DeMix: Deconvolution Models for Mixed Transcriptomes from Heterogeneous Tumor Samples

Implementation of a statistical method for deconvolving expression data of mixed cancer tissues. It provides an estimation of both tumor proportion and tumor-specific expression (when neither is known a priori), and an estimation of individualized expression profiles for both tumor and stromal tissues.

AuthorJaeil Ahn
Date of publication2016-11-05 13:59:18
Maintainer"Jaeil Ahn" <ja1030@georgetown.edu>
LicenseArtistic-2.0
Version0.2.0
http://r-forge.r-project.org/projects/demix

View on R-Forge

Files

DeMix/DESCRIPTION
DeMix/NAMESPACE
DeMix/R
DeMix/R/Filter.R DeMix/R/Model.R DeMix/R/Normalization.R DeMix/R/scalar.R
DeMix/build
DeMix/build/DeMix.pdf
DeMix/data
DeMix/data/datalist
DeMix/data/ntot_NT_Liver.RData
DeMix/inst
DeMix/inst/COPYRIGHTS
DeMix/inst/NEWS.Rd
DeMix/man
DeMix/man/DeMix-package.Rd DeMix/man/Filter.Rd DeMix/man/Normalization.Rd DeMix/man/ntot_NT_Liver-data.Rd
DeMix/src
DeMix/src/bayes_para.h
DeMix/src/main_firstparallel.c

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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All documentation is copyright its authors; we didn't write any of that.