sensDE_limma: Use limma to find differentially expressed genes
In NCBI-Hackathons/robustSingleCell: Robust Subpopulation dEcision Trees
Description
Use limma to find differentially expressed genes
Usage
1
2
sensDE_limma(expression, unique_cluster_membership, q_thresh = 0.1,
FC_thresh = 1.2)
Arguments
expression
m by n expression matrix with $m$ genes and $n$ cells
unique_cluster_membership
a logical vector of size $n$ that indicates membership
q_thresh
q value threshold for DE analysis
FC_thresh
fold change threshold for DE analysis
NCBI-Hackathons/robustSingleCell documentation built on May 9, 2019, 3:27 a.m.
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Description
Use limma to find differentially expressed genes
Usage
1 2 | sensDE_limma(expression, unique_cluster_membership, q_thresh = 0.1,
FC_thresh = 1.2)
|
Arguments
expression |
m by n expression matrix with $m$ genes and $n$ cells |
unique_cluster_membership |
a logical vector of size $n$ that indicates membership |
q_thresh |
q value threshold for DE analysis |
FC_thresh |
fold change threshold for DE analysis |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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