compareoverlappingsmallref
compareoverlappingsmallref identifies overlaps between query sequences and a small reference dataset to support analysis of high-throughput next-generation DNA sequencing data.
Key Features:
- Overlap Identification: Detects query sequences that overlap entries in a provided small reference dataset.
- Integration with Galaxy Project: Operates within the Galaxy framework to be executed as part of Galaxy workflows and histories.
- Scalability for Biomedical Analyses: Designed to handle large-scale genomic datasets typical of next-generation sequencing studies.
Scientific Applications:
- Genomic Research: Identifies overlaps with small reference genomes or gene sets to investigate genetic variation, mutations, or regulatory elements.
- Transcriptomics and Epigenetics: Finds overlaps with known transcripts or epigenetic markers to inform analyses of gene expression patterns and modifications.
- Comparative Genomics: Compares sequences across species or strains to identify conserved elements of potential functional significance.
Methodology:
Computational algorithms detect overlaps between query sequences and a small reference dataset and the tool is executed within the Galaxy framework.
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
Sequence comparison
Inputs
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.