Hi,
What are the disadvantage of local alignment mode in bowtie2?
We have a data set with very high quality reads. But when running tophat2 with the defaults parameters, even after clipping and trimming for adapter residues, I still can map only ~60-65% of the whole data set.
Than I have tried bowtie2 with the local-very-sensitive parameter and got over 99% of the reads mapped.
I was wondering, if there is anything against using bowtie2 in this modeand why other people are not doing it more often, if the results are so good.
Is it just the longer running time of the mapping step which needed to be addressed here or are there any more factors one must take under consideration, when running bowtie2 in local mode?
I know there are other mappers such as BBMap and subread, that are also able to do a local alignments and works also with shorter reads.
But what are the reason people don't really do local alignments when working with RNA-Seq data?
thanks in advance
Assa
What are the disadvantage of local alignment mode in bowtie2?
We have a data set with very high quality reads. But when running tophat2 with the defaults parameters, even after clipping and trimming for adapter residues, I still can map only ~60-65% of the whole data set.
Than I have tried bowtie2 with the local-very-sensitive parameter and got over 99% of the reads mapped.
I was wondering, if there is anything against using bowtie2 in this modeand why other people are not doing it more often, if the results are so good.
Is it just the longer running time of the mapping step which needed to be addressed here or are there any more factors one must take under consideration, when running bowtie2 in local mode?
I know there are other mappers such as BBMap and subread, that are also able to do a local alignments and works also with shorter reads.
But what are the reason people don't really do local alignments when working with RNA-Seq data?
thanks in advance
Assa
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