Question: Fastest (non-pseudo) aligner for RNA-seq illumina seq data (year 2019)
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enxxx23 • 240 wrote:
What is the fastest (non-pseudo) aligner for RNA-seq illumina seq data today in year 2019?
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modified 23 months ago
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kristoffer.vittingseerup • 3.5k
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23 months ago by
enxxx23 • 240
fastestis a relative metric unless you do an apples-to-apples comparison on hardware you will eventually use. Choice of alignment options can have a significant impact on speed. It would be difficult to get those to align well among aligners.bbmap.shfrom BBMap suite will stand with the best of them on any given day.bwa memmay be the smallest memory footprint aligner (~6-7G for human genome).BWA MEM is not a RNA-seq aligner by design.
Sure. While the statement is true if you are looking for a splice-aware aligner it is not applicable in this case. Though you could use it if you were dealing with bacterial RNAseq data.
True, I should have mentioned the target organisms, which in this case are eukaryotes. Retroviruses do not have RNA so doing RNA-seq on retroviruses is the only choice! ;-)
what do you mean by
I don't believe that speed only is a valuable concept. I could write an EXTREMELY fast aligner (with terrible accuracy).
Challenge accepted !
ok great. Now submit to Nature Methods
They'd accept it, for sure.
At last try to :
if read in reference: print('Aligned!')
STAR is for me, the best compromise between running time and efficiency
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792058/
I think STAR and HiSAT are probably similar. STAR requires less tuning, but HiSAT can be tuned to give very similar accuracy performance. The benefit of HiSAT is that it uses much less memory.