aCGH.process              package:aCGH              R Documentation

_P_r_o_c_e_s_s _d_a_t_a _i_n _a_C_G_H _o_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     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.

_U_s_a_g_e:

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

_A_r_g_u_m_e_n_t_s:

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

_V_a_l_u_e:

     Object of class 'aCGH'.

_A_u_t_h_o_r(_s):

     Jane Fridlyand, Peter Dimitrov

_S_e_e _A_l_s_o:

     'aCGH'

_E_x_a_m_p_l_e_s:

     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

