_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-rcistarget 1.28.1
Propagated dependencies: r-arrow@20.0.0 r-aucell@1.30.1 r-biocgenerics@0.54.0 r-data-table@1.17.2 r-dplyr@1.1.4 r-genomeinfodb@1.44.0 r-genomicranges@1.60.0 r-gseabase@1.70.0 r-r-utils@2.13.0 r-s4vectors@0.46.0 r-summarizedexperiment@1.38.1 r-tibble@3.2.1 r-zoo@1.8-14
Channel: guix
Location: gnu/packages/bioconductor.scm (gnu packages bioconductor)
Home page: https://aertslab.org/#scenic
Licenses: GPL 3
Synopsis: Identify transcription factor binding motifs enriched on a gene list
Description:

RcisTarget identifies transcription factor binding motifs (TFBS) over-represented on a gene list. In a first step, RcisTarget selects DNA motifs that are significantly over-represented in the surroundings of the transcription start site (TSS) of the genes in the gene-set. This is achieved by using a database that contains genome-wide cross-species rankings for each motif. The motifs that are then annotated to TFs and those that have a high Normalized Enrichment Score (NES) are retained. Finally, for each motif and gene-set, RcisTarget predicts the candidate target genes (i.e. genes in the gene-set that are ranked above the leading edge).

Total results: 2