runEdgeR: runEdgeR
In nephantes/debrowser_bioconductor_release: Interactive Differential Expresion Analysis Browser
Description
Usage
Arguments
Value
Examples
Description
Run EdgeR 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".
dispersion: either a numeric vector of dispersions or a character
string indicating that dispersions should be taken from the data
object. If a numeric vector, then can be either of length one or
of length equal to the number of genes. Allowable character
values are "common", "trended", "tagwise" or "auto".
Default behavior ("auto" is to use most complex dispersions
found in data object.
testType: exactTest or glmLRT. exactTest: Computes p-values for differential
abundance for each gene between two digital libraries, conditioning
on the total count for each gene. The counts in each group as a
proportion of the whole are assumed to follow a binomial distribution.
glmLRT: Fit a negative binomial generalized log-linear model to the read
counts for each gene. Conduct genewise statistical tests for a given
coefficient or coefficient contrast.
rowsum.filter: regions/genes/isoforms with total count
(across all samples) below this value will be filtered out
Value
edgeR results
Examples
1
x <- runEdgeR()
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 EdgeR 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". dispersion: either a numeric vector of dispersions or a character string indicating that dispersions should be taken from the data object. If a numeric vector, then can be either of length one or of length equal to the number of genes. Allowable character values are "common", "trended", "tagwise" or "auto". Default behavior ("auto" is to use most complex dispersions found in data object. testType: exactTest or glmLRT. exactTest: Computes p-values for differential abundance for each gene between two digital libraries, conditioning on the total count for each gene. The counts in each group as a proportion of the whole are assumed to follow a binomial distribution. glmLRT: Fit a negative binomial generalized log-linear model to the read counts for each gene. Conduct genewise statistical tests for a given coefficient or coefficient contrast. rowsum.filter: regions/genes/isoforms with total count (across all samples) below this value will be filtered out |
Value
edgeR results
Examples
1 | x <- runEdgeR()
|
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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