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	<title><![CDATA[BOL: Related items]]></title>
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	<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/44614/online-resources-on-must-read-papers-in-evolutionary-biology</guid>
	<pubDate>Fri, 26 Jul 2024 01:39:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/44614/online-resources-on-must-read-papers-in-evolutionary-biology</link>
	<title><![CDATA[Online resources on must-read papers in evolutionary biology]]></title>
	<description><![CDATA[<pre>Online resources on must-read papers in evolutionary biology, for a literature club.<br /><br />Below is a summary of all answers that we received.

All the best,

Jana and Xiaoyan

1.       *Nick Barton:*

- The textbook "Evolution" by Nick Barton, with resources for
  exploring the literature: Barton, N. H., Briggs, D. E. G., Eisen, J.
  A., Goldstein, D. B., &amp; Patel, N. H. (2007). Evolution. Cold Spring
  Harbor Laboratory Press.

- Papers from a course named "Classics in Evolutionary Biology":

Evolutionary Synthesis
1. Haldane, J. B. S. 1932. The causes of evolution. Longmans. New York.
   (esp. Ch. IV).
2. Fisher, R. A. 1930. The genetical theory of natural selection. Oxford
   University Press, Oxford. Selected Sections - Fundamental Theorem.

Genetic Variation
1a. Lewontin, R. C., and J. L. Hubby. 1966. A molecular approach to
the study of genic heterozygosity in natural populations. II. Amount
of variation and degree of heterozygosity in natural populations of
Drosophila pseudoobscura. Genetics. 54:595-609.

1b. Sachidandam et al. 2001. A map of human genome sequence variation
containing 1.42 million single nucleotide polymorphisms. 409: 928-33.

2. Wright S., Dobzhansky T., Hovanitz W. 1942 Genetics of natural
populations VII The allelism of lethals in the third chromosome of
Drosophila pseudoobscura. Genetics 27: 363-394.

Recombination and evolution
1. Hill, W. G., and A. Robertson. 1966. The effect of linkage on limits
to artificial selection. Genet. Res. 8:269-294.

2. Maynard Smith and Haigh. 1974. The hitch-hiking effect of a favourable
gene. Genet. Res. 23: 23-35.

Understanding sequence variation
1. Begun D. J., Aquadro C. F., 1992 Levels of naturally occurring DNA
polymorphism correlate with recombination rate in Drosophila melanogaster.
Nature 356: 519-520.

2. Green R. E., Reich D., P&auml;&auml;bo S., 2010 A draft sequence of the
Neandertal genome. Science 328: 710-722.

Quantitative Genetics:  variation in complex traits
1. Galton F., 1877 Typical laws of heredity. Nature 15: 492-495-
512-514- 532-533.

2. Turelli M., 1984 Heritable genetic variation via
mutation-selection balance: Lerch's Zeta meets the abdominal
bristle. Theor. Popul. Biol. 25: 138-193.

Quantitative Genetics:  finding the genes
1. Shrimpton A. E., Robertson A., 1988 The Isolation of polygenic factors
controlling bristle score in Drosophila melanogaster II Distribution of
third chromosome bristle effects within chromosome sections. Genetics
118: 445-459.

2. Boyle E. A., Li Y. I., Pritchard J. K., 2017 An expanded view of
complex traits: from polygenic to omnigenic. Cell 169: 1177-1186.

Neutral Evolution
1. Kimura, M. 1968. Evolutionary rate at the molecular level. Science.
217:624-626.

2a. Kern A. D., Hahn M. W., 2018 The Neutral Theory in Light of Natural
Selection. Molecular Biology and Evolution 110: 21077-6.

2b. Jensen J. D., Payseur B. A., Stephan W., Aquadro C. F., Lynch M.,
Charlesworth D., Charlesworth B., 2018 The importance of the Neutral Theory
in 1968 and 50 years on: a response to Kern and Hahn 2018. Evolution 112:
2109-4.

2c. Ellegren &amp; Galtier. 2016. Determinants of genetic diversity. Nature
Reviews Genetics.

Mutation and Genetic Variability
1. Luria, S. E., and M. Delbr&uuml;ck. 1943. Mutations of Bacteria from Virus
Sensitivity to Virus Resistance. Genetics. 28(6):491-511.

