compute_permuted_corQ: Optimised to work with clustermq (to be used for LSF jobs)...
In barzine/barzinePhdR: Code developed while and for my PhD thesis at the EMBL-EBI
View source: R/genes-meta-analyses.R
compute_permuted_corQ R Documentation
Optimised to work with clustermq (to be used for LSF jobs)
and shuffle randomly one expression dataset before computing the correlation with the same labelled rows
from another dataset across the same set of different tissues
Description
Optimised to work with clustermq (to be used for LSF jobs)
and shuffle randomly one expression dataset before computing the correlation with the same labelled rows
from another dataset across the same set of different tissues
Usage
compute_permuted_corQ(rep, x, y, g.names, method = "spearman",
random = 145)
Arguments
rep
positive integer. The current iteration for
x
numeric data.frame for a first expression study
y
numeric data.frame for a second expression study
g.names
character vector. Names of the genes.
method
a character string indicating which correlation coefficient is to be computed.
One of "pearson", "spearman", "kendall".
random
positive integer. Random seed to add to "rep" so while the shuffling is random,
it can be reproduced.
Value
a random shuffling instance for compute_gene_cor
barzine/barzinePhdR documentation built on Nov. 23, 2024, 8:54 p.m.
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View source: R/genes-meta-analyses.R
| compute_permuted_corQ | R Documentation |
Optimised to work with clustermq (to be used for LSF jobs) and shuffle randomly one expression dataset before computing the correlation with the same labelled rows from another dataset across the same set of different tissues
Description
Optimised to work with clustermq (to be used for LSF jobs) and shuffle randomly one expression dataset before computing the correlation with the same labelled rows from another dataset across the same set of different tissues
Usage
compute_permuted_corQ(rep, x, y, g.names, method = "spearman",
random = 145)
Arguments
rep |
positive integer. The current iteration for |
x |
numeric data.frame for a first expression study |
y |
numeric data.frame for a second expression study |
g.names |
character vector. Names of the genes. |
method |
a character string indicating which correlation coefficient is to be computed. One of "pearson", "spearman", "kendall". |
random |
positive integer. Random seed to add to "rep" so while the shuffling is random, it can be reproduced. |
Value
a random shuffling instance for compute_gene_cor
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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