sam_to_bam

sam_to_bam converts SAM (Sequence Alignment/Map) files to BAM (Binary Alignment Map) format to provide compact, indexed storage and random access for sequence alignment data from high-throughput sequencing.


Key Features:

  • Format Conversion: Converts plain-text SAM alignments into the binary BAM format for more compact storage and faster downstream processing.
  • Compatibility with Large Reads: Supports short and long reads, accommodating sequences up to 128 Mbp in length.
  • Integration with SAMtools Suite: Operates within the SAMtools ecosystem and interoperates with utilities for indexing, variant calling, and alignment viewing.
  • Efficiency in Data Handling: Produces smaller files and enables faster random access, supporting large-scale genomic analyses such as the 1000 Genomes Project.

Scientific Applications:

  • Genomic Research: Processes alignment data from high-throughput sequencing for applications in genomics, transcriptomics, and metagenomics.
  • Variant Analysis: Provides efficient storage and access to aligned reads to support downstream variant calling and identification of genetic variants associated with disease.

Methodology:

Reads SAM records (including metadata and per-read alignment information against a reference genome) and encodes them into the BAM binary format to optimize storage efficiency and computational performance.

Topics

Collections

Details

Maturity:
Mature
Tool Type:
web application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
C
Added:
12/19/2016
Last Updated:
8/16/2020

Operations

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