Sorry, it is genomic sequencing. I tried with -N 1 but increased just to 1.5%. I will try those. Yes, its the same Pinfestans but I am trying to align to Pcap genome to find common SNPs position sites. I have other Pcapsici re-sequencing samples too. Thanks.
I am aligning Pinfestans illumina reads to Pcapsici genome.
bowtie2 \
--local \
-p 4 \
-x Pcap_genome \
-1 ERR299593_1.paired.trimmed.fq \
-2 ERR299593_2.paired.trimmed.fq \
-U ERR299593_1.unpaired.trimmed.fq,ERR299593_2.unpaired.trimmed.fq \
-S ERR299593.sam &> summary_ERR299593
This gave just 0.47% alignment. How can I make the alignment loose or use other tools? Any suggestions. Thanks
2 answers
You may try Anfo or batmis. I believe BBMap is also very forgiving, and it has tons of options to tune the alignment, read is READMe file.
For bowtie2, you may set "-N 1", also look at scoring options.
However, you did not say which kind of reads are you aligning. Is this RNAseq, genomic sequencing, ...? Also, is this the P. infestans you are working on?
How similar are both genomes? Does it makes sense to look for SNPs across the whole genome?
I would map reads against it own genome for both species, call SNPs on genes, find orthologous genes and compare SNPs on pairs of orthologous genes.
You will most likely want to alter the scoring options. See the manual for several of them
http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml#bowtie2-options-mp
Basically every match adds a score, every mismatch/gap subtracts a score, and if the final score after going through the entire read meets some threshold (decided by the scoring function), the alignment is kept. So I would increase the match score (--na), decrease the mismatch and gap penalties (--mp, --rdg, --rfg), and adjust the scoring function with --score-min.
You can read more about the score function here.
I'm not sure exactly what values you should use as I haven't used bowtie in awhile and it will depend on how similar your species are
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If you just get 0.47% of reads mapped and you are counting the numbers right, probably you can't get good results with any short-read mappers. You should do de novo assembly first and then map the assembly.
@lh3 If I get right, you mean mapping whole assembly to the genome? If yes, can SNPs be called? Thanks