PcaGsea: PcaGsea
In princyparsana/netpca: GSEA for Principal Components Analysis
Description
Usage
Arguments
Value
Author(s)
Description
find loadings of a numeric matrix and do GSEA on each loadings vector
Usage
1
2
Arguments
exp
pxn expression matrix (genes in rows, samples in columns)
geneset
a list where each element contains a vector of genes, and the list
names are the names of the genesets
n
the number of principal components to do the calculations on (n=10 suggested).
cumulative.proportion
Keep enough principal components to account for this total proportion of the variance. Over-rides n.
proportion.variance
Keep any principal components which account for at least this
proportion of the variance. Over-rides n and
cumulative.proportion.
...
arguments passed on to prcomp function. scale.=TRUE is advisable.
Value
a list with four elements. 1: the loadings of the expression matrix
for the components kept, 2: the scores, 3: the unadjusted p-values
from GSEA, and 4: the prcomp object which can be used to make a
screeplot, calculate scores from new data, etc.
Author(s)
Princy Parsana and Levi Waldron
princyparsana/netpca documentation built on May 25, 2019, 12:20 p.m.
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Description Usage Arguments Value Author(s)
Description
find loadings of a numeric matrix and do GSEA on each loadings vector
Usage
1 2 |
Arguments
exp |
pxn expression matrix (genes in rows, samples in columns) |
geneset |
a list where each element contains a vector of genes, and the list names are the names of the genesets |
n |
the number of principal components to do the calculations on (n=10 suggested). |
cumulative.proportion |
Keep enough principal components to account for this total proportion of the variance. Over-rides n. |
proportion.variance |
Keep any principal components which account for at least this proportion of the variance. Over-rides n and cumulative.proportion. |
... |
arguments passed on to prcomp function. scale.=TRUE is advisable. |
Value
a list with four elements. 1: the loadings of the expression matrix for the components kept, 2: the scores, 3: the unadjusted p-values from GSEA, and 4: the prcomp object which can be used to make a screeplot, calculate scores from new data, etc.
Author(s)
Princy Parsana and Levi Waldron
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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