2. Hill, W G. 1982. "Rates of Change in Quantitative Traits From Fixation
of New Mutations." Proceedings of the National Academy of Sciences (U.S.A.)
79: 142-45.

Testing for selection
1. McDonald &amp; Kreitman. 1991. Adaptive protein evolution at the Adh locus
in Drosophila. Nature.

2. Begun, et al. Mol. Biol. Evol. 16, 1816-1819 (1999).

3. Siddiq et al. 2016. Experimental test and refutation of a classic case
of molecular adaptation in Drosophila melanogaster.  Nature Ecology &amp;
Evolution.

The shifting balance
1. Wright, S. 1932. The roles of mutation, inbreeding, crossbreeding and
selection in evolution. Proceedings of the VI International Congress of
Genetics: 1. pp 356-366.

2. Coyne, J.A., N.H. Barton, and M. Turelli. 1997. A critique of Wright's
shifting balance theory of evolution.  Evolution 51: 643-671.

3. Barton. 2016. Sewall Wright on Evolution in Mendelian Populations and
the "Shifting Balance". Genetics.

Evolution of Sex
1.  Muller, H.J. 1964. The relation of recombination to mutational advance.
Mutation Res. 1(1):2-9

2. McDonald et al. 2016. Sex speeds adaptation by altering the dynamics of
molecular evolution. Nature.

Kin Selection, Cooperation, and Conflict
1. Hamilton, W. D. 1964. The genetical evolution of social behaviour I.
Journal of Theoretical Biology. 7:1-52.

2. Trivers, R. L. 1974 Parent-offspring conflict. American Zoologist.
14(1):249-264.

Sexual Selection
1. Zahavi, A. 1975. Mate selection - a selection of a handicap. J. Theor.
Biol. 53:205-214.

2. Kirkpatrick, M., and Ryan, M.J. 1991. The evolution of mating
preferences and the paradox of the lek. Nature. 350:33-38.

Fitness Landscapes
1. Dean, A. 1995. A Molecular Investigation of Genotype by Environment
Interactions. Genetics. 139:19-33.

2. Costanzo et al. 2010. The Genetic Landscape of a Cell. Science.

Speciation
1. Coyne, J. A., and H. A. Orr. 1989. Patterns of speciation in Drosophila.
Evolution. 43:362-381.

2. Corbett-Detig et al. 2013. Genetic incompatibilities are widespread
within species. Nature.

2.       *Marcos Antezana:*

Valen, L. v. 1975. Energy and Evolution. University of Chicago, Department
of Biology.

3.       *Remco Folkertsma:*

1. The work by Hopi Hoekstra on local adaptation and oldfield mice

2. Poelstra, J. W., Vijay, N., Bossu, C. M., Lantz, H., Ryll, B., M&uuml;ller,
I., ... &amp; Wolf, J. B. (2014). The genomic landscape underlying phenotypic
integrity in the face of gene flow in crows. Science, 344(6190), 1410-1414.

4.       *Joshka Kaufmann and Leslie Turner*

They offer us a link to 'papers every evolutionary biologist should read',
the papers are collected by Leslie Turner.
https://static1.squarespace.com/static/53e8cb7ce4b02c4bc3aeeee4/t/5ab8fcb670a6ad55c67fcdf4/1522072758665/EvoBioClassicsRefList.pdf

