CDSeq-R-package {CDSeq}R Documentation

CDSeq: A package for complete deconvolution using sequencing data

Description

CDSeq-R-package takes bulk RNA-seq data as input and simultaneously returns estimates of both cell-type-specific gene expression profiles and sample-specific cell-type proportions.

Reduce-Recover

CDSeq uses reduce-recovery strategy and CPU parallel computing to speed up the deconvolution.

Hyperparameter estimation

Estimate hyperparameter for cell-type-specific GEPs (i.e. beta) using reference profile when cell_type_number is scalar.

Estimating number of cell type

Estimate number of cell types when cell_type_number is a vector of integers.

Partition on input bulk RNA-seq data

When block_number (number of partition on the bulk RNASeq data) is 1, whole bulk_data will be used. GEP is not from reduce-recovery.

Author(s)

Kai Kang, David Huang, kangkai0714@gmail.com

References

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007510


[Package CDSeq version 1.0.8 Index]