Hi guys, I had to make my own tool for cutting NGS reads. Because our experimental setup is very unique and we have primers and barcodes in ever changing positions, so I couldn't use anything that's on the market. I wrote it in python and it works really well and finds all the positions, but it isn't exactly fast compared to professional tools. I used the plain needleman-wunsch algorithm for semi-global alignment to find the primer positions in the read. This is obviously the main bottleneck. I'll probably stick with my own script because it achieves exactly what I want. It just made me wonder, what are the algorithms that are being used by the more professional tools? Is it needleman-wunsch as well, just with a better implementation in C? Or do they use more sophisticated approaches, like checking k-mers, oder a seed and extend kind of approach? I tried to read up on this, but I couldn't really find the information. The tool cutadapt for example has its source code on github and a lot of it seems to be in python but I couldn't find the function that does the actual matching of the adapter to the read. I'm just looking for some beginner friendly literature to educate myself a bit further on these algorithms, any help would be much appreciated. Thanks in advance.
Question: What algorithms are underlying in read cutting tools?
10 weeks ago by
Mick • 10
Mick • 10 wrote:
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