5.       *Sarah Stockwell*

Matt Ridley collected classic papers in evolutionary biology and printed
part of these papers in his book Evolution (see Matt Ridley. Evolution
(Univ. of Oxford Press, 2nd edition, 2004))
</pre>]]></description>
	<dc:creator>BioStar</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/35534/awk-for-bioinformatician-and-computational-biologist</guid>
	<pubDate>Tue, 06 Feb 2018 14:54:35 -0600</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/35534/awk-for-bioinformatician-and-computational-biologist</link>
	<title><![CDATA[Awk for Bioinformatician and computational biologist]]></title>
	<description><![CDATA[<p>Awk is a programming language which allows easy manipulation of structured data and is mostly used for pattern scanning and processing. It searches one or more files to see if they contain lines that match with the specified patterns and then perform associated actions. The basic syntax is:</p><blockquote><p><br />awk '/pattern1/ {Actions}<br /> /pattern2/ {Actions}' file</p></blockquote><p><br />The working of Awk is as follows<br />Awk reads the input files one line at a time.<br />For each line, it matches with given pattern in the given order, if matches performs the corresponding action.<br />If no pattern matches, no action will be performed.<br />In the above syntax, either search pattern or action are optional, But not both.<br />If the search pattern is not given, then Awk performs the given actions for each line of the input.<br />If the action is not given, print all that lines that matches with the given patterns which is the default action.<br />Empty braces with out any action does nothing. It wont perform default printing operation.<br />Each statement in Actions should be delimited by semicolon.<br />Say you have data.tsv with the following contents:</p><p><br />$ cat data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />By default Awk prints every line from the file.</p><p><br />$ awk '{print;}' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />We print the line which matches the pattern contig3</p><p><br />$ awk '/contig3/' data/test.tsv<br />contig3 ACTTATATATATATA<br />Awk has number of builtin variables. For each record i.e line, it splits the record delimited by whitespace character by default and stores it in the $n variables. If the line has 5 words, it will be stored in $1, $2, $3, $4 and $5. $0 represents the whole line. NF is a builtin variable which represents the total number of fields in a record.</p><p><br />$ awk '{print $1","$2;}' data/test.tsv<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT</p><p>$ awk '{print $1","$NF;}' data/test.tsv<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT</p><p><br />Awk has two important patterns which are specified by the keyword called BEGIN and END. The syntax is as follows:</p><blockquote><p>BEGIN { Actions before reading the file}<br />{Actions for everyline in the file} <br />END { Actions after reading the file }</p></blockquote><p><br />For example,<br />$ awk 'BEGIN{print "Header,Sequence"}{print $1","$2;}END{print "-------"}' data/test.tsv<br />Header,Sequence<br />contig1,ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2,ACTTTATATATT<br />contig3,ACTTATATATATATA<br />contig4,ACTTATATATATATA<br />contig5,ACTTTATATATT<br />------- <br />We can also use the concept of a conditional operator in print statement of the form print CONDITION ? PRINT_IF_TRUE_TEXT : PRINT_IF_FALSE_TEXT. For example, in the code below, we identify sequences with lengths &gt; 14:</p><p>$ awk '{print (length($2)&gt;14) ? $0"&gt;14" : $0"&lt;=14";}' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG&gt;14<br />contig2 ACTTTATATATT&lt;=14<br />contig3 ACTTATATATATATA&gt;14<br />contig4 ACTTATATATATATA&gt;14<br />contig5 ACTTTATATATT&lt;=14<br />We can also use 1 after the last block {} to print everything (1 is a shorthand notation for {print $0} which becomes {print} as without any argument print will print $0 by default), and within this block, we can change $0, for example to assign the first field to $0 for third line (NR==3), we can use:</p><p>$ awk 'NR==3{$0=$1}1' data/test.tsv<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT<br />You can have as many blocks as you want and they will be executed on each line in the order they appear, for example, if we want to print $1 three times (here we are using printf instead of print as the former doesn't put end-of-line character),</p><p>$ awk '{printf $1"\t"}{printf $1"\t"}{print $1}' data/test.tsv<br />contig1 contig1 contig1<br />contig2 contig2 contig2<br />contig3 contig3 contig3<br />contig4 contig4 contig4<br />contig5 contig5 contig5 <br />Although, we can also skip executing later blocks for a given line by using next keyword:</p><p>$ awk '{printf $1"\t"}NR==3{print "";next}{print $1}' data/test.tsv<br />contig1 contig1<br />contig2 contig2<br />contig3 <br />contig4 contig4<br />contig5 contig5</p><p>$ awk 'NR==3{print "";next}{printf $1"\t"}{print $1}' data/test.tsv<br />contig1 contig1<br />contig2 contig2</p><p>contig4 contig4<br />contig5 contig5<br />You can also use getline to load the contents of another file in addition to the one you are reading, for example, in the statement given below, the while loop will load each line from test.tsv into k until no more lines are to be read:</p><p>$ awk 'BEGIN{while((getline k &lt;"data/test.tsv")&gt;0) print "BEGIN:"k}{print}' data/test.tsv<br />BEGIN:contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />BEGIN:contig2 ACTTTATATATT<br />BEGIN:contig3 ACTTATATATATATA<br />BEGIN:contig4 ACTTATATATATATA<br />BEGIN:contig5 ACTTTATATATT<br />contig1 ACTGTCTGTCACTGTGTTGTGATGTTGTGTGTG<br />contig2 ACTTTATATATT<br />contig3 ACTTATATATATATA<br />contig4 ACTTATATATATATA<br />contig5 ACTTTATATATT <br />You can also store data in the memory with the syntax VARIABLE_NAME[KEY]=VALUE which you can later use through for (INDEX in VARIABLE_NAME) command:</p><p>$ awk '{i[$1]=1}END{for (j in i) print j"&lt;="i[j]}' data/test.tsv<br />contig1&lt;=1<br />contig2&lt;=1<br />contig3&lt;=1<br />contig4&lt;=1<br />contig5&lt;=1</p>]]></description>
	<dc:creator>Poonam Mahapatra</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/42552/bioinformatics-workbook</guid>
	<pubDate>Tue, 05 Jan 2021 22:42:32 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/42552/bioinformatics-workbook</link>
	<title><![CDATA[bioinformatics workbook]]></title>
	<description><![CDATA[<p><span>This books assumes that the reader has some knowledge of biology and basic understanding of the Unix command line. However, for the beginner, the appendix contains introductory material and tips/tricks for common bioinformatic problems, that is referred to for more information throughout the book.</span></p>
<p>https://bioinformaticsworkbook.org/</p><p>Address of the bookmark: <a href="https://bioinformaticsworkbook.org/" rel="nofollow">https://bioinformaticsworkbook.org/</a></p>]]></description>
	<dc:creator>biogeek</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43323/biostarhandbook</guid>
	<pubDate>Fri, 27 Aug 2021 01:31:01 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43323/biostarhandbook</link>
	<title><![CDATA[biostarhandbook]]></title>
	<description><![CDATA[<p>Nice book collection for bioinformatician ... highly recommended.</p><p>Address of the bookmark: <a href="https://www.biostarhandbook.com/" rel="nofollow">https://www.biostarhandbook.com/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38169/amstat-display-statistics-of-large-sequence-files-from-next-generation-sequencing-projects</guid>
	<pubDate>Fri, 09 Nov 2018 13:34:56 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38169/amstat-display-statistics-of-large-sequence-files-from-next-generation-sequencing-projects</link>
	<title><![CDATA[AMStat: display statistics of large sequence files from next generation sequencing projects]]></title>
	<description><![CDATA[<p><span>SAMStat is an efficient C program to quickly display statistics of large sequence files from next generation sequencing projects. When applied to&nbsp;</span><a href="http://samstat.sourceforge.net/#about">SAM/BAM</a><span>&nbsp;files all statistics are reported for unmapped, poorly and accurately mapped reads separately. This allows for identification of a variety of problems, such as remaining linker and adaptor sequences, causing poor mapping. Apart from this SAMStat can be used to verify individual processing steps in large analysis pipelines.</span></p><p>Address of the bookmark: <a href="http://samstat.sourceforge.net/" rel="nofollow">http://samstat.sourceforge.net/</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/3013/python-and-biopython-tutorial</guid>
	<pubDate>Fri, 23 Aug 2013 06:47:40 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/3013/python-and-biopython-tutorial</link>
	<title><![CDATA[Python and BioPython Tutorial]]></title>
	<description><![CDATA[<p>A quickstart tutorial that allows to become familiar with the Python language. The exercises expect knowledge of basic concepts of programming. A group of 2nd year computer science students with no previous Python knowledge required 60'-90' to complete the exercises. With about 3 hours time, the exercise is suitable for non-programmers as well.</p><p>Address of the bookmark: <a href="http://www.biotnet.org/training-materials/python-programmers" rel="nofollow">http://www.biotnet.org/training-materials/python-programmers</a></p>]]></description>
	<dc:creator>Manshi Raghubanshi</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/news/view/20331/type-hinting</guid>
	<pubDate>Fri, 09 Jan 2015 22:26:13 -0600</pubDate>
