Bowtie vs Bowtie2

[beajorrin]

I'm doing my PhD in Genomics of the interaction rhizobium-legume.
I've sequenced 100 bacteria pooled with Illumina Hiseq 2000, 500 bp PE library, 100 bp reads, and I obtained 12 millions of reads. I've trimmed the reads in the 3' end with Trimmomatic. Then I've analysed my data with Bowtie and Bowtie2, but I've got different results between them, but not those that appear in the article Langmead & Salzberg, 2012, Fast Gapped-read alignment with Bowtie2. Nature Methods 9(4):357-359.
( http://www.nature.com/nmeth/journal/...meth.1923.html )

The options that I've used are:

Bowtie 2: --phred64 --very-sensitive --end-to-end -M2 -I0 -X1000 --fr --no-discordant --no-contain --no-overlap -p4 --no-mixed -t -x
Bowtie: --phred64 --fr -n0 --best -q -M2 -X1000 -I0 -p2 -t

Bowtie recruits more reads than Bowtie2 in this conditions, but Bowtie2 allows more SNPs (differences from reference genome) than Bowtie. I've represented my data in a graphic. I've selected one region of the genome and I've analysed the coverage and the SNPs (representing it as % of differences from reference sequence). As I have 100 bacteria DNA, I need to see the diversity, and the only way is with the SNPs. I include some of this results.

I don't know by what is happennig...

Thanks for all

[jp.]

did you get any answer?
Can you please share your idea ?
I got this one from bowtie website which says: http://bowtie-bio.sourceforge.net/index.shtml
Differences between Bowtie 2 and Bowtie 1 include:
For reads longer than about 50 bp Bowtie 2 is generally faster, more sensitive, and uses less memory than Bowtie 1. For relatively short reads (e.g. less than 50 bp) Bowtie 1 is sometimes faster and/or more sensitive.
Bowtie 2 supports gapped alignment with affine gap penalties. Number of gaps and gap lengths are not restricted, except by way of the configurable scoring scheme. Bowtie 1 finds just ungapped alignments.
Bowtie 2 supports local alignment, which doesn't require reads to align end-to-end. Local alignments might be "trimmed" ("soft clipped") at one or both extremes in a way that optimizes alignment score. Bowtie 2 also supports end-to-end alignment which, like Bowtie 1, requires that the read align entirely.
There is no upper limit on read length in Bowtie 2. Bowtie 1 has an upper limit of around 1000 bp.
Bowtie 2 allows alignments to overlap ambiguous characters (e.g. Ns) in the reference. Bowtie 1 does not.
Bowtie 2 does away with Bowtie 1's notion of alignment "stratum", and its distinction between "Maq-like" and "end-to-end" modes. In Bowtie 2 all alignments lie along a continuous spectrum of alignment scores where the scoring scheme, similar to Needleman-Wunsch and Smith-Waterman.
Bowtie 2's paired-end alignment is more flexible. E.g. for pairs that do not align in a paired fashion, Bowtie 2 attempts to find unpaired alignments for each mate.
Bowtie 2 does not align colorspace reads.

expecting your view
Thank you
jp.

I'm doing my PhD in Genomics of the interaction rhizobium-legume.
I've sequenced 100 bacteria pooled with Illumina Hiseq 2000, 500 bp PE library, 100 bp reads, and I obtained 12 millions of reads. I've trimmed the reads in the 3' end with Trimmomatic. Then I've analysed my data with Bowtie and Bowtie2, but I've got different results between them, but not those that appear in the article Langmead & Salzberg, 2012, Fast Gapped-read alignment with Bowtie2. Nature Methods 9(4):357-359.
( http://www.nature.com/nmeth/journal/...meth.1923.html )

The options that I've used are:

Bowtie 2: --phred64 --very-sensitive --end-to-end -M2 -I0 -X1000 --fr --no-discordant --no-contain --no-overlap -p4 --no-mixed -t -x
Bowtie: --phred64 --fr -n0 --best -q -M2 -X1000 -I0 -p2 -t

Bowtie recruits more reads than Bowtie2 in this conditions, but Bowtie2 allows more SNPs (differences from reference genome) than Bowtie. I've represented my data in a graphic. I've selected one region of the genome and I've analysed the coverage and the SNPs (representing it as % of differences from reference sequence). As I have 100 bacteria DNA, I need to see the diversity, and the only way is with the SNPs. I include some of this results.

I don't know by what is happennig...

Thanks for all