These BWT-based sequence alignment tools provide fast mapping of short reads of DNA sequences against a reference genome sequence with small memory footprint using a data structure like FM-Index [18] built atop the BWT.
For certain tasks of bioinformatics workflows, such as sequence alignment and mapping of short reads which are also incidentally some of the most computationally expensive processes, this approach can allow for a very high degree of parallelism in multiprocessor architectures and distributed computing environments.
RNA-Seq analyzes complementary DNA (cDNA) by means of highly efficient, next-generation DNA sequencing methods and subsequent mapping of short sequence fragments (reads) onto the reference genome.
As quantitative transcript profiling by massively parallel sequencing is potentially affected by the accuracy of the mapping of short reads, we performed an in silico analysis to evaluate this.
We have created a web portal, TagScan at http://www.isrec.isb-sib.ch/tagger, for rapid mapping of short oligo sequences to large sequence databases comprising full genomes or transcriptomes (i.e. full length mRNA sequences from human, mouse, bee, drosophila, dog, rat, cow, and chimpanzee).
Bioinformatic analysis of RNA-seq data should involve mapping of short reads to the genome [ 17].
However, the detection of ASE depends critically on accurate mapping of short reads in the presence of sequence variation.
Because Bowtie 2 was designed for high-throughput mapping of short sequences (50 200 bp), fewer than 5% of full-length 2D reads could be mapped.
Indel calling from short reads next-generation sequencing data is especially difficult, because the presence of polymorphic indels obscures mapping of short reads.
Our data show that the effect of indels on the mapping of short sequencing reads is a major source of false positive for ASE.