	<link>https://bioinformaticsonline.com/news/view/20331/type-hinting</link>
	<title><![CDATA[Type Hinting]]></title>
	<description><![CDATA[<p>Python creator Guido van Rossum&rsquo;s proposal for static type-checking annotations is inching closer to reality, and the feature has taken on a new name: type hinting.</p><p><img src="http://sdtimes.com/wp-content/uploads/2015/01/0107.sdt-python-typehinting.png" alt="image" width="619" height="219" style="border: 0px; border: 0px;"></p><p>Back in August, van Rossum published a proposal on the Python mailing list recommending type-checking annotations as a valuable feature for the next version of Python to improve the performance of editors and IDEs, linter capabilities, standard notation, and refactoring. Van Rossum&rsquo;s <a href="http://lwn.net/Articles/627558/">latest proposal</a>, posted late last month, outlined plans to publish a Python Enhancement Proposal (PEP) in early January to put the feature now known as type hinting on track for inclusion in Python 3.5, slated for release this September.</p><p>Reference</p><p>https://quip.com/r69HA9GhGa7J</p>]]></description>
	<dc:creator>Pranjali Yadav</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/30018/bipype</guid>
	<pubDate>Thu, 01 Dec 2016 08:47:38 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/30018/bipype</link>
	<title><![CDATA[bipype]]></title>
	<description><![CDATA[<p><span>Bipype is a very useful program, which prepare a lot of types of bioinformatics analyses. There are three input options: amplicons, WGS (whole genome sequences) and metatranscriptomic data. If amplicons are input data, then bipype does reconstruction and pairs merging. After that biodiversity is searching. There are two types of searching depending on the amplicons types (ITS or 16S). If WGS are chosen, then bipype finds the SA coordinates of the input reads and generates alignments in the SAM format given single-end reads, aligns reads to reference sequence(s). All of these analyses will be shown with Krona program, which allows to show hierarchical data with pie charts.</span></p><p>Address of the bookmark: <a href="https://readthedocs.org/projects/bipype/" rel="nofollow">https://readthedocs.org/projects/bipype/</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/37627/setting-python-version-as-default-on-linux</guid>
	<pubDate>Tue, 04 Sep 2018 10:15:47 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/37627/setting-python-version-as-default-on-linux</link>
	<title><![CDATA[Setting python version as default on Linux]]></title>
	<description><![CDATA[<p>If you have a later version than 2.6 you'll need to set 2.6 as the default Python. Later versions would be 2.7 and 3.1; see what you have by typing</p><pre>python -V
</pre><p><span>at the terminal. For purposes of this example we'll assume you have 3.1 installed. You'll next need to execute the following commands:</span></p><p>&nbsp;</p><pre>sudo apt-get install python2.6 idle-python2.6
sudo update-alternatives --install /usr/bin/python python /usr/bin/python3.1 1
sudo update-alternatives --install /usr/bin/python python /usr/bin/python2.6 10
sudo update-alternatives --config python
</pre><p>This last command will allow you to choose which version of python to use by default. If you have done everything above correctly, python2.6 should already be set as the default. If it is not, choose it to be the default. From now on, running python should start version 2.6.</p><div><p>Undoing These Changes</p><p>In some cases (e.g., installing or updating certain packages), you'll get an error message if you've run the commands above. To update these packages, you'll have to temporarily undo these changes. Here's how to do that:</p><pre>sudo update-alternatives --remove-all python
sudo ln -s python3.1 /usr/bin/python
</pre><p>Once you're done updating these packages, execute the commands at the top to set python2.6 as the default again.</p></div>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data</guid>
	<pubDate>Sun, 02 Feb 2020 08:14:19 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/40834/nucleus-python-and-c-code-for-reading-and-writing-genomics-data</link>
	<title><![CDATA[Nucleus: Python and C++ code for reading and writing genomics data.]]></title>
	<description><![CDATA[<p>Nucleus is a library of Python and C++ code designed to make it easy to read, write and analyze data in common genomics file formats like SAM and VCF. In addition, Nucleus enables painless integration with the TensorFlow machine learning framework, as anywhere a genomics file is consumed or produced, a TensorFlow tfrecords file may be used instead.</p><p>Address of the bookmark: <a href="https://github.com/google/nucleus" rel="nofollow">https://github.com/google/nucleus</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

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