GetTable: Obtain a genes x values table

Description

This is the main function to access slot data for all genes as a large matrix. If data from a particular gene (or a small set of genes) must be retrieved, use the GetData function. For analysis results, use the GetAnalysisTable function.

Usage

GetTable(
  data,
  type = DefaultSlot(data),
  columns = NULL,
  genes = Genes(data),
  ntr.na = TRUE,
  gene.info = FALSE,
  summarize = NULL,
  prefix = NULL,
  name.by = "Symbol",
  reorder.columns = FALSE
)

Value

A data frame containing the desired values

Arguments

data: A grandR object
type: Either a mode.slot (see details) or a regex to be matched against analysis names. Can also be a vector
columns: A vector of columns (either condition/cell names if the type is a mode.slot, or names in the output table from an analysis; use Columns(data,<analysis>) to learn which columns are available); all condition/cell names if NULL
genes: Restrict the output table to the given genes
ntr.na: For columns representing a 4sU naive sample, should types ntr,new.count and old.count be 0,0 and count (ntr.na=FALSE; can be any other slot than count) or NA,NA and NA (ntr.na=TRUE)
gene.info: Should the table contain the GeneInfo values as well (at the beginning)?
summarize: Should replicates by summarized? see details
prefix: Prepend each column in the output table (except for the gene.info columns) by the given prefix
name.by: A column name of Coldata(data). This is used as the rownames of the output table
reorder.columns: if TRUE, the columns in the output table are ordered according to column (otherwise according to their order in the grandR object)

Details

This is a convenience wrapper for GetData (values from data slots) and GetAnalysisTable (values from analyses). Types can refer to any of the two (and can be mixed). If there are types from both data and analyses, columns must be NULL. Otherwise columns must either be condition/cell names (if type refers to one or several data slots), or regular expressions to match against the names in the analysis tables.

Columns definitions for data slots can be given as a logical, integer or character vector representing a selection of the columns (samples or cells). The expression is evaluated in an environment having the Coldata, i.e. you can use names of Coldata as variables to conveniently build a logical vector (e.g., columns=Condition=="x").

To refer to data slots via type, the mode.slot syntax can be used: Each name is either a data slot, or one of (new,old,total) followed by a dot followed by a slot. For new or old, the data slot value is multiplied by ntr or 1-ntr. This can be used e.g. to obtain the new counts.

The summarization parameter can only be specified if columns is NULL. It is either a summarization matrix (GetSummarizeMatrix) or TRUE (in which case GetSummarizeMatrix(data) is called). If there a NA values, they are imputed as the mean per group!

Examples

Run this code

sars <- ReadGRAND(system.file("extdata", "sars.tsv.gz", package = "grandR"),
                  design=c("Condition",Design$dur.4sU,Design$Replicate))
sars <- Normalize(FilterGenes(sars))

head(GetTable(sars))
# DefaultSlot values, i.e. size factor normalized read counts for all samples
head(GetTable(sars,summarize=TRUE))
# DefaultSlot values averaged over the two conditions
head(GetTable(sars,type="new.count",columns=!no4sU))
# Estimated counts for new RNA for all samples with 4sU

sars<-LFC(sars,contrasts=GetContrasts(sars,group = "duration.4sU"))
head(GetAnalysisTable(sars,columns="LFC"))
# Estimated fold changes SARS vs Mock for each time point