Hi! I was wondering - what kind of comparisons have users of this forum run on Tophat vs STAR?
What have you found to be the main differences in terms of accuracy and "quality" of mapping (as opposed to speed/memory requirements, which have been covered in the paper quite well)?
And how does STAR compare to the newer versions of Tophat, which are purported to have solved the pseudogene problem?
I have seen this post, but didn't want to lead the discussion off topic there:
To quote pbluescript from that thread:
More reads != better mapping, it may just mean more false assignments of reads to location + salvaging more reads that may not be mappable...
What have you found to be the main differences in terms of accuracy and "quality" of mapping (as opposed to speed/memory requirements, which have been covered in the paper quite well)?
And how does STAR compare to the newer versions of Tophat, which are purported to have solved the pseudogene problem?
I have seen this post, but didn't want to lead the discussion off topic there:
To quote pbluescript from that thread:
You should try STAR. http://gingeraslab.cshl.edu/STAR/
I've mentioned this elsewhere on the forums, but in the comparisons I've done, STAR yields more mapped reads, more uniquely mapped reads, and more reads with both pairs mapped than Tophat all in about 20% of the time it takes Tophat. The only downside is an increase in potential false positive splice junctions, but those can be filtered out easily enough.
It was just published too:
http://bioinformatics.oxfordjournals...ts635.abstract
I've mentioned this elsewhere on the forums, but in the comparisons I've done, STAR yields more mapped reads, more uniquely mapped reads, and more reads with both pairs mapped than Tophat all in about 20% of the time it takes Tophat. The only downside is an increase in potential false positive splice junctions, but those can be filtered out easily enough.
It was just published too:
http://bioinformatics.oxfordjournals...ts635.abstract
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