time (years ago) Time (years ago)\n",
|
||
"\n",
|
||
"simulated population splits 10,000 and 100,000 years ago. The dotted lines plot the expected relative cross coalescence rate between the two\n",
|
||
"populations before and after the splits. Maximum-likelihood estimates are shown in red (four haplotypes) and purple (eight haplotypes). As expected,\n",
|
||
"four haplotypes yield good estimates for the older split, whereas eight haplotypes give better estimates for the more recent split.\n",
|
||
"\n",
|
||
"ond\n",
|
||
"o\n",
|
||
"\n",
|
||
"°\n",
|
||
"©\n",
|
||
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|
||
"10°\n",
|
||
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|
||
"°\n",
|
||
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|
||
"\n",
|
||
"10*\n",
|
||
"\n",
|
||
"Effective population size\n",
|
||
"°\n",
|
||
"ny\n",
|
||
"\n",
|
||
"Relative cross coalescence rate\n",
|
||
"o\n",
|
||
"o\n",
|
||
"\n",
|
||
"°\n",
|
||
"\n",
|
||
"\n",
|
||
"eco (ff = > OQ VD BG monkeytype.com Ws. Search SEARXNG-NALAKATH eo @°\n",
|
||
"\n",
|
||
"New merch store now open, including a limited edition metal keycap! monkeytype.store x\n",
|
||
"\n",
|
||
"70\n",
|
||
"94%\n",
|
||
"\n",
|
||
"cautich 80 176/7/86/0 82% 30s\n",
|
||
"\n",
|
||
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|
||
"\n",
|
||
"GO @QZx,gQvnvuds» HM BOC BD.\n",
|
||
"\n",
|
||
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|
||
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|
||
"Workspaces v <_|/txtai: @ All-in-one a Examples - txtai () txtai/examples/13_Similar () txtai/examples/38_Introdu Mc Introducing RAG with txta *K Image caption generation (m) Monkeytype | A minimalis' > +\n",
|
||
"\n",
|
||
"0@e S CI CQ Reset —O——$—$——— 100% = 21:20\n",
|
||
"\n",
|
||
"g\n",
|
||
"&\n",
|
||
"\n",
|
||
"‘oUala Cel (urgor IS Freguiatea DY a\n",
|
||
"\n",
|
||
"ABA complex network of interacting second\n",
|
||
"Se messengers, pH, membrane potential,\n",
|
||
"protein phosphorylation, ion channel\n",
|
||
"NOE 10 activity — and more!!\n",
|
||
"\n",
|
||
"\n",
|
||
"Variable population size\n",
|
||
"\n",
|
||
"Beyond the Standard Neutral Model\n",
|
||
"\n",
|
||
"Slow fluctuations\n",
|
||
"in population size : = =\n",
|
||
"\n",
|
||
"4 Need:\n",
|
||
"A, 7 T << min[N, |\n",
|
||
"\n",
|
||
"\n",
|
||
"@ = Safari File\n",
|
||
"\n",
|
||
"Edit View\n",
|
||
"\n",
|
||
"History\n",
|
||
"\n",
|
||
"¥% © & @ &#\n",
|
||
"\n",
|
||
">\n",
|
||
"cod\n",
|
||
"\n",
|
||
"Q\n",
|
||
"\n",
|
||
"S Mon3.Nov 14:17\n",
|
||
"\n",
|
||
"-\n",
|
||
"eco -\n",
|
||
"\n",
|
||
"rp | A pipeline for...\n",
|
||
"\n",
|
||
"HUMAN CELL ATLAS,\n",
|
||
"DATA EXPLORER\n",
|
||
"\n",
|
||
"<\n",
|
||
"\n",
|
||
"Q tINIT tutorial...\n",
|
||
"\n",
|
||
"Bookmarks Window Help\n",
|
||
"0O9eW¢s8\n",
|
||
"Ce) The integrate... © Swagger UI\n",
|
||
"\n",
|
||
"explore.data.humancellatlas.org\n",
|
||
"\n",
|
||
"ce) Choose Expor...\n",
|
||
"\n",
|
||
"Explore > Export Selected Data > Download Selecte..\n",
|
||
"\n",
|
||
"Download Selected Data Using “curl”\n",
|
||
"\n",
|
||
"io Census data...\n",
|
||
"\n",
|
||
"io The integrate...\n",
|
||
"\n",
|
||
"Gea ©\n",
|
||
"\n",
|
||
"(=) HLCA/docs/fa...\n",
|
||
"\n",
|
||
"e Files from projects with access \"required\" will be excluded from this export.\n",
|
||
"\n",
|
||
"Download via curt\n",
|
||
"Species\n",
|
||
"\n",
|
||
"Mus musculus\n",
|
||
"\n",
|
||
"Homo sapiens\n",
|
||
"\n",
|
||
"File Type\n",
|
||
"Name\n",
|
||
"bai\n",
|
||
"\n",
|
||
"bam\n",
|
||
"\n",
|
||
"cmd.exe\n",
|
||
"\n",
|
||
"quest curl Command\n",
|
||
"\n",
|
||
"File Count\n",
|
||
"\n",
|
||
