SOAPdenovo2 Demystified, BWA Mystified
In January and February, we went over the code of SOAPdenovo2 genome assembler, and discussed in a number of commentaries.
Our First Look at SOAPdenovo2 Source Code
SOAPdenovo2 Demystified part 1
SOAPdenovo2 Demystified part (a)
SOAPdenovo2 Demystified part (b) [multi-thread implementations]
More SOAPdenovo2 Commentaries Will Come in February
SOAPdenovo2 Demystified A Rough Guideline of Functionality
Analyzing code written by someone else is not fun. In fact, analyzing own code is not fun, if it is in PERL. Thanks to Ryan Chikhi, the author of Minia assembler, we decided to place the SOAPdenovo2 code in wiki. Both of us were interested in the scaffolding algorithm, and Rayan helped us figure out the major blocks of scaffolder in SOAPdenovo2.
Today we added a new feature to the wiki page of SOAPdenovo2. This is based on a script that goes over all code files and generates dependencies between functions in wiki format. We then upload those dependencies on the wiki page to share with you. As an example, when you click on ‘main.c’ in SOAPdenovo, the wiki page shows all functions being called and the files they are in. Also the hyperlinks work. So, you can click on those functions to get to the wiki section for the called function (note: the following image will not work. You need to try in the actual wiki).
To show you the usefulness of this new script, we also generated similar wiki page for BWA. Recently, we went through the BWA code to learn how BWA-MEM works and posted about it in a blog commentary.
The above is not panacea regarding figuring out the code and the wiki generation script itself is not faultless, but we hope it would help you navigate through the codes better. The BWA wiki page has no annotation apart from the links between functions, but we can now start putting text in between and create references for the code that others can use in their teaching or research. At the end of the day (long summer one in Seattle :)), we like to combine those wiki code analysis pages with the Tutorial section so that those learning bioinformatics can do it by seeing the latest codes from yet-to-be- published papers and get to the frontier of research.
