gblocks_oneclick

gblocks_oneclick removes poorly aligned positions and divergent regions from multiple sequence alignments to improve alignment quality for downstream analyses such as phylogenetic inference, functional annotation, and comparative genomics.


Key Features:

  • Automated Sequence Cleaning: Automates removal of ambiguously aligned segments and divergent regions from multiple sequence alignments.
  • Reproducibility and Transparency: Operates within the Galaxy framework to record analysis steps and support reproducible workflows.
  • Scalability for Large Datasets: Processes large-scale datasets typical of next-generation sequencing outputs.

Scientific Applications:

  • Phylogenetic Analysis: Produces cleaner alignments that improve accuracy of phylogenetic tree construction.
  • Functional Genomics: Removes regions of alignment uncertainty to support more reliable functional annotation from alignments.
  • Comparative Genomics: Refines alignments for comparative analyses across species or strains to facilitate evolutionary and genetic studies.

Methodology:

Identifies and eliminates poorly aligned positions within multiple sequence alignments by evaluating alignment blocks using user-defined criteria such as gap content and conservation levels to retain the most reliable regions.

Topics

Collections

Details

Maturity:
Mature
Tool Type:
web application
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.

Links