"22.0k\n",
|
||
"\n",
|
||
"22.0k\n",
|
||
"\n",
|
||
"22\n",
|
||
"\n",
|
||
"File Size\n",
|
||
"\n",
|
||
"39.15 GB\n",
|
||
"\n",
|
||
"3.98 TB\n",
|
||
"\n",
|
||
"24.66 GB\n",
|
||
"\n",
|
||
"The generated curl command is compatible with the Bash shell on Mac and Linux systems,\n",
|
||
"and the Command shell on Windows systems, and will remain valid for seven days.\n",
|
||
"\n",
|
||
"Current Query\n",
|
||
"\n",
|
||
"Access\n",
|
||
"true\n",
|
||
"\n",
|
||
"Genus Species\n",
|
||
"Homo sapiens\n",
|
||
"\n",
|
||
"Paired End\n",
|
||
"true\n",
|
||
"\n",
|
||
"Nucleic Acid Source\n",
|
||
"single cell\n",
|
||
"\n",
|
||
"File Source\n",
|
||
"DCP/2 Analysis\n",
|
||
"\n",
|
||
"File Format\n",
|
||
"loom\n",
|
||
"\n",
|
||
"Selected Data Summary\n",
|
||
"\n",
|
||
"Estimated Cells\n",
|
||
"570.8k\n",
|
||
"\n",
|
||
"File Size\n",
|
||
"24.66 GB\n",
|
||
"\n",
|
||
"Files\n",
|
||
"22\n",
|
||
"\n",
|
||
"Projects\n",
|
||
"19\n",
|
||
"\n",
|
||
"Species\n",
|
||
"Homo sapiens\n",
|
||
"\n",
|
||
"Donors\n",
|
||
"45\n",
|
||
"\n",
|
||
"Disease Status (Donor)\n",
|
||
"4 disease statuses\n",
|
||
"\n",
|
||
"Specimens\n",
|
||
"775\n",
|
||
"\n",
|
||
"Disease Status (Specimen)\n",
|
||
"3 disease statuses\n",
|
||
"\n",
|
||
"Anatomical Entity\n",
|
||
"12 anatomical entities\n",
|
||
"\n",
|
||
"Organ Part\n",
|
||
"14 organ parts\n",
|
||
"\n",
|
||
"Library Construction Method\n",
|
||
"2 library construction methods\n",
|
||
"\n",
|
||
"Paired End\n",
|
||
"true\n",
|
||
"\n",
|
||
"Downloaded and exported data is\n",
|
||
"\n",
|
||
"@ ChatGPT - Dr...\n",
|
||
"\n",
|
||
"Pastebin.com...\n",
|
||
"\n",
|
||
"a\n",
|
||
"© @ +\n",
|
||
"\n",
|
||
"Ce) Download Sel\n",
|
||
"\n",
|
||
"Help & Documentation + e@\n",
|
||
"\n",
|
||
"(\n",
|
||
"\n",
|
||
"v Please select\n",
|
||
"Chalmers tekniska hoegskola AB\n",
|
||
"Goteborgs Universitet\n",
|
||
"Handelshégskolan i Stockholm (HHS)\n",
|
||
"Hégskolan i Halmstad\n",
|
||
"Karlstads universitet\n",
|
||
"Karolinska Institutet\n",
|
||
"Kungliga Tekniska H6gskolan (KTH)\n",
|
||
"Linképings universitet (LiU)\n",
|
||
"Linnéuniversitetet\n",
|
||
"Lulea tekniska universitet\n",
|
||
"Lunds universitet\n",
|
||
"Stockholms universitet\n",
|
||
"Sveriges lantbruksuniversitet (SLU)\n",
|
||
"Umea universitet\n",
|
||
"Uppsala universitet\n",
|
||
"\n",
|
||
"Genetic context of bacterial aqpN genes\n",
|
||
"\n",
|
||
"44 AQPNsinKEGG (45% in arsenic resistance operons — 55 % in NO operon)\n",
|
||
"57 AQPNsin NCBI (68% in arsenic resistance operons — 32 % in NO operon)\n",
|
||
"As(V)\n",
|
||
"\n",
|
||
"As(II!)\n",
|
||
"\n",
|
||
"Progeny genotypes\n",
|
||
"\n",
|
||
"p2\n",
|
||
"PH\n",
|
||
"\n",
|
||
"=\n",
|
||
"—\n",
|
||
"eo\n",
|
||
"\n",
|
||
"(1/4)H2 (1/2)H2 (1/4)H2\n",
|
||
"HQ HQ\n",
|
||
"\n",
|
||
"2(P+(1/2)H)\n",
|
||
"(P rads (Q +(1/2)H) (Q oo\n",
|
||
"\n",
|
||
"\n",
|
||
"Arbuscule development\n",
|
||
"\n",
|
||
"a cee. ees\n",
|
||
"SbtM1 Gene\n",
|
||
"ceeennnnnnennnsnnenseneesennenennsenneenenennseneenensesnenasenennsecunmeaneneanees expression\n",
|
||
"BCPI\n",
|
||
"\n",
|
||
"PM Cell wall\n",
|
||
"\n",
|
||
"C | stage! Stage Il Stage Ill Stage lV Stage V\n",
|
||
"PPA Cell entry Birdsfoot Mature arbuscule Collapsed arbuscule\n",
|
||
"t t t t TL\n",
|
||
"CYCLOPS RAM1, RAM2 OsPT13\n",
|
||
"DIS\n",
|
||
"RED\n",
|
||
"\n",
|
||
"3 VAMPs @ PT4 tT ] SbtM1 P BCPI\n",
|
||
"\n",
|
||
"Scientific interests\n",
|
||
"\n",
|
||
"Research Interests:\n",
|
||
"\n",
|
||
"Description: At this stage, which research areas and scientific questions are you most interested in exploring during your PhD? Please describe the techniques and\n",
