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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