classifieRc

classifieRc performs transcriptional subtype classification and functional annotation of colorectal cancer (CRC) transcriptomes to support molecular subtyping and biological interpretation.


Key Features:

  • Subtype Classification: Assigns CRC samples to established molecular subtype frameworks including the four Consensus Molecular Subtypes (CMS) and five intrinsic CRIS subtypes (CRIS).
  • Cross-Platform Compatibility: Processes transcriptional data from diverse assay and sequencing platforms for unified subtype assignment.
  • Cellular Composition Estimation: Estimates sample cell-type composition using MCP-counter and xCell.
  • Gene Set Enrichment Analysis (ssGSEA): Performs single-sample GSEA (ssGSEA) to profile pathway and gene-set activity per sample.
  • Transcription Factor Activity Prediction: Predicts transcription factor activities using DoRothEA.

Scientific Applications:

  • Molecular Subtyping of CRC: Classifies colorectal cancer samples into CMS and CRIS subtypes to enable subtype-specific analyses.
  • Prognostic and Therapeutic Insight: Generates subtype and pathway-level annotations that can inform prognosis and potential treatment strategies.
  • Discovery Research: Supports investigation of regulatory mechanisms, cellular composition, and pathway activity in transcriptome datasets.

Methodology:

Assigns samples to CMS and CRIS subtypes using established classifier gene sets and applies MCP-counter, xCell, ssGSEA, and DoRothEA for functional annotation of transcriptomes.

Topics

Details

License:
Not licensed
Cost:
Free of charge (with restrictions)
Tool Type:
web application, workflow
Operating Systems:
Mac, Linux, Windows
Programming Languages:
R, Java
Added:
7/20/2022
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

Gene expression profiling

Publications

Quinn GP, Sessler T, Ahmaderaghi B, Lambe S, VanSteenhouse H, Lawler M, Wappett M, Seligmann B, Longley DB, McDade SS. classifieR a flexible interactive cloud-application for functional annotation of cancer transcriptomes. BMC Bioinformatics. 2022;23(1). doi:10.1186/s12859-022-04641-x. PMID:35361119. PMCID:PMC8974006.

PMID: 35361119
PMCID: PMC8974006
Funding: - Cancer Research UK: C11884/A24367, C11884/A24387, C212/A13721 - HDR-UK: JHR1157-100/1230 - ECMC: C36697/A25176 - Biotechnology and Biological Sciences Research Council: BB/T002824/1

Links