|
||
"methods you are currently considering. (min. 100 words - max. 400 words)\n",
|
||
"\n",
|
||
"CURRENT research area (Primary) Computational Biology, Genomes and Evolution\n",
|
||
"\n",
|
||
"Scientific Question:\n",
|
||
"Click here to enter your comments (What excites you about doing science?)\n",
|
||
"Applicant's answer:\n",
|
||
"\n",
|
||
"Epigenetic basis of complex Spontaneous epimutations Epigenetic clocks Machine learning of 3D\n",
|
||
"\n",
|
||
"traits chromatin contacts\n",
|
||
"\n",
|
||
"Genomic and epigenomic basis\n",
|
||
"\n",
|
||
"of high-alpine adaptation\n",
|
||
"\n",
|
||
"Usefulness of crosses\n",
|
||
"\n",
|
||
"Selection of Parents\n",
|
||
"\n",
|
||
"U, = Cj +R;\n",
|
||
"\n",
|
||
"m midparent value, perfect predictor of cj with additive gene action\n",
|
||
"\n",
|
||
"4 and absence of epistasis\n",
|
||
"\n",
|
||
"0.7 ¢ (0.8\n",
|
||
"\n",
|
||
"Vinyl\n",
|
||
"Rij = iho,\n",
|
||
"\n",
|
||
"i prediction difficult\n",
|
||
"\n",
|
||
"\n",
|
||
"Method\n",
|
||
"\n",
|
||
"Heterozygosity\n",
|
||
"\n",
|
||
"Nucleotide diversity (tt)\n",
|
||
"\n",
|
||
"Site Frequency Spectrum (SFS)\n",
|
||
"Linkage Disequilibrium (LD)\n",
|
||
"Tajima’s D\n",
|
||
"\n",
|
||
"Runs of Homozygosity (ROH)\n",
|
||
"\n",
|
||
"Effective Population Size (Ne)\n",
|
||
"\n",
|
||
"Signature of Bottleneck\n",
|
||
"\n",
|
||
"Decreased heterozygosity\n",
|
||
"\n",
|
||
"Reduced genetic diversity\n",
|
||
"\n",
|
||
"Skew toward intermediate alleles\n",
|
||
"\n",
|
||
"Increased LD, slower decay\n",
|
||
"\n",
|
||
"Positive values due to allele frequency shift\n",
|
||
"Longer ROH in bottlenecked populations\n",
|
||
"\n",
|
||
"Sudden decrease in Ne\n",
|
||
"\n",
|
||
"3. What sort of growth pattern in the epidermis would explain\n",
|
||
"the kink formation?\n",
|
||
"\n",
|
||
"°\n",
|
||
"3.1. Is there any cellular evidence for PD growth signal in epidermis?\n",
|
||
"\n",
|
||
"\n",
|
||
"Genome vv Tracks ¥ Sample Info v Session v Share Bookmark Save Image Circular View v Help v\n",
|
||
"\n",
|
||
"IGV oxford_e...me.fasta tig00000002:1,989,819-1,993,234 Q 3,416 bp (Select Tracks ) (Crosshairs )(_Center Line )(TrackLabels) @ +)\n",
|
||
"1,990 kb j 1,991 kb j 1,992 kb j 1,993 kb\n",
|
||
"AQ 0 EA A MY TAY A AY a\n",
|
||
"|= SS SS en |\n",
|
||
"tnaB tnaA mnmE_1\n",
|
||
"\n",
|
||
"INSTITUTE\n",
|
||
"\n",
|
||
"Heng igv.org UCSan Diego fe BROAD\n",
|
||
"\n",
|
||
"\n",
|
||
"Genome vv Tracks ¥ Sample Info v Session v Share Bookmark Save Image Circular View v Help v\n",
|
||
"\n",
|
||
"GV oxford_e...me.fasta _ tig00000002:2,754-6,178 Q 3,425 bp (Select Tracks )( Crosshairs )( Center Line ){ Track Labels ) (—) auu==® +)\n",
|
||
"3 kb j 4 kb j 5 kb j 6 kb\n",
|
||
"LSA A A 8 a\n",
|
||
"po ee ss sss | %\n",
|
||
"dadA_1 IKAOHOFJ_00007 fadR_1\n",
|
||
"pac Pi\n",
|
||
"dadA_2 fadR_2\n",
|
||
"\n",
|
||
"igv.org UCSanDiego EEBROAD\n",
|
||
"\n",
|
||
"INSTITUTE\n",
|
||
"\n",
|
||
"i al\n",
|
||
"\n",
|
||
"Leaf Hi-C K4me3 HiChIP K27me3 HiChIP\n",
|
||
"\n",
|
||
"eQTL-gene\n",
|
||
"links >20 kb |\n",
|
||
"\n",
|
||
"shuffled pairs\n",
|
||
"\n",
|
||
"\n",
|
||
"Leaf Hi-C\n",
|
||
"\n",
|
||
"N=OS (fihered) 347 (unique) 347 (total), PALL = 0,909\n",
|
||
"\n",
|
||
"eQTL-gene —\n",
|
||
"links >20 kb .\n",
|
||
"\n",
|
||
"shuffled pairs\n",
|
||
"\n",
|
||
"\n",
|
||
"Figure 3 Inference of population size from whole- —— YRI (Nigeria) —— CHB (China)\n",
|
||
"\n",
|
||
". : . — MKK (Kenya) — JPT (Japan)\n",
|
||
"genome sequences. (a) Population size estimates —— LWK (Kenya) — GIH (N. India\n",
|
||
"indivi — CEU (N.Europe) —— MXL (Mexico — CEU (N. Europe)\n",
|
||
"\n",
|
||
