geneRegionScan        package:GeneRegionScan        R Documentation

_G_e_n_e _R_e_g_i_o_n _S_c_a_n

_D_e_s_c_r_i_p_t_i_o_n:

     The top-level wrapper function that outputs as much data as
     possible, concerning one or a few genes. Refer to the functions
     plotCoexpression and plotOnGene for further explanation of each
     part of the plot.

_U_s_a_g_e:

         geneRegionScan(object, gene, genomicData=NULL, probeData=NULL, label=NULL, genename=NULL, summaryType="median", yMax=NULL, testType=NULL,forcePValue=FALSE,verbose=TRUE,cutoff=0.2, directions="all",correlationCutoff=0.3, probeLevelInfo=c("probeid"))
         

_A_r_g_u_m_e_n_t_s:

  object: A ProbeLevelSet object or a regular ExpressionSet object (in
          which case a probeData argument is required). See
          getLocalProbeIntensities and related functions on how to
          create a ProbeLevelSet.

    gene: A number of gene sequences as DNAString, list of DNAString
          objects, character-vectors or readFASTA outputs.

genomicData: Optional. If only one gene is specified this can be of the
          same form as given in exonStructure. If more than one gene is
          given, it must be a list, containing of one of these forms of
          the argument for each of the genes, in the same order.

probeData: Optional if a ProbeLevelSet is submitted as object argument.
          Otherwise, it must be a data frame with rownames
          corresponding to the featureNames of the ExpressionSet and a
          column named "sequence" with the probe sequences as character
          strings

   label: An optional character string specifying a column name in the
          pData of the object. If this argument is given, the gene plot
          will be colour coded based on the different groups (factors)
          in the pData entry. If a summaryType other than 'dots' is
          selected the summarisation is done stratified by the
          different groups in the pData.

genename: Optional character string specifying a gene name to include
          in the plot. If not included and a FASTA sequence is given,
          it will default to the name in the FASTA sequence. Otherwise
          it will default to 'Unknown genename'.

summaryType: Character string specifying one of the following summary
          methods: 'median', 'mean', 'quartiles' or 'dots' (i.e. no
          summary). Specifies how all the sample values or all the
          samples values in a group if 'label' is given, should be
          summarised. Defaults to 'median'.

    yMax: Optional integer. If given, this value will be the maximal
          value on the y-axis. This is useful if a few outlier probes
          have very high intensity values, as the default is to set the
          yMax to the maximal intensity value.

testType: Optional character string, defining a statistic procedure to
          identify especially interesting probes. Can be either 'linear
          model', 'students' or 'wilcoxons'. If given, a label must
          also be specified. In this case the plotStatistics function
          will be called and probes that are significantly changed
          between the groups in label at the P-value set in cutoff (see
          cutoff argument) will be circled.

forcePValue: Logical. Is used if the testType argument is used. If TRUE
          all significantly changed probes have P-value given on the
          plot. If FALSE, only plots with less than 10 significant
          probes write P-values. Plots can become very cluttered with
          data if set to TRUE

 verbose: TRUE or FALSE

  cutoff: Integer specifying at what p-value probes should be circled
          when using the 'testType' variable. Defaults to 0.2. For
          cutoffs higher than 0.05, all probes with P >0.05 will be
          circled in grey instead of black.

directions: A character vector of the matching-directions that should
          be scanned (which combinations of complementary and reverse).
          Defaults to "all" which is shorthand for all possible
          directions, but can take anything from:
          c("matchForwardSense", "matchForwardAntisense",
          "matchReverseSense", "matchReverseAntisense")

correlationCutoff: A number between 0 and 1. The limit at which Pearson
          correlation (in absolute values) should not be plotted below.
          Defaults to 0.5

probeLevelInfo: The information about each probe to include in the
          plot. Should be a vector of one or more of the following
          elements: probeid, probesetid, sequence. Default is only
          probeid.

_D_e_t_a_i_l_s:

     This function is a wrapper around plotOnGene and plotCoexpression.
     The output of plotOnGene is  included in the top half of the plot
     and the output of plotCoexpression will be included in the bottom
     half of the plot. Refer to each of these functions for more
     detailed help. 

     In general, this function gives an overview of how intensity
     values of individual probes on a microarray are in relation to an
     actual gene or set of genes in a region of the genome. 

     The function has only been tested with up to four genes at the
     same time. A plot with more genes would probably also be  too
     complicated to interpret with this method. In addition, the
     alignment of the top and bottom plots also becomes somewhat
     difficult with more genes. This alignment is also the reason why
     the function can not export to any device.

     See getLocalProbeIntensities for more info on how to obtain
     ProbeLevelSets.

_V_a_l_u_e:

     No value, but plots the local expression levels of each probe
     found in the submitted sequence of the gene or  genes as a
     function of its location along this sequence on the top half of a
     pdf-file. On the bottom half of the pdf-file  it will plot the
     pairwise correlations between all probes found in the sequences.
     The pdf file will be named "report_" + title of ExpressionSet or
     ProbeLevelSet

_A_u_t_h_o_r(_s):

     Lasse Folkersen

_S_e_e _A_l_s_o:

     'plotCoexpression', 'plotOnGene', 'getLocalProbeIntensities'

_E_x_a_m_p_l_e_s:

             data(exampleProbeLevelSet)
             
             #simple:
             geneRegionScan(exampleProbeLevelSet,mrna)
             
             #more complicated - note that we slice the mrna to simulate comparing two different isoforms
             gene1<-DNAString(mrna[[1]]$seq)[1:1000]
             gene2<-DNAString(mrna[[1]]$seq)[1500:3000]
             
             geneRegionScan(exampleProbeLevelSet, list(gene1,gene2), genomicData=list(genomic,genomic), label="genotype3", summaryType="mean",
         testType="linear model", forcePValue=TRUE, cutoff=0.1, directions="all", correlationCutoff=0.6,
         probeLevelInfo=c("probeid","sequence"))

