aCGH.process: Process data in aCGH object

Description Usage Arguments Value Author(s) See Also Examples

View source: R/aCGH.read.R

Description

This function takes object of class aCGH, and filters clones based on their mapping information and proportion missing. It also average duplicated clones and reports quality statistic.

Usage

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aCGH.process(aCGH.obj, chrom.remove.threshold = 24,
                 prop.missing = 0.25, sample.quality.threshold = 0.4,
                 unmapScreen=TRUE, dupRemove = TRUE)

Arguments

aCGH.obj

Object of class aCGH

chrom.remove.threshold

Chromosomes are ordered and numbered as usual, except for X and Y chromosome, which in for Homo sapiens genome have numbers 23 and 24 repsectivelly, in for Mus musculus 20 and 21, etc.

prop.missing

Clones are screened out and if the proportion missing in the samples is prop.missing they are removed.

sample.quality.threshold

Mark those samples that have their proportion of missing values sample.quality.threshold.

unmapScreen

Indicator for whether clones with incomplete mapping information should be removed from the dataset. Note that leaving them in may cause plotting routines fail. Defaults to TRUE

dupRemove

Indicator for whether clones with duplicate names should be averaged and removed from the dataset leaving only one occurence of each duplicated set.Defaults to TRUE

Value

Object of class aCGH.

Author(s)

Jane Fridlyand, Peter Dimitrov

See Also

aCGH

Examples

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datadir <- system.file(package = "aCGH")
datadir <- paste(datadir, "/examples", sep="")

clones.info <-
      read.table(file = file.path(datadir, "clones.info.ex.txt"),
                 header = TRUE, sep = "\t", quote="", comment.char="")
log2.ratios <-
      read.table(file = file.path(datadir, "log2.ratios.ex.txt"),
                 header = TRUE, sep = "\t", quote="", comment.char="")
pheno.type <- read.table(file = file.path(datadir, "pheno.type.ex.txt"),header = TRUE, sep = "\t", quote="", comment.char="")
ex.acgh <- create.aCGH(log2.ratios, clones.info, pheno.type)
ex.acgh <-
    aCGH.process(ex.acgh, chrom.remove.threshold = 23, prop.missing = .25, 
sample.quality.threshold = .4, unmapScreen=TRUE, dupRemove = FALSE)
ex.acgh

aCGH documentation built on Nov. 8, 2020, 6:58 p.m.