"from four haplotypes (two phased individuals) a — fsiaayy pe) — we re Rletive American) b ~ TSI (aly)\n",
|
||
"from each of nine populations. The dashed line — CHB (China)\n",
|
||
"was generated from a reduced data set of only the © g 10° — JPT (Japan)\n",
|
||
"Native American components of the MXL genomes. 3 ae — GIH (N. India)\n",
|
||
"\n",
|
||
". < 5 10 — YRI (Nigeria)\n",
|
||
"Estimates from two haplotypes for CEU and YRI g FS — LWK (Kenya)\n",
|
||
"are shown for comparison as dotted lines. 2 2 108\n",
|
||
"N, Northern. (b) Population size estimates from a a\n",
|
||
"eight haplotypes (four phased individuals) from the g 2 108\n",
|
||
"same populations as in a but excluding MXL and 3 E 10!\n",
|
||
"\n",
|
||
"Ww\n",
|
||
"\n",
|
||
"MKK. In contrast to estimates with four haplotypes,\n",
|
||
"estimates are more recent. For comparison, we\n",
|
||
"show the result from four haplotypes for CEU,\n",
|
||
"\n",
|
||
"10° 104 10°\n",
|
||
"CHB and YRI as dotted lines. Time (years ago) Time (years ago)\n",
|
||
"\n",
|
||
"\n",
|
||
"Leaf Hi-C K4me3 HiChIP K27me3 HiChIP\n",
|
||
"\n",
|
||
"face mar rapa mat\n",
|
||
"\n",
|
||
"eQTL-gene\n",
|
||
"links >20 kb\n",
|
||
"\n",
|
||
"shuffled pairs :\n",
|
||
"\n",
|
||
"\n",
|
||
"(mustache_aman) [papantonis1@gwdu1@1 aman]$ awk '$1 == $9 {print $1}' GE02457_dots_5kb.bedpe | sort | unig -c && wc -1 GE02457_dots_5kb.bedpe\n",
|
||
"842 chri\n",
|
||
"413 chr1e\n",
|
||
"465 chri1\n",
|
||
"442 chr12\n",
|
||
"244 chri3\n",
|
||
"254 chri4\n",
|
||
"234 chris\n",
|
||
"174 chri16\n",
|
||
"248 chr17\n",
|
||
"196 chri8\n",
|
||
"122 chri9\n",
|
||
"817 chr2\n",
|
||
"196 chr2e\n",
|
||
"\n",
|
||
"81 chr21\n",
|
||
"78 chr22\n",
|
||
"731 chr3\n",
|
||
"\n",
|
||
"594 chr4\n",
|
||
"609 chr5\n",
|
||
"631 chr6é\n",
|
||
"478 chr7\n",
|
||
"\n",
|
||
"505 chr8&\n",
|
||
"349 chr9\n",
|
||
"\n",
|
||
"184 chrx\n",
|
||
"\n",
|
||
"8888 GE02457_dots_5kb.bedpe\n",
|
||
"\n",
|
||
"ge Plant Epigenome\n",
|
||
"Browser\n",
|
||
"\n",
|
||
"sect\n",
|
||
"\n",
|
||
"anc seg 3\n",
|
||
"\n",
|
||
"meg :\n",
|
||
"Bea meri\n",
|
||
"\n",
|
||
"rae ‘\n",
|
||
"\n",
|
||
"irsenabnitninpmeyiityrr afl mnie ahi\n",
|
||
"\n",
|
||
"\n",
|
||
"Chromosomes\n",
|
||
"\n",
|
||
"o\n",
|
||
"\n",
|
||
"8\n",
|
||
"\n",
|
||
"ae\n",
|
||
"\n",
|
||
"Show\n",
|
||
"\n",
|
||
"Observed\n",
|
||
"\n",
|
||
"Normalization (Obs | Ctrl)\n",
|
||
"\n",
|
||
"None ¢\n",
|
||
"\n",
|
||
"Bala...\n",
|
||
"\n",
|
||
"Resolution (BP)\n",
|
||
"\n",
|
||
"I rrdtdot ttt td\n",
|
||
"2.5MB 500KB 100KB 25KB 5KB 1KB 200BP\n",
|
||
"\n",
|
||
"OMB\n",
|
||
"\n",
|
||
"\n",
|
||
"Genetic context of bacterial aqpN genes TUT\n",
|
||
"\n",
|
||
"44 AQPNsinKEGG (45% in arsenic resistance operons — 55 % in NO operon)\n",
|
||
"\n",
|
||
"57 AQPNs in NCBI (68% in arsenic resistance operons — 32 % in NO operon)\n",
|
||
"\n",
|
||
"As(V)\n",
|
||
"\n",
|
||
"transporter\n",
|
||
"\n",
|
||
"As(ltl)\n",
|
||
"\n",
|
||
"= > > | >> >>>\n",
|
||
"f GipF Aqpz |\n",
|
||
"\n",
|
||
"Crop\n",
|
||
"Physiology\n",
|
||
"56\n",
|
||
"\n",
|
||
"\n",
|
||
"clonalAbundance\n",
|
||
"\n",
|
||
"We can also examine the relative distribution of clones by abundance. Here clonalAbundance() will produce a line graph with a total\n",
|
||
"number of clones by the number of instances within the sample or run. Like above, we can also group.by this by vectors within the\n",
|
||
"contig object using the group.by variable in the function.\n",
|
||
"\n",
|
||
"clonalAbundance(combined. TCR,\n",
|
||
"cloneCall = \"gene\",\n",
|
||
"scale = FALSE)\n",
|
||
"\n",
|
||
"5000\n",
|
||
"4000\n",
|
||
"Samples\n",
|
||
"— P17B\n",
|
||
"3 PI7L\n",
