Question: How can I deepen my knowledge in NGS data analysis?
gravatar for AndyJian
2.1 years ago by
AndyJian0 wrote:

I have completed my master thesis project in ChIP-Seq analysis, now I am seeking Ph.D. studentship position in USA, UK. Before entering my doctoral studies, I want to improve my analytical skills in bioinformatics, both in the theoretical context of computational biology and programming skills. I have known with developing software package in R, but I also checked other sources where mentioned that Python, Perl programming are also used for respective analysis. My background in computer science, and I am still quite fresh to solve bioinformatics problems. Thus, I'd like to continue my exploration in bioinformatics, to match future research project more closely. Be short, I need reliable resources where I could learn and expand my knowledge in bioinformatics, so starting with MOOC, entry level book for a junior bioinformatician, tutorial, or related guidance could expand my knowledge in this field, but don't know which one I can follow up. Can anyone propose a list of books, tutorial, MOOC, or other resources that help me out to deepen my knowledge in bioinformatics? Any advice or helpful feedback for designing career path are highly appreciated.

There is a list of my questions:

  1. I am expecting rather well-motivated books or tutorial that specifically designed for educating junior bioinformatics enthusiast to get familiar with a respective analytical mission (NGS, computational cancer biology and so on). which book, tutorial, or online course I can give it try? Any idea?

  2. I am also seeking the tutorial, or list of resources where I could improve my programming skills (I am favored with coding in R, but I want to broaden my skills in others as well). Could any experienced biostar scholar give me a piece of advice?

  3. I am not familiar with Perl programming, but a bit of known with Python. Is that worth to learn those if my later research focuses on the field of computational cancer biology? Can anyone help me how to deepen my programming skills in R, Python or Perl to solve computational problems in bioinformatics?

I am very interested in bioinformatics and my knowledge is still growing. I realize learning theoretical concept of computational biology is necessary, meanwhile improving problem-solving skills is vital. But how can I go through with this? Thanks in advance

bioinforatics ngs gene • 1.2k views
ADD COMMENTlink modified 2.1 years ago by genomax68k • written 2.1 years ago by AndyJian0

jian_liangli : You can learn a lot by going through Biostars threads (some weeding out is required).

Bioinformatics courses, workshops or training compilation by @Deepak Tanwar contains a large cache of learning resources.

ADD REPLYlink modified 2.1 years ago • written 2.1 years ago by genomax68k

@genomax2: is there little preview where I can go through the main context of biostars handbook? Plus, I am familiar with ChIP-Seq analysis, so what's best practice to continue my current research interest? Thanks :)

ADD REPLYlink written 2.1 years ago by AndyJian0

If it is more about learning with real world programmatic tutorials, MOOCs are good but also blogs are important to follow. I would highlight this. There are several links from experts which should be a good start-point. Obviously, MOOCs come with certification which blogs might not but forum like Biostar's and blogs come with problem-solving requests. That is what one encounter while handling data.

ADD REPLYlink written 2.1 years ago by ivivek_ngs4.8k

I don't think there is a preview but the refund policy is pretty generous and outlined in the FAQ here.

ADD REPLYlink written 2.1 years ago by genomax68k

Tutorial tags are generally reserved for threads that discuss how to use a program or tool\do an analysis explained in a step-wise manner. It is not appropriate for this thread.

ADD REPLYlink modified 2.1 years ago • written 2.1 years ago by genomax68k
gravatar for Santosh Anand
2.1 years ago by
Santosh Anand4.9k
Santosh Anand4.9k wrote:

You need just one: The Biostar Handbook. A bioinformatics e-book for beginners.

I gave a very generic answer as your are Qs are very broad. Just a few more comments from my side:

  • Python vs. Perl: Definitely Python (10 years before the answer would have been reversed)

  • R is essential for many things. You will be better off learning it (at least knowing how it functions because sooner or later, you'll find working with some R-packages)

As genomax points out, It's not free (20$), but worth every penny if you can afford it. Contains cumulative knowledge of Biostars!

ADD COMMENTlink modified 2.1 years ago • written 2.1 years ago by Santosh Anand4.9k

Appropriate to include a disclaimer that Biostars handbook is not free. Which may be an important consideration in some parts of the world.

ADD REPLYlink modified 2.1 years ago • written 2.1 years ago by genomax68k
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