debCAM-package: debCAM: A package for fully unsupervised deconvolution of...

Description References

Description

The core function in this package is CAM which achieves fully unsupervised deconvolution on mixture expression profiles. Each step in CAM can also be performed separately by CAMPrep, CAMMGCluster and CAMASest in a more flexible workflow. MGstatistic can help extract a complete marker list from CAM results. MDL can help decide the underlying subpopulation number. With other functions, e.g. AfromMarkers and MGstatistic, this package can also perform supervised deconvolution based on prior knowledge of molecular markers, subpopulation-specific expression matrix (S) or proportion matrix (A). Semi-supervised deconvolution can be achieved by combining molecular markers from CAM and from prior knowledge to analyze mixture expressions.

References

Wang, N., Hoffman, E. P., Chen, L., Chen, L., Zhang, Z., Liu, C., <e2><80><a6> Wang, Y. (2016). Mathematical modelling of transcriptional heterogeneity identifies novel markers and subpopulations in complex tissues. Scientific Reports, 6, 18909. http://doi.org/10.1038/srep18909


debCAM documentation built on Nov. 8, 2020, 5:33 p.m.