|
||
"5 3000\n",
|
||
"ro) — P18B\n",
|
||
"ao) — P18L\n",
|
||
"3 — P19B\n",
|
||
"2000\n",
|
||
"5 — PI19L\n",
|
||
"Zz\n",
|
||
"— P20B\n",
|
||
"— P20L\n",
|
||
"1000\n",
|
||
"oo §\n",
|
||
"1 10 100 1000\n",
|
||
"Abundance\n",
|
||
"\n",
|
||
"clonalAbundance() output can also be converted into a density plot, which may allow for better comparisons between different\n",
|
||
"repertoire sizes, by setting scale = TRUE.\n",
|
||
"\n",
|
||
"clonalAbundance(combined.TCR, cloneCall = \"gene\", scale = TRUE)\n",
|
||
"\n",
|
||
"Gibberellin biosynthesis is well understood TUT\n",
|
||
"\n",
|
||
"core\n",
|
||
"SS\n",
|
||
") The “green revolution”\n",
|
||
"semidwarf1 rice variety is\n",
|
||
"af mutated in a GA20ox that is\n",
|
||
"expressed in shoots but not\n",
|
||
"\n",
|
||
"GAg\n",
|
||
"\n",
|
||
"a\n",
|
||
"\n",
|
||
"1\n",
|
||
"i 5, ¢ ot — ent-kaurenoic acid in reproductive tissues, ; Q\n",
|
||
"i | t Ga2q GA. leading to increased grain |\n",
|
||
"i GA GAs . yields.\n",
|
||
"a; —_—_\n",
|
||
"5A200 .\n",
|
||
"\\ GA _ Sasaki ef al. & Matsuoka, 2002, Nature\n",
|
||
"A > GA, —+ GA, —+> GAy, Spielmeyer et al. & Chandler, 2002, PNAS\n",
|
||
"”\n",
|
||
"\n",
|
||
"4 Ce Gazal\n",
|
||
"\n",
|
||
"CA» ——> GA,\n",
|
||
"\n",
|
||
"~\n",
|
||
"\n",
|
||
"GA30x\n",
|
||
"\n",
|
||
"GA\n",
|
||
"\n",
|
||
"GAs ——® GA\n",
|
||
"\n",
|
||
"Brigitte Poppenberger (TUM) Hernandez-Garcia et al & Blazquez, 2021, Sem. Cell Dev. Biol 13\n",
|
||
"\n",
|
||
"\n",
|
||
"Genome vv Tracks ¥ Sample Info v Session v Share Bookmark Save Image Circular View v Help v\n",
|
||
"\n",
|
||
"IGV oxford_e...me.fasta _ tig00000002:1,604,261-1,606,695 § Q. 2,435 bp (Select Tracks ) (\"Crosshairs )(_Center Line )(TrackLabels) @ iE +)\n",
|
||
"\n",
|
||
"C D)\n",
|
||
"\n",
|
||
"604,300 bp 1,604,500 bp 1,604,700 bp 1,604,900 bp 1,605,100 bp 1,605,300 bp 1,605,500 bp 1,605,700 bp 1,605,900 bp 1,606,100 bp 1,606,300 bp 1,606,500 bp 1,606,\n",
|
||
"L i 1 L L L 1 L L L 1 L L L 1 L L L 1 L L L 1 L L L 1 L L L 1 L L L 1 L L L 1 L L i 1 L L L 1 L\n",
|
||
"\n",
|
||
"%\n",
|
||
"ee Pe | ZZ\n",
|
||
"\n",
|
||
"pdeC_1 IKAOHOFJ_01847 ssb\n",
|
||
"\n",
|
||
"pdeC_2\n",
|
||
"\n",
|
||
"Investigating the Impact of Hexaploidization on Gene Expression in Oat: in this project, we compare gene expression in hexaploid oat\n",
|
||
"species with their tetraploid ancestors. The aim is to explore how the addition of a new genome through hybridization has affected gene\n",
|
||
"regulation.\n",
|
||
"\n",
|
||
"Results - 1. Confocal Images\n",
|
||
"\n",
|
||
"~ Adaxial oi1\n",
|
||
"\n",
|
||
"Nucelus ss __-» Abaxial oi2\n",
|
||
"\n",
|
||
"Adaxial ii1. <——\n",
|
||
"\n",
|
||
"Abaxial ii2 __—» Chalaza\n",
|
||
"\n",
|
||
"—+ Funiculus\n",
|
||
"\n",
|
||
"chromosome1 x1 x2 chromosome2 yl y2 color observed\n",
|
||
"expected_bottom_left expected_donut expected_horizontal expected_vertical\n",
|
||
"fdr_bottom_left fdr_donut fdr_horizontal fdr_vertical\n",
|
||
"number_collapsed centroid1 centroid2 radius\n",
|
||
"\n",
|
||
"eoo <— > OQ VD G monkeytype.com Ws Search SEARXNG-NALAKATH eave @ @ ~™@®\n",
|
||
"ay & a Ab New merch store now open, including a limited edition metal keycap! monkeytype.store x\n",
|
||
"\n",
|
||
"monkeytype\n",
|
||
"\n",
|
||
"73\n",
|
||
"96%\n",
|
||
"\n",
|
||
"cautich 76 182/3/1/0 84% 30s\n",
|
||
"\n",
|
||
"GCO@Qe2® ag Avnud9g HSBTOC BD\n",
|
||
"\n",
|
||
"english\n",
|
||
"&\n",
|
||
"S Workspaces v (mi) Monkeytype | A minimalisti + Vv\n",
|
||
"0&8 S CI CQ Reset Om 100% 11:12\n",
|
||
"\n",
|
||
"3.3 SUVRS affects the gene region more than the TE region\n",
|
||
"\n",
|
||
"\n",
|
||
"~*~\n",
|
||
"\n",
|
||
