runPCA: Perform principal component analysis on traits
In AndersenLab/easysorter: A Package to Read, Process, and Manage Data from the Andersen Lab's Worm Sorter
Description
Usage
Arguments
Value
Description
Perform principal component analysis on traits
Usage
1
Arguments
df
A regressed dataframe of HTA traits for PCA
Value
pca_obj, a PCA object output from princomp;
loadings, a vector of loadings for each HTA trait into each PC;
cumsums, a matrix of cumulative sums of variance explained by each PC;
RIAILPCphenos, a dataframe of PC values for each strain;
corr_PC_trait, correlation of each trait to each PC
AndersenLab/easysorter documentation built on Nov. 27, 2020, 4:26 a.m.
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Description Usage Arguments Value
Description
Perform principal component analysis on traits
Usage
1 |
Arguments
df |
A regressed dataframe of HTA traits for PCA |
Value
pca_obj, a PCA object output from princomp; loadings, a vector of loadings for each HTA trait into each PC; cumsums, a matrix of cumulative sums of variance explained by each PC; RIAILPCphenos, a dataframe of PC values for each strain; corr_PC_trait, correlation of each trait to each PC
R Package Documentation
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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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