Question: Spliced aligners for RNA-seq
gravatar for amirmhzadeh
2.5 years ago by
Canada, Vancouver
amirmhzadeh70 wrote:


I'm working on RNA-Seq data. I am planing to evlaute the performance of the below-listed RNA-seq spliced aligners to find the most befitting one for my study. It is worth mentioning that the species of my interest is homo sapiens.

Right now I am considering the following aligners:

  1. TopHat
  2. MapSplice
  3. SpliceMap
  4. STAR
  5. RUM
  6. GSNAP
  7. HMMSplicer
  8. SOAP-splice
  9. CRAC
  10. QPALMA

I know this question has been asked repeatedly over the past few years and there are many great and thorough answers for it but I am wondering if there are some RNA-seq splice aligners out there that I have never heard of?

Any advise would be greatly apprecited.



P.S. I am including some relevant posts from BioStar and SeqAnswers here for future references by the readers:

rna-seq next-gen alignment • 1.7k views
ADD COMMENTlink modified 2.5 years ago by h.mon9.2k • written 2.5 years ago by amirmhzadeh70

HSAT aligner from tophat group. 

ADD REPLYlink written 2.5 years ago by poisonAlien2.5k


Here's a nice poster of it:

The defaults are fine for organisms with short introns<16kbp.  For vertebrates or other organisms with very long introns be sure to set "maxindel=200000".

ADD REPLYlink modified 2.5 years ago • written 2.5 years ago by Brian Bushnell14k

Subjunc -- as fast as STAR.

ADD REPLYlink written 2.5 years ago by Lynxoid210


ADD REPLYlink written 2.2 years ago by khikho100
gravatar for h.mon
2.5 years ago by
h.mon9.2k wrote:

Unless you want to write a paper comparing spliced aligners, I would read the literature relevant for your area and pick two or three aligners for testing. Are you willing to optimize parameters for each program, or just use defaults? A program performing badly may just need some tuning.

All in all, it seems just an enormous amount of work, to probably get a small improvement (I am speaking from experience).

ADD COMMENTlink written 2.5 years ago by h.mon9.2k
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