cshl_fastx_nucleotides_distribution
cshl_fastx_nucleotides_distribution computes position-specific nucleotide frequencies in DNA sequencing datasets and generates stacked-histogram graphs to represent nucleotide distributions from high-throughput technologies such as Solexa libraries.
Key Features:
- Visualization: Generates stacked-histogram graphs that display nucleotide composition across sequence positions.
- Position-specific frequency calculation: Calculates the frequency of each nucleotide (A, T, C, G) at various positions across sequences.
- High-throughput sequencing support: Operates on DNA sequencing datasets produced by high-throughput technologies such as Solexa libraries.
Scientific Applications:
- Biomedical research: Assists interpretation of sequence composition and identification of anomalous or informative nucleotide patterns in biological studies.
- Next-generation sequencing (NGS) data analysis: Summarizes position-wise nucleotide distributions to aid quality assessment and compositional analyses of large NGS datasets.
Methodology:
Processes sequencing data to calculate the frequency of each nucleotide (A, T, C, G) at each sequence position and uses these frequencies to generate a stacked-histogram graph.
Topics
Collections
Details
- Maturity:
- Mature
- Tool Type:
- web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Perl
- Added:
- 12/19/2016
- Last Updated:
- 11/24/2024
Operations
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.