View source: R/expression_funks.R
correlationRpkmCopyNo | R Documentation |
mean
value is used. Note, that only genes are considered that have
some expression in any tissue, never expressed genes are discarded from the
analysis.Generates a data.frame of the Genes' names, copy numbers, and expression
values (RPKM). Furthermore, computes a lm model for the observed data. If
expression levels are extracted for more than a single tissue the
mean
value is used. Note, that only genes are considered that have
some expression in any tissue, never expressed genes are discarded from the
analysis.
correlationRpkmCopyNo(rpkm.df = rpkm.rna.seq.counts, r.gene.col = "id",
r.rpkm.col = "expression", r.tissue.col = "tissue",
copy.no.df = gene.copy.number.df, c.gene.col = "Gene.no.expr.var",
c.copy.no.col = "copy.no", tissues = unique(rpkm.df[, r.tissue.col]),
stat.funk = mean, lapply.funk = lapply)
rpkm.df |
An instance of data frame holding the genes expression counts
(RPKM). Default is |
r.gene.col |
A string or integer identifying the column of
|
r.rpkm.col |
A string or integer identifying the column of
|
r.tissue.col |
A string or integer identifying the column of
|
copy.no.df |
An instance of |
c.gene.col |
A string or integer identifying the column of
|
c.copy.no.col |
A string or integer identifying the column of
|
tissues |
A character of minimum length one in which the tissues to
extract expression levels for are stored. Default is |
stat.funk |
The statistical measure applied on the expression values
found for a respective gene within the argument |
lapply.funk |
One of |
A list with entries: data
the above data.frame, lm
the
above mentioned computed generalized linear model, and the R^2
(R
squared) value.
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