"@ Safari File Edit View History Bookmarks Develop Window Help @ ne) ¥@6© €& @) F Q ® Fri21.Nov 14:15\n",
|
||
"eecax m&-< ‘on © {1| @ 2g pax-db.org Ga co Oo +\n",
|
||
"{0.0} Yes. The paper states that t... iG] geckopy/geckopy/experimen... FE] geckopy — geckopy 0.0.1 do... a= PaxDb - Help 2 https://pax-db.org/download... a PaxDb - Download iN} FragPipe workflows | FragPipe\n",
|
||
"\n",
|
||
"paxdb®° PaxDb: Protein Abundance Database\n",
|
||
"\n",
|
||
"dary\n",
|
||
"Pio,\n",
|
||
"\n",
|
||
"x protein(s) id/name\n",
|
||
"\n",
|
||
"PaxDb Downloads\n",
|
||
"\n",
|
||
"Accessory files\n",
|
||
"\n",
|
||
"e All datasets can be found here paxdb-abundance-files.zip (~31MB).\n",
|
||
"\n",
|
||
"¢ Protein sequences fasta file can be found here paxdb-protein-sequences.zip (~498MB).\n",
|
||
"¢ Mapped peptides files can be found here paxdb-mapped_peptides.zip (~193MB).\n",
|
||
"\n",
|
||
"¢ Orthologs list can be found here paxdb-orthologs.zip (~25MB).\n",
|
||
"\n",
|
||
"e UniProt mappings can be found here paxdb-uniprot-links.zip (~11MB).\n",
|
||
"\n",
|
||
"e Files from previous PaxDB versions can be found here: /downloads/\n",
|
||
"\n",
|
||
"Per-species abundance files\n",
|
||
"\n",
|
||
"ES -\n",
|
||
"\n",
|
||
"Species Datasets J?\n",
|
||
"Homo sapiens 375\n",
|
||
"Mus musculus 175\n",
|
||
"\n",
|
||
"DOWNLOAD\n",
|
||
"\n",
|
||
"COMPUTE+;\n",
|
||
"\n",
|
||
"REQUEST+*;\n",
|
||
"\n",
|
||
"Download\n",
|
||
"\n",
|
||
"9606.zip\n",
|
||
"\n",
|
||
"10090.zip\n",
|
||
"\n",
|
||
"WHAT'S NEW4;\n",
|
||
"\n",
|
||
"HELP\n",
|
||
"\n",
|
||
"\n",
|
||
"First 5 rows and columns of raw genotype data:\n",
|
||
"\n",
|
||
"Cl\n",
|
||
"\n",
|
||
"dddde|\n",
|
||
"trop\n",
|
||
"\n",
|
||
"dddae\n",
|
||
"\n",
|
||
"dddd|\n",
|
||
"rrr\n",
|
||
"\n",
|
||
"ddd\n",
|
||
"\n",
|
||
"dddd|\n",
|
||
"rrr\n",
|
||
"\n",
|
||
"a)\n",
|
||
"\n",
|
||
"dadded\n",
|
||
"rrr\n",
|
||
"\n",
|
||
"eSeeooe\n",
|
||
"\n",
|
||
"dade|\n",
|
||
"\n",
|
||
"eeoo\n",
|
||
"\n",
|
||
"® -1]]]\n",
|
||
"\n",
|
||
"\n",
|
||
"AN Tene enginevelry, 5 Py weeds\n",
|
||
"- eZ Anal biota Beat dp\n",
|
||
"ate - Tyce Gear bei Oo\n",
|
||
"46, Trtwesip * Feashig UP ES\n",
|
||
"\n",
|
||
"yor\n",
|
||
"\n",
|
||
"SONGS [ab 2 S welts wort\n",
|
||
"\n",
|
||
"Coup peggy\n",
|
||
"\n",
|
||
"Repars — PDO)\n",
|
||
"Brcacvnud,\n",
|
||
"Summer school\n",
|
||
"\n",
|
||
"Reding Dalukinnoyy gprs\n",
|
||
"L¥ Pap & Stiles\n",
|
||
"Chater — Pronses\n",
|
||
"Saf & Stee Duatle fo Ui?\n",
|
||
"Anping fe Hos. Haig HG\n",
|
||
"\n",
|
||
"a\n",
|
||
"\n",
|
||
"I\n",
|
||
"I\n",
|
||
".* a\n",
|
||
"\n",
|
||
"LIEN TIE uc\n",
|
||
"\n",
|
||
"olathe id- \"4 ut ]\n",
|
||
"Figure 2 | Haplotype pattern in a region defined by SNPs that are at high\n",
|
||
"frequency in Tibetans and at low frequency in Han Chinese. Each column is\n",
|
||
"a polymorphic genomic location (95 in total), each row is a phased haplotype\n",
|
||
"(80 Han and 80 Tibetan haplotypes), and the coloured column on the left\n",
|
||
"denotes the population identity of the individuals. Haplotypes of the Denisovan\n",
|
||
"individual are shown in the top two rows (green). The black cells represent the\n",
|
||
"presence of the derived allele and the grey space represents the presence of\n",
|
||
"the ancestral allele (see Methods). The first and last columns correspond to the\n",
|
||
"first and last positions in Supplementary Table 3, respectively. The red and\n",
|
||
"blue arrows indicate the 32 sites in Supplementary Table 3. The blue arrows\n",
|
||
"represent a five-SNP haplotype block defined by the first five SNPs in the\n",
|
||
"32.7-kb region. Asterisks indicate sites at which Tibetans share a derived allele\n",
