R453Plus1Toolbox

R453Plus1Toolbox: Analysis of Roche 454 Sequencing Data in R/Bioconductor

R453Plus1Toolbox integrates Roche 454 sequencing data into the R/Bioconductor environment and extends native Roche software functionality with statistical analysis, quality control, variant annotation, visualization, and structural variant detection.


Key Features:

  • Data Importation: Imports projects generated by Roche 454 data analysis software into R/Bioconductor for downstream statistical and graphical analysis.
  • Quality Assurance: Implements quality control methods to assess sequencing data accuracy and reliability.
  • Variant Annotation and Visualization: Annotates detected genetic variants and provides functions for graphical representation of variant data.
  • Structural Variant Detection Pipeline: Detects structural variants, including balanced chromosomal translocations, to identify genomic rearrangements.
  • Customizable Workflows: Supports adaptable analytical workflows within the R/Bioconductor framework for project-specific analyses.

Scientific Applications:

  • Genomic Variant Analysis: Enables detection and interpretation of genetic and structural variants in Roche 454 sequencing datasets for structural genomics and personalized medicine research.

Methodology:

Processes Roche 454 sequencing projects by importing native output into R/Bioconductor, applying quality control procedures, performing statistical analyses, annotating genetic variants, visualizing variant data, and executing a pipeline for structural variant detection, including balanced chromosomal translocations.

Topics

Collections

Details

License:
GPL-3.0
Tool Type:
command-line tool, library
Operating Systems:
Linux, Windows, Mac
Programming Languages:
R
Added:
1/17/2017
Last Updated:
12/30/2018

Operations

Data Inputs & Outputs

Publications

Klein H, Bartenhagen C, Kohlmann A, Grossmann V, Ruckert C, Haferlach T, Dugas M. R453Plus1Toolbox: an R/Bioconductor package for analyzing Roche 454 Sequencing data. Bioinformatics. 2011;27(8):1162-1163. doi:10.1093/bioinformatics/btr102. PMID:21349869.

Documentation

Downloads