countreadgcpercent

countreadgcpercent calculates the GC content percentage for each DNA read aligned to a reference genome to quantify per-read guanine (G) and cytosine (C) composition in next-generation sequencing (NGS) datasets.


Key Features:

  • GC Content Calculation: Determines the percentage of guanine (G) and cytosine (C) bases in each DNA read aligned to a reference genome.
  • Reference-aware per-read analysis: Produces per-read GC metrics in the context of reads aligned to a reference genome.
  • Integration with Galaxy Project: Implements execution within the Galaxy platform infrastructure.
  • Scalability: Processes large NGS datasets to compute GC percentages across many reads in batch.

Scientific Applications:

  • Genomic Characterization: Profiles per-read GC content to inform analyses of chromatin structure and gene regulation.
  • Comparative Genomics: Compares GC content distributions across species or strains for evolutionary and diversity studies.
  • Quality Control: Assesses GC content distributions to detect biases introduced during library preparation or sequencing.

Methodology:

Calculates per-read GC percentage by counting guanine (G) and cytosine (C) bases in DNA reads aligned to a reference genome from NGS datasets.

Topics

Collections

Details

Maturity:
Mature
Tool Type:
web application
Operating Systems:
Linux, Windows, Mac
Added:
12/19/2016
Last Updated:
11/25/2024

Operations

Data Inputs & Outputs

Publications

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