Showing 5 of total 5 results (show query)
bioc
maftools:Summarize, Analyze and Visualize MAF Files
Analyze and visualize Mutation Annotation Format (MAF) files from large scale sequencing studies. This package provides various functions to perform most commonly used analyses in cancer genomics and to create feature rich customizable visualzations with minimal effort.
Maintained by Anand Mayakonda. Last updated 5 months ago.
datarepresentationdnaseqvisualizationdrivermutationvariantannotationfeatureextractionclassificationsomaticmutationsequencingfunctionalgenomicssurvivalbioinformaticscancer-genome-atlascancer-genomicsgenomicsmaf-filestcgacurlbzip2xz-utilszlib
461 stars 14.59 score 948 scripts 18 dependents
sachaepskamp
qgraph:Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation
Fork of qgraph - Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>.
Maintained by Sacha Epskamp. Last updated 1 years ago.
69 stars 11.43 score 1.2k scripts 63 dependentsbioc
graphite:GRAPH Interaction from pathway Topological Environment
Graph objects from pathway topology derived from KEGG, Panther, PathBank, PharmGKB, Reactome SMPDB and WikiPathways databases.
Maintained by Gabriele Sales. Last updated 5 months ago.
pathwaysthirdpartyclientgraphandnetworknetworkreactomekeggmetabolomicsbioinformaticsmirrorpathway-analysis
8 stars 10.24 score 122 scripts 21 dependentsbioc
ReactomeGSA:Client for the Reactome Analysis Service for comparative multi-omics gene set analysis
The ReactomeGSA packages uses Reactome's online analysis service to perform a multi-omics gene set analysis. The main advantage of this package is, that the retrieved results can be visualized using REACTOME's powerful webapplication. Since Reactome's analysis service also uses R to perfrom the actual gene set analysis you will get similar results when using the same packages (such as limma and edgeR) locally. Therefore, if you only require a gene set analysis, different packages are more suited.
Maintained by Johannes Griss. Last updated 4 months ago.
genesetenrichmentproteomicstranscriptomicssystemsbiologygeneexpressionreactome
22 stars 8.50 score 67 scripts 1 dependentsbioc
BulkSignalR:Infer Ligand-Receptor Interactions from bulk expression (transcriptomics/proteomics) data, or spatial transcriptomics
Inference of ligand-receptor (LR) interactions from bulk expression (transcriptomics/proteomics) data, or spatial transcriptomics. BulkSignalR bases its inferences on the LRdb database included in our other package, SingleCellSignalR available from Bioconductor. It relies on a statistical model that is specific to bulk data sets. Different visualization and data summary functions are proposed to help navigating prediction results.
Maintained by Jean-Philippe Villemin. Last updated 3 months ago.
networkrnaseqsoftwareproteomicstranscriptomicsnetworkinferencespatial
5.22 score 15 scripts