runLimma: runLimma
In nephantes/debrowser_bioconductor_release: Interactive Differential Expresion Analysis Browser
Description
Usage
Arguments
Value
Examples
Description
Run Limma algorithm on the selected conditions. Output is
to be used for the interactive display.
Usage
1
Arguments
data,
A matrix that includes all the expression raw counts,
rownames has to be the gene, isoform or region names/IDs
columns,
is a vector that includes the columns that are going
to be analyzed. These columns has to match with the given data.
conds,
experimental conditions. The order has to match
with the column order
params,
normfact: Calculate normalization factors to scale the raw
library sizes. Values can be "TMM","RLE","upperquartile","none".
fitType, fitting method; "ls" for least squares or "robust"
for robust regression
normBet: Normalizes expression intensities so that the
intensities or log-ratios have similar distributions across a set of arrays.
rowsum.filter: regions/genes/isoforms with total count
(across all samples) below this value will be filtered out
Value
Limma results
Examples
1
x <- runLimma()
nephantes/debrowser_bioconductor_release documentation built on May 29, 2019, 7:15 a.m.
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Description Usage Arguments Value Examples
Description
Run Limma algorithm on the selected conditions. Output is to be used for the interactive display.
Usage
1 |
Arguments
data, |
A matrix that includes all the expression raw counts, rownames has to be the gene, isoform or region names/IDs |
columns, |
is a vector that includes the columns that are going to be analyzed. These columns has to match with the given data. |
conds, |
experimental conditions. The order has to match with the column order |
params, |
normfact: Calculate normalization factors to scale the raw library sizes. Values can be "TMM","RLE","upperquartile","none". fitType, fitting method; "ls" for least squares or "robust" for robust regression normBet: Normalizes expression intensities so that the intensities or log-ratios have similar distributions across a set of arrays. rowsum.filter: regions/genes/isoforms with total count (across all samples) below this value will be filtered out |
Value
Limma results
Examples
1 | x <- runLimma()
|
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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