Serves as a post-alignment micro re-aligner for next-generation high throughput sequencing data. SRMA is a local re-alignment algorithm that can reduce the false positive variant detection rate with short-read next generation sequencing technology. This software exploits correlated alignments to construct a limited graph structure that illustrates these alignments and their differences in compact form.
Runs as a post-processing step in conjunction with an RNA-seq aligner and systematically corrects common alignment artifacts. Its key innovations are a two-pass splice junction alignment system that includes de novo splice junctions and the use of an empirically determined estimate of the fragment size distribution when resolving read pairs. RNASequel is useful in applications requiring the accurate identification of variants in RNA sequencing data, the discovery of RNA editing sites and the analysis of alternative splicing.
A post-processor for BAM files, resolving ambiguous alignment locations. MMR infers optimal mapping locations from the coverage density of other mapped reads. Filtering alignments with MMR can significantly improve the performance of downstream analyses like transcript quantitation and differential testing. Our efficient implementation of the MMR algorithm is easily applicable as a post-processing step to existing alignment files in BAM format. Its complexity scales linearly with the number of alignments and requires no further inputs.
Enables easy and fast post-processing for TopHat unmapped reads. The tool can be used to process TopHat-written unmapped reads to make them compatible with downstream tools such as samtools, the Picard suite and GATK, which is currently not possible with the stock unmapped reads. This will increase the utility of the immense amount of RNA-seq data that has been analyzed by TopHat.
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