Bcbio-nextgen
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Application data |
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| Created by | Brad Chapman et al. |
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| Biological application domain(s) | Workflows |
| Principal bioinformatics method(s) | Sequencing quality control, filtering, Sequence trimming, Read mapping, Peak calling, Differential expression analysis, genomic region matching, Sequence alignment, Genotyping, Sequence motif recognition |
| Created at | Mass General Hospital, Harvard Public School of Health, Science for Life Laboratory Stockholm among other contributors |
| Maintained? | Yes |
| Input format(s) | FASTQ |
| Output format(s) | FASTQ, SAM, BAM, BED, VCF, PDF |
| Programming language(s) | Python |
| Resource type(s) | Script |
| Licence | MIT |
| Operating system(s) | platform-independent |
Summary: Python scripts and modules for automated next gen sequencing analysis. These provide a fully automated pipeline for taking sequencing results from an Illumina sequencer, converting them to standard Fastq format, aligning to a reference genome, doing SNP calling, and producing a summary PDF of results.
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Description
All documentation is mantained in the official GitHub site
Roman Valls Guimera contributes in bcbio-nextgen development and in the SeqAhead COST action BM1006 "Next Generation Sequencing Data Analysis Network". The complete list of tools developed by the SeqAhead network can be found here.
Links
References
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