[adaptivegenome]

@adaptivegenome

Thank you for redirecting me to GCAT website. I am sure with time it will become more useful.

At the moment, it does not well answers my concern. I want a comparison of Bowtie2 vs BWA-MEM and not Bowtie1. Also a comparison of BWA-MEM vs BWA-SW on sequences as long as several kilobases. Comparison of BWA-SW vs Megablast for several kilobases of sequences. Comparison of BWT-SW vs Blast with e-value parameter as high as 10.

I am sure a 3rd party analysis such as GCAT will be useful. At the same time the opinions of the makers of these tools would be very useful as they are aware of the alternatives.

Narain

GCAT is using Bowtie2 and not Bowtie1. Also you can choose what tools are compared or add your own.

You don't even need to use GCAT. I mentioned it because I did not want to make a claim of performance without being able to back it up with results. In my discussions with Heng Li, he did indicate as well that BWA-MEM was designed to replace preview BWA and BWA-SW implementations but you should certainly get his opinion directly as well.

[narain]

@adaptivegenome

Thank you for redirecting me to GCAT website. I am sure with time it will become more useful.

At the moment, it does not well answers my concern. I want a comparison of Bowtie2 vs BWA-MEM and not Bowtie1. Also a comparison of BWA-MEM vs BWA-SW on sequences as long as several kilobases. Comparison of BWA-SW vs Megablast for several kilobases of sequences. Comparison of BWT-SW vs Blast with e-value parameter as high as 10.

I am sure a 3rd party analysis such as GCAT will be useful. At the same time the opinions of the makers of these tools would be very useful as they are aware of the alternatives.

Narain

[adaptivegenome]

@lh3 and other eminent speakers in the thread

Its nice to know that we have so many new aligners that have come up in competition to the BLAST which dominated for about 2 decades, and in many way is still the most popular.

In your opinion, for what purposes is bwa-sw better than bwa-mem. I am assuming bwa-mem to be a more equivalent for bowtie2 for long reads such as 250 to 400 bp, but not very good for reads in the order of kilobases.

For what purposes could bwt-sw be better applicable than bwa-sw ?

In what ways bwa-sw is better than MegaBlast given that both do alignment for long sequences in order of kilobases or larger.

In what way bwt-sw could be different than BLAST as though the latter uses heuristics, it still comes up with all the relevant local alignments if you tune the -e parameter accordingly, such as increasing it to 10. The website of bwt-sw states to use it at your own risk, implying that the software is not well tested!

Narain

I think that BWA-MEM outperforms both BWA and BWA-SW. You can check out some of the comparisons we have done on gcat (www.bioplanet.com/gcat) and I am sure others here probably have tried out BWA-MEM as well.

[narain]

@lh3 and other eminent speakers in the thread

Its nice to know that we have so many new aligners that have come up in competition to the BLAST which dominated for about 2 decades, and in many way is still the most popular.

In your opinion, for what purposes is bwa-sw better than bwa-mem. I am assuming bwa-mem to be a more equivalent for bowtie2 for long reads such as 250 to 400 bp, but not very good for reads in the order of kilobases.

For what purposes could bwt-sw be better applicable than bwa-sw ?

In what ways bwa-sw is better than MegaBlast given that both do alignment for long sequences in order of kilobases or larger.

In what way bwt-sw could be different than BLAST as though the latter uses heuristics, it still comes up with all the relevant local alignments if you tune the -e parameter accordingly, such as increasing it to 10. The website of bwt-sw states to use it at your own risk, implying that the software is not well tested!

Narain

[oiiio]

I started to reply in adaptivegenome's purposed thread here: http://seqanswers.com/forums/showthr...688#post101688

[lh3]

Well, fewer people will see if I comment there. Perhaps the developers might consider to open a thread here.

I am looking at the ROC-like curves. For all data sets, BWA-SW quickly picks up high mapQ wrong alignments. But as you have considered clipping, maybe that is really the fault of bwa-sw. I don't know for sure. Anyway, for typical illumina/454/iontorrent reads, bwa-sw is now deprecated by bwa-mem.

For exome variant calling, it would be better to give statistics in the target regions only.

[adaptivegenome]

Here I started a new thread since we have sort of highjacked this one...

http://seqanswers.com/forums/showthread.php?p=101688#post101688

[adaptivegenome]

Thanks Heng -

It does account for soft clipping, and also allows +/- 5bp in deciding if the alignment is correct. I also find your observation very surprising, because in most of the reports BWA-SW is more accurate than Bowtie2. For example, this report is for a 100bp paired-end illumina sample: http://www.bioplanet.com/gcat/reports/21/alignment/100bp-pe-small-indel/bwa_sw . I see here that BWA-SW appears more accurate than Bowtie2 as more reads are considered, but you are right that it looks bad at the beginning of the graph.

Also, it would awesome for building the GCAT community if you could ask these types of questions on the surrounding forum. The lead developers are watching there, and continuously add improvements as users make suggestions. The user name "lh3" is also available

I would be interested in hearing what suggestions Heng might have for better metrics. GCAT is awesome but we need to think of more ways to evaluate pipelines...

[oiiio]

Thanks Heng -

It does account for soft clipping, and also allows +/- 5bp in deciding if the alignment is correct. I also find your observation very surprising, because in most of the reports BWA-SW is more accurate than Bowtie2. For example, this report is for a 100bp paired-end illumina sample: http://www.bioplanet.com/gcat/reports/21/alignment/100bp-pe-small-indel/bwa_sw . I see here that BWA-SW appears more accurate than Bowtie2 as more reads are considered, but you are right that it looks bad at the beginning of the graph.

Also, it would awesome for building the GCAT community if you could ask these types of questions on the surrounding forum. The lead developers are watching there, and continuously add improvements as users make suggestions. The user name "lh3" is also available

[lh3]

Very impressive website. There is though a question: when evaluating alignments, how do you tell if an alignment is correct? If there is a clipping in an alignment, how do you deal with that?

I ask this because bwa-sw is surprisingly bad. While bwa-sw is less accurate than bwa-mem, it should be similar to bowtie2. A possible cause is that among the mappers evaluated on your website, bwa-sw reports the most soft clipping. If you do not correct clipping, bwa-sw will be easily the worst.

[zee]

GCAT is great because it allows you to run and submit your own datasets for public scrutiny. We are going to make good use of it.

[oiiio]

Since it appears this excellent thread has been resurrected recently already-

I'd like to show you all a comparison of bowtie2+GATK and other pipelines for variant calling on the NA12878 illumina exome with 150x coverage. These variant calling reports are generated by the GCAT resource on bioplanet.com:

http://www.bioplanet.com/gcat/report...x/bowtie-atlas

You can use the check box menu at left to choose other pipelines to compare to.

[shi]

Hi ka90,

We have recently made comparisons for a few aligners. Please see

http://nar.oxfordjournals.org/content/early/2013/04/03/nar.gkt214.abstract

Cheers
Wei

[ka90]

Sorry for bringing this thread back to life. I was wondering how they compared now that bowtie2 has a stable release and is not in beta anymore. Has anyone been able to compare the latest versions of bowtie2 with other mappers? If so, can you provide your observations.

[wlangdon]

ps: Bowtie2 has a --very-sensitive command line option which can increase its
accuracy at the expense of increased run time. (In one case by 0.8% to 83.4% but
run time increased by 53%).
Bill