Bioinformatician’s Pocket Reference !!

It is amusing how brain of bioinformaticians work! Learning a new programming language for days feels so much of fun that making 5 minute discussion with neighbours (unless under special circumstances!) in our own mother-tongue. Today every bioinformatician keeps more than few languages and core IT toolkits on their plate. It has become mandatory to be able to mould different code snippets to build our own custom workflows, and thus keeping syntax at our fingertips has become essential.Although Google is best way to get syntax problem solved, it is not a bad idea to keep reference sheets is our smartphones or stick out some printed sheets on the back of your door, in the old fashion way!!

1) Apache

2) Awk/Gwak

3) C

4) C++

5) Debian

6) Git


8) Java

  9) LaTeX

10) Mathematica

11) Matlab

12) MySQL

13) Perl

14) PHP

15) Python

16) R

17) Screen

18) Ubuntu

19) UNIX

20) Vim

These are handpicked reference sheets and you may encounter various other versions of these over Internet. If you find any version of reference sheet which is worth sharing, feel free to paste the link below.

At the end, I sincerely acknowledge the authors who have put their efforts in designing these informative reference sheets and made them available to us.

Extracting Specific Fasta record/s from a Multi-fasta File

While dealing with multi-fasta files, it is often required to extract few fasta sequences which contain the keyword/s of interest. One fast way to do this, is by awk.

For example:

Input file: hg19_genome.fa


We would like to extract the sequence for Chr2 from hg19_genome.fa. Use the following command:

$ awk ‘BEGIN {RS=”>”} /Chr2/ {print “>”$0}’ hg19_genome.fa



Note that, the search keyword (here ‘Chr2’) doesn’t have to be an exact match. If you use ‘MT‘ instead, you will get the third and fourth entry, since ‘MT’ is a sub-string of the third and fourth fasta record.

Now lets break down the command so that we don’t have to mug it up or we could mold it and use it in variety of other places.

  • awk — This is the main command (Or more of a very powerful programming language)
  • — We write every bit of awk code inside these single quotes
  • BEGIN — This tells the awk to execute the immediately following code in curly brackets at the beginning.
  • {RS=”>”} — Record separator  (If we look at the file, we can observe every sequence starts with a “>” sign. This helps us to separate two fasta records)
  • /Chr2/ — keyword to search in the entire record
  • {print “>”$0} — Here $0 is the current record (From “Chr2” to the entire sequence till next “>”). We added “>” at the beginning just to get the standard identitifer which is not included in $0.
  • hg19_genome.fa — This is the input multi-fasta file that we have used.

Suppose we are interested in more that one keyword then two possibilities arise:

You want BOTH the keywords present,
awk ‘BEGIN {RS=”>”} /Chr2/ && /MT/ {print “>”$0}’ hg19_genome.fa

You want EITHER of the keyword present,
awk ‘BEGIN {RS=”>”} /Chr2|MT/ {print “>”$0}’ hg19_genome.fa

Note: If you are using Windows, you can download and install ‘gwak’ and use similar command. In zsh shell you might need to use an escape character for | (pipe).

I am sure many of you might have different flavors to do the same. If you think it is worth sharing then the comment box is all yours.

Happy Coding !!