User:Timothee Flutre/Notebook/Postdoc/2012/05/25: Difference between revisions

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==One-liners with GNU tools==
==About one-liners in data wrangling==


* '''Toolbox''': often available by default on many computers running GNU/Linux
* '''Motivation''': Once we receive raw data and before drawing robust conclusions, we (almost) always need to reformat them as well as extract a few key summary statistics. Hopefully this activity, called [https://en.wikipedia.org/wiki/Data_wrangling data wrangling], is particularly quick and easy on [http://www.gnu.org/gnu/gnu-linux-faq.html GNU/Linux] computers. For instance, using GNU utilities via the [https://en.wikipedia.org/wiki/Command-line_interface command-line interface], we can write a "one-liner", a sequence of tools in which the output of a tool is the input of the next. This is not only easy but also very powerful, as shown below.
 
* '''Toolbox''': often available by default on many computers with GNU/Linux
** [https://en.wikipedia.org/wiki/Bash_%28Unix_shell%29 Bash]
** [https://en.wikipedia.org/wiki/Bash_%28Unix_shell%29 Bash]
** [https://en.wikipedia.org/wiki/AWK AWK]
** [https://en.wikipedia.org/wiki/AWK AWK]
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** [https://en.wikipedia.org/wiki/Sed sed]
** [https://en.wikipedia.org/wiki/Sed sed]
** [https://en.wikipedia.org/wiki/GNU_Core_Utilities GNU coreutils] (head, tail, cut, uniq, sort, tr, ...)  
** [https://en.wikipedia.org/wiki/GNU_Core_Utilities GNU coreutils] (head, tail, cut, uniq, sort, tr, ...)  


* '''Tutorials''':
* '''Tutorials''':
** [http://en.flossmanuals.net/command-line/index/ Introduction to the command-line]
** [http://en.flossmanuals.net/command-line/index/ Introduction to the command-line]
** [http://www.ibm.com/developerworks/aix/library/au-unixtext/index.html Introduction to text manipulation on UNIX-based systems] by Brad Yoes (IBM)
** [http://www.ibm.com/developerworks/aix/library/au-unixtext/index.html Introduction to text manipulation on UNIX-based systems] by Brad Yoes (IBM)
** [http://quinlanlab.org/tutorials/cshl2013/bedtools.html tutorial for bedtools]




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About one-liners in data wrangling

  • Motivation: Once we receive raw data and before drawing robust conclusions, we (almost) always need to reformat them as well as extract a few key summary statistics. Hopefully this activity, called data wrangling, is particularly quick and easy on GNU/Linux computers. For instance, using GNU utilities via the command-line interface, we can write a "one-liner", a sequence of tools in which the output of a tool is the input of the next. This is not only easy but also very powerful, as shown below.
  • Toolbox: often available by default on many computers with GNU/Linux


  • Skip a subset of successive lines:
for i in {1..10}; do echo $i; done | sed 3,6d


  • Extract a subset of successive lines:
$ for i in {1..20}; do echo $i; done | sed -n 3,5p


  • Use absolute values:
$ for i in {-5..5}; do echo $i; done | awk 'function abs(x){return (((x < 0.0) ? -x : x) + 0.0)} {print abs($1)}'


  • Extract the best snp per gene:
$ echo -e "gene\tsnp\tpvalue\ng1\ts1\t0.3\ng1\ts2\t0.002\ng2\ts2\t0.7\ng2\ts3\t0.05" > dat.txt
gene    snp     pvalue
g1      s1      0.3
g1      s2      0.002
g2      s2      0.7
g2      s3      0.05

$ cat dat.txt | sed 1d | sort -k1,1 -k3,3 | awk '{print $3"\t"$2"\t"$1}' | uniq -f2
g1      s2      0.002
g2      s3      0.05


  • Loop over pairs:
$ subgroups=("s1" "s2" "s3" "s4"); for i in {0..2}; do let a=$i+1; for j in $(seq $a 3); do s1=${subgroups[$i]}; s2=${subgroups[$j]}; echo $s1 $s2; done; done



$ awk 'BEGIN{RS=">"} {if(NF==0)next; split($0,a,"\n"); printf "@"a[1]"\n"a[2]"\n+\n"; \
for(i=1;i<=length(a[2]);i++)printf "}"; printf"\n"}' probes.fa > probes.fq


  • Sort a file with header line: that is, we don't want the first line to be sorted
$ echo -e "x\ty"; for i in {1..10}; do echo -e $i"\t"$RANDOM; done | (read -r; printf "%s\n" "$REPLY"; sort -k2,2n)


  • Get rows from a big file which are also in a small file: example of using awk with 2 input files by loading the important information from the small file into an array in memory, then parsing the big file line by line and comparing each with the content of the array
$ echo -e "gene\tsnp\tpvalue\ngene1\tsnp1\t0.002\ngene2\tsnp2\t0.8\ngene2\tsnp3\t0.1" > file_all.txt
$ echo -e "gene1\tsnp1" > file_subset.txt
$ awk 'NR==FNR{a[$1$2]++;next;}{x=$1$2;if(x in a)print $0}' file_subset.txt <(sed 1d file_all.txt)



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