SEDA
SEDA processes FASTA files containing DNA and protein sequences to prepare and transform sequence datasets for downstream phylogenetic and selection analyses.
Key Features:
- FASTA processing: Processes FASTA files containing DNA and protein sequences for dataset preparation.
- Data transformation protocols: Transforms genome datasets into formats suitable for downstream analyses.
- Remove isoforms operation: Removes coding-sequence isoforms to accelerate generation of sequence data files for phylogenetic analyses.
Scientific Applications:
- Gene evolution studies: Enables analysis of comprehensive genome datasets beyond model species, exemplified by investigation of the GULO gene across Protostomian groups (Molluscs, Priapulida, Arachnida) revealing putative functional genes.
- Positive selection analysis: Supports identification of positively selected amino-acid sites within gene families, demonstrated for primate HLA immunity genes where MHC class I and II show significant positive selection alongside purifying selection.
Methodology:
Operations explicitly include the "Remove isoforms" operation and transformations of FASTA DNA/protein datasets into formats suitable for downstream phylogenetic and selection analyses.
Topics
Collections
Details
- License:
- GPL-3.0
- Maturity:
- Emerging
- Cost:
- Free of charge
- Tool Type:
- command-line tool, desktop application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- Java
- Added:
- 5/3/2018
- Last Updated:
- 5/30/2023
Operations
Publications
López-Fernández H, Duque P, Henriques S, Vázquez N, Fdez-Riverola F, Vieira CP, Reboiro-Jato M, Vieira J. Bioinformatics Protocols for Quickly Obtaining Large-Scale Data Sets for Phylogenetic Inferences. Interdisciplinary Sciences: Computational Life Sciences. 2018;11(1):1-9. doi:10.1007/s12539-018-0312-5. PMID:30511150.
López-Fernández H, Duque P, Vázquez N, Fdez-Riverola F, Reboiro-Jato M, Vieira CP, Vieira J. SEDA: A Desktop Tool Suite for FASTA Files Processing. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2022;19(3):1850-1860. doi:10.1109/tcbb.2020.3040383.