Question: Which skills are most required to become a good bioinformatician?
3
Entering edit mode

I am half way through my PhD and I am considering pursuing a career in bioinformatics. My experience in bioinformatics is limited: I started coding 3 years ago but very slowly and my PhD is half bioinformatics half laboratory based. I currently have experience in bash and R. I am also trying to learn Python.

I am trying to find out how best to improve and prepare my CV for when I apply for jobs after my PhD. Any recommendations as to which skills in particular I should focus on would be greatly appreciated.

ADD COMMENTlink 2.4 years ago m93 • 150 • updated 2.3 years ago Biostar 20
Entering edit mode
3

Becoming adept in Python is very useful (one might say essential; you should be adept in some language (not R) and Python is a good choice). Becoming fluent with a wide variety of commonly-used bioinformatics software and data from different sequencing platforms is also a big plus. So, be able to take raw Illumina data and map it, call variants, look at the data in IGV; de-novo assemble the data and calculate coverage on the assembly; call peaks with Chip-SEQ; analyze differential expression with RNA-seq; taxonomically classify unknown contaminant reads; annotate variants with predicted effects of mutations on proteins; look for structural variations with long-read (PacBio/Nanopore) data; that sort of thing. It helps in interviews if you have personally done each of these on several different datasets so you know some of the nuances of them.

ADD REPLYlink 2.4 years ago
Brian Bushnell
16k
Entering edit mode
0

I agree that being able to use published tools, especially beyond!!! simply using the defaults is a big plus. A reasonable understanding of the theory behind the algorithms is also advisable to be able to adapt them to non-standard datasets. Still, I (also being a half-half student, far from being a proper programmer) prefer R much of Py or any other language, as Bioconductor offers a plethora of customizable packages that require a proper knowledge of R for efficient use. Beyond that, being able to write proper bash scripts to efficiently manipulate large files and automate repetitive tasks is a must. Experience in using a Linux cluster also helps, but that depends if your field requires large data handling.

ADD REPLYlink 2.4 years ago
ATpoint
17k
Entering edit mode
0

Here are some resources I'm working through:

Bioinformatics tools/resources https://github.com/crazyhottommy/getting-started-with-genomics-tools-and-resources

Online tutorial over bioinformatics which has a nice python section

ADD REPLYlink 2.4 years ago
Ghoti
• 50
1
Entering edit mode

This heavily depends on your field. I know bioinformaticians who more or less deal with webserver development, yet others mostly deal with low level algorithms, used by many others. R and py are definitely a plus, as prototyping becomes really, really fast.

ADD COMMENTlink 2.4 years ago Bioaln • 310
1
Entering edit mode
ADD COMMENTlink 2.4 years ago theobroma22 ♦ 1.1k
0
Entering edit mode

Thanks to you all of you for your answers, that's really useful. Will definitely keep learning Python, R I know better but not in great depth (I still struggle while using specific rare packages). I also know Bash as I have to handle large datasets on the cluster. Thanks again!

ADD COMMENTlink 2.4 years ago m93 • 150

Login before adding your answer.

Powered by the version 1.8