|
||
"with the Denisovan individual.\n",
|
||
"\n",
|
||
"\n",
|
||
"Building regulatory landscapes\n",
|
||
"reveals that an enhancer can recruit\n",
|
||
"cohesin to create contact domains,\n",
|
||
"engage CTCF sites and activate\n",
|
||
"distant genes\n",
|
||
"\n",
|
||
"Rinzema NJ, Sofiados k, [...], de Laat W\n",
|
||
"\n",
|
||
"Nature Structural & Molecular Biology (2022)\n",
|
||
"\n",
|
||
"[| DOWNLOAD | 2022\n",
|
||
"\n",
|
||
"Robust detection of translocations in\n",
|
||
"lymphoma FFPE samples using\n",
|
||
"targeted locus capture-based\n",
|
||
"sequencing\n",
|
||
"\n",
|
||
"Allahyar A, Pieterse M, [...], de Laat W\n",
|
||
"\n",
|
||
"NATURE COMMUNICATIONS: 12:3361\n",
|
||
"\n",
|
||
"[| DOWNLOAD | 2021\n",
|
||
"\n",
|
||
"Ready-to-use public infrastructure\n",
|
||
"for global SARS-CoV-2 monitoring\n",
|
||
"Krijger PHL, Hoek TA, [...], de Laat W, Tanenbaum M\n",
|
||
"\n",
|
||
"Nature Biotechnology 39: 1178-1184\n",
|
||
"\n",
|
||
"[| DOWNLOAD | 2021\n",
|
||
"\n",
|
||
"Novel orthogonal methods to\n",
|
||
"uncover the complexity and diversity\n",
|
||
"of nuclear architecture\n",
|
||
"\n",
|
||
"Tjalsma SJD, de Laat W\n",
|
||
"\n",
|
||
"Current Opinion in Genetics & Development: 67:10-17\n",
|
||
"\n",
|
||
"[| DOWNLOAD | 2021\n",
|
||
"\n",
|
||
"Interplay between CTCF boundaries\n",
|
||
"and a super enhancer controls\n",
|
||
"cohesin extrusion trajectories and\n",
|
||
"gene expression\n",
|
||
"\n",
|
||
"Vos ESM, Valdes-Quezada C, Huang Y [...], de Laat\n",
|
||
"Ww\n",
|
||
"\n",
|
||
"Mol. Cell 81(15):3082-3095\n",
|
||
"\n",
|
||
"[| DOWNLOAD | 2021\n",
|
||
"\n",
|
||
"How chromosome topologies get\n",
|
||
"their shape: views from proximity\n",
|
||
"ligation and microscopy methods\n",
|
||
"Huang Y, Neijts R, de Laat W\n",
|
||
"\n",
|
||
"FEBS Letters: 594 3439-3449\n",
|
||
"\n",
|
||
"[| DOWNLOAD | 2020\n",
|
||
"\n",
|
||
"Instituto Universitario de Lisboa (ISCTE IUL)\n",
|
||
"UNIVERSIDADE CATOLICA PORTUGUESA\n",
|
||
"Universidade de Coimbra\n",
|
||
"\n",
|
||
"Universidade de Evora\n",
|
||
"\n",
|
||
"Universidade de Lisboa\n",
|
||
"\n",
|
||
"Universidade do Porto\n",
|
||
"\n",
|
||
"Universidade Nova de Lisboa\n",
|
||
"\n",
|
||
"Ice ot\n",
|
||
"‘earn ere ta rao pen 2 prema ne oe [eeremsne [seen]\n",
|
||
"\n",
|
||
"FastQC: Per Sequence GC Content\n",
|
||
"Pea Samp\n",
|
||
"\n",
|
||
"Per Base N Content [aim\n",
|
||
"\n",
|
||
"‘epocenapecttancastcan poten ren an asa\n",
|
||
"\n",
|
||
"FastQC: Per Base N Content\n",
|
||
"\n",
|
||
"‘Sequence Length Distribution [a\n",
|
||
"\n",
|
||
"Mimosa equa ci ng)\n",
|
||
"\n",
|
||
"‘Sequence Duplication Levels SE (ome)\n",
|
||
"‘eae ge yer\n",
|
||
"[eeewwres [cere]\n",
|
||
"\n",
|
||
"FastQC: Sequence Duplication Levels,\n",
|
||
"\n",
|
||
"Overrepresented sequences by sample SKIN\n",
|
||
"\n",
|
||
"‘Pett arr ctonnpeericsminceanh eaten.\n",
|
||
"\n",
|
||
"Top overrepresented sequences\n",
|
||
"\n",
|
||
"‘ie onmmteeseince sr ssarde The soe 2 trent ser cern aye noosa yr\n",
|
||
"\n",
|
||
"‘Adapter Content [ZI [ome]\n",
|
||
"\n",
|
||
"‘Peamusiepenep cathe sana yay te asa en aspen enon\n",
|
||
"[eeremsne [seen]\n",
|
||
"\n",
|
||
"FastQC: Adapter Content\n",
|
||
"\n",
|
||
"\n",
|
||
"% TADS\n",
|
||
"\n",
|
||
"Sequencing technologies have been a driving force in genomics science\n",
|
||
"since the 70's.\n",
|
||
"\n",
|
||
"After reading the article De novo genome assembly: what every biologist\n",
|
||
"should know (Published: March 2012)\n",
|
||
"\n",
|
||
"Link: https://www.nature.com/articles/nmeth.1935,\n",
|
||
"\n",
|
||
