Package: coMET
Type: Package
Title: coMET: visualisation of regional epigenome-wide association scan
(EWAS) results and DNA co-methylation patterns
Version: 1.4.4
Date: 2016-06-12
Author: Tiphaine C. Martin, Thomas Hardiman, Idil Yet, Pei-Chien Tsai, Jordana T. Bell
Maintainer: Tiphaine Martin <tiphaine.martin@kcl.ac.uk>
Description: Visualisation of EWAS results in a genomic region. In addition to phenotype-association P-values, coMET also generates plots of co-methylation patterns and provides a series of annotation tracks. It can be used to other omic-wide association scans as long as the data can be translated to genomic level and for any species.
Depends: R (>= 3.3.0), grid, utils, biomaRt, Gviz, psych
Suggests: knitr, RUnit, BiocGenerics, BiocStyle
Imports: colortools, hash, grDevices, gridExtra, rtracklayer, IRanges, S4Vectors, GenomicRanges, ggbio, ggplot2, trackViewer, stats, corrplot
License: GPL (>= 2)
URL: http://epigen.kcl.ac.uk/comet
biocViews: Software, DifferentialMethylation, Visualization,
Sequencing, Genetics, FunctionalGenomics, Microarray,
MethylationArray, MethylSeq, ChIPSeq, DNASeq, RiboSeq, RNASeq,
ExomeSeq, DNAMethylation, GenomeWideAssociation
VignetteBuilder: knitr
NeedsCompilation: no
Repository: Bioconductor
Packaged: 2016-06-13 05:03:36 UTC; biocbuild
Package: GenomeGraphs
Version: 1.32.0
Title: Plotting genomic information from Ensembl
Author: Steffen Durinck <sdurinck@gmail.com>, James Bullard <bullard@berkeley.edu>
Maintainer: Steffen Durinck <sdurinck@gmail.com>
Depends: R (>= 2.10), methods, biomaRt, grid
biocViews: Visualization, Microarray
Description: Genomic data analyses requires integrated visualization of known genomic information and new experimental data. GenomeGraphs uses the biomaRt package to perform live annotation queries to Ensembl and translates this to e.g. gene/transcript structures in viewports of the grid graphics package. This results in genomic information plotted together with your data. Another strength of GenomeGraphs is to plot different data types such as array CGH, gene expression, sequencing and other data, together in one plot using the same genome coordinate system.
Collate: GenomeGraphs-classes.R GenomeGraphs-methods.R GenomeGraphs.R
Overlay.R
License: Artistic-2.0
LazyLoad: yes
NeedsCompilation: no
Packaged: 2016-05-05 01:57:20 UTC; biocbuild
Package: Roleswitch
Type: Package
Title: Infer miRNA-mRNA interactions using paired expression data from
a single sample
Version: 1.10.0
Date: 2013-12-20
Author: Yue Li
Maintainer: Yue Li <yueli@cs.toronto.edu>
Description: Infer Probabilities of MiRNA-mRNA Interaction Signature
(ProMISe) using paired expression data from a single sample.
Roleswitch operates in two phases by inferring the probability
of mRNA (miRNA) being the targets ("targets") of miRNA (mRNA),
taking into account the expression of all of the mRNAs (miRNAs)
due to their potential competition for the same miRNA (mRNA).
Due to dynamic miRNA repression in the cell, Roleswitch assumes
that the total transcribed mRNA levels are higher than the
observed (equilibrium) mRNA levels and iteratively updates the
total transcription of each mRNA targets based on the above
inference. NB: in the paper, we used ProMISe as both the model
name and inferred score name.
Depends: R (>= 2.10), pracma, reshape, plotrix, microRNA, biomaRt, Biostrings, Biobase, DBI
Suggests: ggplot2
License: GPL-2
URL: http://www.cs.utoronto.ca/~yueli/roleswitch.html
Lazyload: yes
biocViews: miRNA
NeedsCompilation: no
Packaged: 2016-05-06 03:59:52 UTC; biocbuild
Package: DrugVsDisease
Type: Package
Title: Comparison of disease and drug profiles using Gene set
Enrichment Analysis
Version: 2.12.0
Date: 2015-04-13
Author: C. Pacini
Maintainer: j. Saez-Rodriguez <saezrodriguez@ebi.ac.uk>
Description: This package generates ranked lists of differential gene
expression for either disease or drug profiles. Input data can
be downloaded from Array Express or GEO, or from local CEL
files. Ranked lists of differential expression and associated
p-values are calculated using Limma. Enrichment scores
(Subramanian et al. PNAS 2005) are calculated to a reference
set of default drug or disease profiles, or a set of custom
data supplied by the user. Network visualisation of significant
scores are output in Cytoscape format.
LazyData: yes
LazyLoad: yes
License: GPL-3
Depends: R (>= 2.10), affy, limma, biomaRt, ArrayExpress, GEOquery, DrugVsDiseasedata, cMap2data, qvalue
Imports: annotate, hgu133a.db, hgu133a2.db, hgu133plus2.db, RUnit, BiocGenerics, xtable
biocViews: Microarray, GeneExpression, Clustering
NeedsCompilation: no
Packaged: 2016-05-05 03:46:41 UTC; biocbuild
providing 
.