import.GISTIC

Transform GISTIC scores for CNAs in a TRONCO compliant object. Input can be either a matrix, with columns for each altered gene and rows for each sample; in this case colnames/rownames mut be provided. If input is a character an attempt to load a table from file is performed. In this case the input table format should be constitent with TCGA data for focal CNA; there should hence be: one column for each sample, one row for each gene, a column Hugo_Symbol with every gene name and a column Entrez_Gene_Id with every gene\'s Entrez ID. A valid GISTIC score should be any value of: "Homozygous Loss" (-2), "Heterozygous Loss" (-1), "Low-level Gain" (+1), "High-level Gain" (+2). For details and examples regarding the loading functions provided by the package we refer to the Vignette Section 3.

import.GISTIC(
  x,
  filter.genes = NULL,
  filter.samples = NULL,
  silent = FALSE,
  trim = TRUE,
  rna.seq.data = NULL,
  rna.seq.up = NULL,
  rna.seq.down = NULL
)

Arguments

x

Either a dataframe or a filename

filter.genes

A list of genes

filter.samples

A list of samples

silent

A parameter to disable/enable verbose messages.

trim

Remove the events without occurrence

rna.seq.data

Either a dataframe or a filename

rna.seq.up

TODO

rna.seq.down

TODO

Value

A TRONCO compliant representation of the input CNAs.

Examples

data(crc_gistic)
gistic = import.GISTIC(crc_gistic)
#> *** Using full GISTIC: #dim  9  x  6 
#> *** GISTIC input format conversion started.
#> Converting input data to character for import speedup.
#> Creating  24 events for 6 genes 
#> Extracting "Homozygous Loss" events (GISTIC = -2) 
#> Extracting "Heterozygous Loss" events (GISTIC = -1) 
#> Extracting "Low-level Gain" events (GISTIC = +1) 
#> Extracting "High-level Gain" events (GISTIC = +2) 
#> Transforming events in TRONCO data types ..... 
#> *** Binding events for 4 datasets.
#> *** Data extracted, returning only events observed in at least one sample 
#>  Number of events: n = 7 
#>  Number of genes: |G| = 6 
#>  Number of samples: m = 9