hello I am trying to alignment RNA-seq data to refrence genome using bwa mem.... my data type is single end and 140-150 bp Is it right to use bwa mem ?
bwa mem -B 0 -t 4 BWA-index.fa trimmed.fastq.gz > bwa-out.sam
or i have to use the BWA aln and witch option for snp discovery ? sorry for my bad english ........
If you have RNA-Seq data you should try using STAR or Tophat.
Hi mra8187,
Unless your organism is prokaryotic you need to use an aligner which is aware of splicing, to map RNA-seq reads over introns. Examples of these are STAR, Tophat2 and HISAT2. In addition, SNP discovery is possible for RNA-seq, but it is not straightforward and not the most reliable technique for SNP discovery.
Try when you ask a question to be as informative as possible and don't forget to mention which organism you are working on!
In addition, I'm not sure -B 0 is a good setting for bwa mem, but that's something else... (Unless you know what you are doing, stick with the default settings. A tool should have reasonable default settings so you don't have to think about tens of options.)
Cheers,
Wouters
See this post for bwa aln vs mem
When and why is bwa aln better then bwa mem?
If flexible with aligners, STAR is very fast and gives good results. If you need to run fusions as well,you can use STAR fusion which will give you BAM as well as fusions. https://github.com/STAR-Fusion/STAR-Fusion
for SNPS in RNAseq : https://github.com/davidliwei/rnaseqmut http://gatkforums.broadinstitute.org/gatk/discussion/3891/calling-variants-in-rnaseq
thanks for your annswers..... i first use tophat 2.1.1 for alignment .. and percentage of map is very low ... Reads: Input : 11677522 Mapped : 4646585 (39.8% of input) of these: 63466 ( 1.4%) have multiple alignments (536 have >20) 39.8% overall read mapping rate. i work on rna-seq of honey bee .
with use bwa mem percentage is about :
11677594 + 0 in total (QC-passed reads + QC-failed reads) 0 + 0 secondary 72 + 0 supplementary 0 + 0 duplicates 9133705 + 0 mapped (78.22% : N/A)
so i think i have to denovo assembling the unmap may bee refrence genome of honey bee have not compelate ... any advise i appreciate to hear that....
Please use ADD COMMENT to reply to earlier answers, as such this thread remains logically structured and easy to follow.
It should be possible to improve the tophat alignment, I guess. Could you elaborate on how you processed the data (adapter and quality trimming) and how you performed the tophat alignment?
i am using trimmomatic and it is the resaults :
single end https://www.dropbox.com/s/wqqxav4qxy3sk1e/single-end.zip?dl=0
paired end1 https://www.dropbox.com/s/b7rfgqgee3ds9u3/SRR1571716-1.trimmed_fastqc.zip?dl=0
paired end2 https://www.dropbox.com/s/5zqc4sgg3ccrtcr/SRR1571716-2.trimmed_fastqc.zip?dl=0
because reverse has bad quality im using forward only (single) and script tophat2.1.1:
single : tophat2 -p 4 -G anotation.gtf -o output indexed-refrence.fa trimmed1.fastq.gz
paired : tophat2 -p 4 -r 200 --mate-std-dev 50 -G anotation.gtf -o output indexed-refrence.fa trimmed1.fastq.gz trimmed2.fastq.gz
and tophat output:
single : Reads: Input : 10858264 Mapped : 4083998 (37.6% of input) of these: 53299 ( 1.3%) have multiple alignments (16 have >20) 37.6% overall read mapping rate.
paired : Left reads: Input : 8066646 Mapped : 3376613 (41.9% of input) of these: 41967 ( 1.2%) have multiple alignments (61 have >20) Right reads: Input : 8066646 Mapped : 4488196 (55.6% of input) of these: 55841 ( 1.2%) have multiple alignments (66 have >20) 48.7% overall read mapping rate.
Aligned pairs: 3164464 of these: 39807 ( 1.3%) have multiple alignments 9497 ( 0.3%) are discordant alignments 39.1% concordant pair alignment rate.
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you need to use aligner which support split alignments for rna-seq - like tophat.