"1. Pick one issue or problem that is mentioned in it. Describe it shortly with\n",
|
||
"your own words and try to produce a possible solution for it based on what\n",
|
||
"you have learnt in this course so far (it doesn't matter if your solution is\n",
|
||
"\n",
|
||
"really doable)\n",
|
||
"\n",
|
||
"2. Share your problem description and solution in TWO places:\n",
|
||
"In the discussion forum “Impact of sequencing technology\" and submit the\n",
|
||
"same text also in the task “Impact of sequencing technology”. Please, read in\n",
|
||
"\n",
|
||
"the discussion forum your peers’ answers,\n",
|
||
"\n",
|
||
"TAL\n",
|
||
"TECH\n",
|
||
"\n",
|
||
"NEXT STEPS |\n",
|
||
"\n",
|
||
"CHECK THE DEADLINES IN MOODLE\n",
|
||
"\n",
|
||
"* Read \"De novo genome assembly: what every biologist should know\"\n",
|
||
"\n",
|
||
"* Do and submit Coursework 3 (based on the lectures so far + reading).\n",
|
||
"\n",
|
||
"Once you have done all these, you may move on to the \"Week 4, Session 1\"\n",
|
||
"\n",
|
||
". 7 sad\n",
|
||
"\n",
|
||
"Ethylene induces expression of ACS genes during ripening\n",
|
||
"\n",
|
||
"ACS ACO\n",
|
||
"\n",
|
||
"SAM LEACSS ACC — > C2H, — Perception\n",
|
||
"DS\n",
|
||
"LEACS1A —\n",
|
||
"4 LEACS4 =e)\n",
|
||
"LEACS2\n",
|
||
"\n",
|
||
"Developmentally\n",
|
||
"regulated\n",
|
||
"\n",
|
||
"Brigitte Poppenberger (TUM) Plant Cell teaching tool\n",
|
||
"\n",
|
||
"OMB\n",
|
||
"\n",
|
||
"100 MB\n",
|
||
"\n",
|
||
"200 MB\n",
|
||
"\n",
|
||
"Chromosomes Show Normalization (Obs | Ctrl) Resolution (BP)\n",
|
||
"“aw “aw a a a — y,\n",
|
||
"2 Bp Observed Bala... None © Pivrb ttre teins\n",
|
||
"2.5MB 500KB 100KB 25KB 5KB 1KB 200BP\n",
|
||
"OMB 100 MB 200 MB 300 MB\n",
|
||
"\n",
|
||
"\n",
|
||
"@ Zoom Workplace\n",
|
||
"\n",
|
||
"ox\n",
|
||
"\n",
|
||
"Ww\n",
|
||
"\n",
|
||
"4\n",
|
||
"\n",
|
||
"a\n",
|
||
"\n",
|
||
"Clipboard\n",
|
||
"\n",
|
||
"11\n",
|
||
"\n",
|
||
"Slide 10 0f 14 4\n",
|
||
"\n",
|
||
"Meeting View Edit\n",
|
||
"\n",
|
||
"[==] Layout ¥\n",
|
||
"\n",
|
||
"‘© Reset\n",
|
||
"New\n",
|
||
"\n",
|
||
"Slide v Section\n",
|
||
"\n",
|
||
"Slides\n",
|
||
"\n",
|
||
"English (India)\n",
|
||
"\n",
|
||
"Cy, Accessibility: Investigate\n",
|
||
"\n",
|
||
"W4\n",
|
||
"\n",
|
||
"x\n",
|
||
"\n",
|
||
"Pre\n",
|
||
"\n",
|
||
"& 00 Ce PD Find i) A\n",
|
||
"D | 5 b S yy\n",
|
||
"ALLS o5|¥ 82 Replace v\n",
|
||
"D Swen Arrange Create PDF Create PDF and Add-ins\n",
|
||
"° soe 2 I$ Select v and Share link Share via Outlook\n",
|
||
"Font Paragraph Drawing Editing Adobe Acrobat Add-ins\n",
|
||
"\n",
|
||
"Growth : Tissue expansion\n",
|
||
"\n",
|
||
"Across stages (from 2-III to 2-V) , interval [0.75-1.00] along PD axis sees the highest tissue expansion\n",
|
||
"\n",
|
||
"U\n",
|
||
"\n",
|
||
"What sort of tissue expansion is it (isotropic or anisotropic) ?\n",
|
||
"\n",
|
||
"MAXMIN Histogram MAXMID Histogram\n",
|
||
"(0.75. 1.00} 00} oe\n",
|
||
"= 2 7\n",
|
||
"} (0.25, 0.30) 4\n",
|
||
"- Po om st 0.00, 0.25)\n",
|
||
"a =\n",
|
||
"\n",
|
||
"Average of MAXMID\n",
|
||
"\n",
|
||
"> No evidence of purely isotropic cell growth in any stage at any interval\n",
|
||
"\n",
|
||
"> Cell growth on average is anisotropic for all intervals at each stage\n",
|
||
"\n",
|
||
"“ oo\n",
|
||
"= Notes QB comments oo\n",
|
||
"\n",
|
||
"oO\n",
|
||
"\n",
|
||
"Window Help Bevwvue@8Wrt+ ort.t@goe wy Se Wed Feb 12 22:24\n",
|
||
"\n",
|
||
"\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"print(*results, sep='\\n')"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "base",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.12.7"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|