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Syksy / curatedPCaData

Bioconductor R-package: Curated Prostate Cancer Data
Creative Commons Attribution 4.0 International
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List of methods/packages for downstream processing and appending to corresponding fields in pData #8

Closed Syksy closed 2 years ago

Syksy commented 4 years ago

Methods with R-packages in GitHub/CRAN/BioConductor

xCell - cell types enrichment analysis xCell is a webtool that performs cell type enrichment analysis from gene expression data for 64 immune and stroma cell types. Data type required: RNA expression Output: Tumor purity / cell composition Notes: Perhaps better used via wrapper 'immunedeconv'

DeMix Deconvolution models for mixed transcriptomes from heterogeneous tumor samples with two or three components using expression data from RNAseq or microarray platforms. Data type required: RNA expression Output: Tumor purity / cell composition Notes: -

MCPcounter Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression Data type required: RNA expression Output: Cell populations Notes: Perhaps better used via wrapper 'immunedeconv'

EPIC Package implementing EPIC method to estimate the proportion of immune, stromal, endothelial and cancer or other cells from bulk gene expression data. Data type required: Bulk RNA expression Output: Notes: Perhaps better used via wrapper 'immunedeconv'

deconstructSigs (?) deconstructSigs aims to determine the contribution of known mutational processes to a tumor sample. Data type required: SNP or similar mutation data Output: Known mutational processes Notes: COSMIC v3.1 mutational signature database has to be incorporated manually to deconstructSigs.

ABSOLUTE (?) ABSOLUTE can estimate purity/ploidy, and from that compute absolute copy-number and mutation multiplicities. Data type required: HAPSEG file or a segmentation file Output: Tumor purity Notes:

AR activity score methods Notes: multiple possibilities, e.g. Hieronimus, et al.

immunedeconv an R package for unified access to computational methods for estimating immune cell fractions from bulk RNA sequencing data. Data type required: Method-dependent GEX Output: Immune decomposition Notes: Wrapper package for methods quantiseq, timer, cibersort, cibersort_abs, mcp_counter, xcell, epic

Methodology outside R

pVACtools / NetMHCPan (?) Neoantigen load Data type required: MAF Output: Neoantigen load Notes: Written in Python. Set up in Jim's cluster.

CIBERSORT Estimation of the abundances of member cell types in a mixed cell population, using gene expression data. Data type required: RNA expression Output: Notes: Behind registration wall

quanTIseq Quantifying tumor-infiltrating immune cells from RNA sequencing data Data type required: FASTQ of RNA-seq (?) Output: Immune cell decomposition Notes: Docker-image

jhcreed commented 4 years ago

Gene-based risk scores

Alternative risk assessments ?

Syksy commented 2 years ago

Given the current nature and stage of the package, these options have largely been exhausted and the checklists are no longer up-to-date.