Video Tip of the Week: SeqMonk

Always on the lookout for effective visualization tools, I recently came across a series of videos about the SeqMonk software. It’s not software that I had used before, so I wanted to look at the videos, and then try it out. It downloaded quickly, offered me an extensive list of genomes to load up, and then right away I was kicking the tires. And I was impressed. It was easy to locate and explore different regions and the different tracks that were available. And it appears to be very straightforward to load up your own data as well. The video I’ll highlight here is called “Creating Custom Genomes with SeqMonk” which gives a nice intro to their setup.

But they have a whole BabrahamBioinf channel with helpful videos, including a nice short one on how to export graphical representations to use for presentations and publications and such. This is a request I hear a lot from people, and this is a nice guide.

Then I went to look for references for the software to learn more. The group that has developed it–Babraham Bioinformatics–hasn’t published papers specifically on their tools, apparently. They are a services and support group for an institution and not a research group. But they make many of their tools available to the public.

As I’ve noted, though, I really like to get a sense of how people are using the tools, and who is using tools, by looking deeply at the literature. When something has no official citation, it’s harder to assess. And as I’ve pointed out, many papers don’t even cite the tools in the main paper, sometimes it’s in figure legends, or supplements.

A lot of folks have found SeqMonk useful. But it took me 3 different site searches to figure out how useful. I searched at PubMed, PubMedCentral, and Google Scholar. The results were pretty interesting, actually. Just a basic search for SeqMonk yields these differences:

Literature search site number of results
PubMed 1
PubMedCentral 53
Google Scholar 110

The paper in PubMed wasn’t in PubMedCentral, but it was among the 100+ in Google Scholar. Of the 53 in PMC, 2 were absent from Scholar–one had SeqMonk in a figure legend, one had SeqMonk in supplemental procedures. Google Scholar obviously had the biggest range–it also included meeting abstracts, theses, and patent documents, and also a few false positives (from 1840?, 1929, and a couple of other things I couldn’t figure out). Oddly, sometimes the titles differed between PMC and Scholar, but they appeared to be the same paper.  As I’ve noted before, it’s challenging to find out where software is being used, since the way people reference it can be so variable. This was another interesting example of this variability.

But that aside, I was certainly impressed by the various types of data and species that SeqMonk has supported. The variety of species included archaea, chloroplast genome studies, bacteria, ancient maize, yeast, medicinal mushroom mitochondria, zebrafish, and a lot of mammalian research. It has supported a wide range of explorations and topics–lots of epigenetics, PCR techniques, telomere erosion, methylomes of tumors, and even comparison of sequence alignment software. Figure 1 of that aligners paper gives you a nice look at SeqMonk in the wild.

So have a look at the features of SeqMonk for visualization, analysis, and display of existing genomes or your own data. It’s a flexible and effective tool for many purposes.

Quick links:


Their video channel:

Their training materials:

Follow them on twitter:


Chatterjee A., P. A. Stockwell, E. J. Rodger & I. M. Morison (2012). Comparison of alignment software for genome-wide bisulphite sequence data, Nucleic Acids Research, 40 (10) e79-e79. DOI: