Novice's intro

[seqansweruser]

Hello Everyone.

Wanted to say hello and post a question about some learning.

Questions.

-->Which one to master. R or Python?

--> Where can I find sample pipelines for NGS data-analysis?
Currently scouring through some old pub-med articles. Any other simpler source will be much appreciated.

Thank you everyone.

[blancha]

If you're serious about bioinformatics, you'll have to learn both unfortunately, however confusing that may be.

The one, irreplaceable, feature of R that cannot be found in Python is the library of bioinformatics programs found in the Bioconductor repository.
R has other features that do make it a great programming language, but many of these features have been copied by Python (e.g. pandas, ...), albeit not always very succesfully.
For example, the static graphs that can be generated by R, with ggplot2 for example, are second to none. R was also designed by statisticians so statistical analyses are very straightforward.

Outside of bioinformatics and pure statistics, Python has become the dominant language.
It is a very straightforward language, and given the number of users, there are constantly new modules being added.

I know principal investigators who have based their entire, very succesful, careers solely on their mastery of R. Should they need a program to be written in Python or any other language, they ask a student or hire an employee to do it for them. As a student or an analyst, you don't have this luxury.

The analysis pipelines are dependent on the type of analysis you want to perform.
For RNA-Seq, I recommend reading the Nature article on the Tuxedo protocol.

http://www.nature.com/nprot/journal/v7/n3/full/nprot.2012.016.html

For Exome-Seq, consult the Broad institute protocol.
https://www.broadinstitute.org/gatk/...best-practices

[seqansweruser]

Thank you very much. I do want to be a real bioinformatics. I currently handle LIMs programming and clinical reporting related stuff. ( lot of java framework, Ruby on rails and Restful stuff) .

I will start focusing on R more and eventually learn Bio-python ( I know how to program in python already, need to know bio-python much much better.)



I will download those papers and start reading.

Thank you again.