bam_to_sam_parallel

bam_to_sam_parallel converts a list of Binary Alignment/Map (BAM) files to Sequence Alignment/Map (SAM) format using parallel processing to accelerate large-scale alignment file conversion for downstream analyses.


Key Features:

  • Parallel Processing: Uses parallel computing to convert multiple BAM files concurrently, reducing overall conversion time versus sequential processing.
  • Support for Large Reads: Handles short and long reads, supporting sequences up to 128 Mbp in length.
  • Efficiency and Compactness: Produces SAM format output noted for flexibility, compact size, and efficient random access capabilities for large genomic datasets.
  • Integration with Bioinformatics Pipelines: Facilitates downstream processing with tools such as SAMtools, including indexing and variant calling.

Scientific Applications:

  • Genomic Research: Provides converted alignment files required for alignment processing and downstream analyses in genomic studies.
  • Metagenomics and Phylogenetics: Supports preprocessing of alignment data for metagenomic analyses and phylogenetic studies within larger analysis workflows.

Methodology:

Operates within computational frameworks such as Galaxy to launch tools or workflows on high-performance clusters and integrate into larger bioinformatics pipelines, facilitating data management and processing in research environments such as the Institut Pasteur.

Topics

Collections

Details

Maturity:
Mature
Tool Type:
web application
Operating Systems:
Linux, Windows, Mac
Added:
12/19/2016
Last Updated:
6/16/2020

Operations

Data Inputs & Outputs

Publications

Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078-2079. doi:10.1093/bioinformatics/btp352. PMID:19505943. PMCID:PMC2723002.

Afgan E, Baker D, van den Beek M, Blankenberg D, Bouvier D, Čech M, Chilton J, Clements D, Coraor N, Eberhard C, Grüning B, Guerler A, Hillman-Jackson J, Von Kuster G, Rasche E, Soranzo N, Turaga N, Taylor J, Nekrutenko A, Goecks J. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Research. 2016;44(W1):W3-W10. doi:10.1093/nar/gkw343. PMID:27137889. PMCID:PMC4987906.

Mareuil F, Doppelt-Azeroual O, Ménager H. A public Galaxy platform at Pasteur used as an execution engine for web services. Unknown Journal. 2017. doi:10.7490/f1000research.1114334.1.

Documentation

Links