I'm looking for a book about bioinformatics algorithms, such as alignment, BLAST search, and variant calling.

I'm hoping reading about this subject will give me a deeper understanding of the foundations of bioinformatics, and I'm also interested in developing my own tools and algorithms for sequence and variant analysis. I studied applied mathematics and computer science at university, so I don't shy away from math-heavy books.

I've listed some candidates below.

Durbin et al. is quite old, Sung is the newest.

I am looking for books with:

  • material (algorithms) on alignment, assembly, and variant calling if possible.
  • New books are preferred
  • 1
    $\begingroup$ "Biological Sequence Analysis" is excellent, you say it's old but it's been re-printed many times with edits and is still very relevant. My edition is the 10 re-reprinting from 2010, they may be an even more recent one $\endgroup$ – Chris_Rands Mar 27 '18 at 14:36
  • $\begingroup$ Ziheng Yang's "Computational Molecular Evolution" is also good I recall $\endgroup$ – Chris_Rands Mar 27 '18 at 14:37
  • 1
    $\begingroup$ @Llopis it's common on biology.stackexchange.com to ask for book recommendations. I asked the same question there, and was recommended that I ask it here instead. For what it's worth, I think the question is better suited here, as it is more likely to reach relevant people here. $\endgroup$ – Ólavur Mar 28 '18 at 8:51
  • 2
    $\begingroup$ The asker is looking for books that meet various fact-based criteria — it covers topics A, B, C, etc. A book recommendation objectively either meets or does not meet those criteria. If it does not meet the criteria, that is a problem with the answer, not the question. It's difficult to see what is open-ended or opinion-based about meeting plainly-stated criteria. Voting to reopen. $\endgroup$ – Alex Reynolds Mar 29 '18 at 0:12
  • $\begingroup$ Completely agree with Alex, voted to reopen. $\endgroup$ – Kamil S Jaron Mar 29 '18 at 9:47

Here are a couple books I'd recommend:

Dan Gusfield's Algorithms on Strings, Trees, and Sequences is a deep and wide treatment of aligning, searching, and processing strings, trees, and sequences.

Warren Ewens' Statistical Methods in Bioinformatics devotes a chapter to BLAST and the math underneath it.

Edit - Another book that may be useful for some mathematical underpinnings would be Michael S. Waterman's Introduction to Computational Biology.

  • $\begingroup$ I agree that algorithm books, like Gusfield's, are hugely important. Personally though, I have that covered decently already. $\endgroup$ – Ólavur Mar 28 '18 at 8:59
  • $\begingroup$ The Waterman book looks quite interesting, it has some material that I haven't seen in other books. $\endgroup$ – Ólavur Mar 28 '18 at 9:00

If you're interested in variant calling, I just co-authored an O'Reilly book called Genomics in the Cloud that covers the GATK Best Practices from a scientific standpoint (germline and somatic short variants + somatic copy number alterations), as well as technical considerations like how to run it efficiently at scale (that's where the cloud part comes in).

You can read more about it on the GATK blog; there's an announcement and a second more personal blog post that I wrote to explain how I approached the topic. Happy to discuss more if you're interested.

Oh and you can preview the first few chapters for free on Amazon if you like.


Bioinformatics and Functional Genomics by Jonathan Pevsner is a good one, he goes over the biology as well as how the algorithms work, and provides real-world examples.

  • $\begingroup$ This one is very nice, a colleague of mine happens to have it. It doesn't seem to go into much detail with the math and algorithms though (which is not a deal breaker or anything), probably because it's targeted mostly at biology students. I think it has a very nice way of tying the algorithms to the biological context. Perhaps this book is a good introduction, and to get more mathematical details one can read papers on BLAST, aligners such as BWA, and so on. $\endgroup$ – Ólavur Apr 5 '18 at 12:11

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