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.
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
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