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chagall.med.cornell.edu - RNAseq can be roughly divided into two "types": Reference genome-based - an assembled genome exists for a species for which an RNAseq experiment is performed. It allows reads to be aligned against the reference genome and significantly improves...

www.healthcare.uiowa.edu - Long read alignment analysis. Generate a reports on sequence alignments for mappability vs read sizes, error patterns, annotations and rarefraction curve analysis. The most basic analysis only requires a BAM file, and outputs a web browser...

samstat.sourceforge.net - SAMStat is an efficient C program to quickly display statistics of large sequence files from next generation sequencing projects. When applied to SAM/BAM files all statistics are reported for unmapped, poorly and accurately mapped reads...

Learn about bioinformatics online by watching videos, reading engaging articles and practicing bioinformatics skills using public domain datasets.

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csb5.github.io - LoFreq* (i.e. LoFreq version 2) is a fast and sensitive variant-caller for inferring SNVs and indels from next-generation sequencing data. It makes full use of base-call qualities and other sources of errors inherent in sequencing (e.g. mapping or...

github.com - Key features Filters SNVs from any variant caller to remove false positives Calculates metrics based on BAM files and provides filtering not possible with other tools Fully user-configurable filtering (including which filters to use and their...

github.com - VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store...

github.com - jackalope simply and efficiently simulates (i) variants from reference genomes and (ii) reads from both Illumina and Pacific Biosciences (PacBio) platforms. It can either read reference genomes from FASTA files or simulate new ones. Genomic variants...

samtools.sourceforge.net - In current genome era, our day to day work is to handle the huge geneome sequences, expression data, several other datasets. This link provide a comprehensive list of commonly used sofware/tools.