bioconductor-fourcseq¶

Summary¶

FourCSeq is an R package dedicated to the analysis of (multiplexed) 4C sequencing data. The package provides a pipeline to detect specific interactions between DNA elements and identify differential interactions between conditions. The statistical analysis in R starts with individual bam files for each sample as inputs. To obtain these files, the package contains a python script (extdata/python/demultiplex.py) to demultiplex libraries and trim off primer sequences. With a standard alignment software the required bam files can be then be generated.

Home¶

http://bioconductor.org/packages/release/bioc/html/FourCSeq.html

Versions¶

1.4.0

License¶

GPL (>= 3)

Meta¶

package:
  name: bioconductor-fourcseq
  version: 1.4.0
source:
  fn: FourCSeq_1.4.0.tar.gz
  url: https://bioarchive.galaxyproject.org/FourCSeq_1.4.0.tar.gz
  md5: 1fa8c7291a9c0806ae9ada8e1f97e7f1
build:
  number: 1
  rpaths:
    - lib/R/lib/
    - lib/
requirements:
  build:
    - bioconductor-biobase
    - bioconductor-biostrings
    - 'bioconductor-deseq2 >=1.9.11'
    - bioconductor-genomicalignments
    - bioconductor-genomicranges
    - bioconductor-ggbio
    - bioconductor-rsamtools
    - bioconductor-rtracklayer
    - bioconductor-summarizedexperiment
    - 'r >=3.0'
    - r-fda
    - r-ggplot2
    - r-gtools
    - r-lsd
    - r-reshape2
  run:
    - bioconductor-biobase
    - bioconductor-biostrings
    - 'bioconductor-deseq2 >=1.9.11'
    - bioconductor-genomicalignments
    - bioconductor-genomicranges
    - bioconductor-ggbio
    - bioconductor-rsamtools
    - bioconductor-rtracklayer
    - bioconductor-summarizedexperiment
    - 'r >=3.0'
    - r-fda
    - r-ggplot2
    - r-gtools
    - r-lsd
    - r-reshape2
test:
  commands:
    - '$R -e "library(''FourCSeq'')"'
about:
  home: http://bioconductor.org/packages/release/bioc/html/FourCSeq.html
  license: 'GPL (>= 3)'
  summary: 'FourCSeq is an R package dedicated to the analysis of (multiplexed) 4C
    sequencing data. The package provides a pipeline to detect specific interactions
    between DNA elements and identify differential interactions between conditions.
    The statistical analysis in R starts with individual bam files for each sample
    as inputs. To obtain these files, the package contains a python script (extdata/python/demultiplex.py)
    to demultiplex libraries and trim off primer sequences. With a standard alignment
    software the required bam files can be then be generated.'