Quantcast

Documentation Center

  • Trial Software
  • Product Updates

cghfreqplot

Display frequency of DNA copy number alterations across multiple samples

Syntax

FreqStruct = cghfreqplot(CGHData)

FreqStruct = cghfreqplot(CGHData, ...'Threshold', ThresholdValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'Group', GroupValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'Subgrp', SubgrpValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'Subplot', SubplotValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'Cutoff', CutoffValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'Chromosome', ChromosomeValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'IncludeX', IncludeXValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'IncludeY', IncludeYValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'Chrominfo', ChrominfoValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'ShowCentr', ShowCentrValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'Color', ColorValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'YLim', YLimValue, ...)
FreqStruct = cghfreqplot(CGHData, ...'Titles', TitlesValue, ...)

Input Arguments

CGHData

Array-based comparative genomic hybridization (aCGH) data in either of the following forms:

  • Structure with the following fields:

    • Sample — Cell array of strings containing the sample names (optional).

    • Chromosome — Vector containing the chromosome numbers on which the clones are located.

    • GenomicPosition — Vector containing the genomic positions (in bp, kb, or mb units) to which the clones are mapped.

    • Log2Ratio — Matrix containing log2 ratio of test to reference signal intensity for each clone. Each row corresponds to a clone, and each column corresponds to a sample.

  • Matrix in which each row corresponds to a clone. The first column contains the chromosome number, the second column contains the genomic position, and the remaining columns each contain the log2 ratio of test to reference signal intensity for a sample.

ThresholdValue

Positive scalar or vector that specifies the gain/loss threshold. A clone is considered to be a gain if its log2 ratio is above ThresholdValue, and a loss if its log2 ratio is below negative ThresholdValue.

The ThresholdValue is applied as follows:

  • If a positive scalar, it is the gain and loss threshold for all the samples.

  • If a two-element vector, the first element is the gain threshold for all samples, and the second element is the loss threshold for all samples.

  • If a vector of the same length as the number of samples, each element in the vector is considered as a unique gain and loss threshold for each sample.

Default is 0.25.

GroupValue

Specifies the sample groups to calculate the frequency from. Choices are:

  • A vector of sample column indices (for data with only one group). The samples specified in the vector are considered a group.

  • A cell array of vectors of sample column indices (for data divided into multiple groups). Each element in the cell array is considered a group.

Default is a single group of all the samples in CGHData.

SubgrpValueControls the analysis of samples by subgroups. Choices are true (default) or false.
SubplotValueControls the display of all plots in one Figure window when more than one subgroup is analyzed. Choices are true (default) or false (displays plots in separate windows).
CutoffValueScalar or two-element numeric vector that specifies a cutoff, which controls the plotting of only the clones with frequency gains or losses greater than or equal to CutoffValue. If a two-element vector, the first element is the cutoff for gains, and the second element is for losses. Default is 0.
ChromosomeValueSingle chromosome number or a vector of chromosome numbers that specify the chromosomes for which to display frequency plots. Default is all chromosomes in CGHData.
IncludeXValueControls the inclusion of the X chromosome in the analysis. Choices are true (default) or false.
IncludeYValueControls the inclusion of the Y chromosome in the analysis. Choices are true or false (default) .
ChrominfoValue

Cytogenetic banding information specified by either of the following:

  • Structure returned by the cytobandread function

  • String specifying the file name of an NCBI ideogram text file or a UCSC Genome Browser cytoband text file

Default is Homo sapiens cytogenetic banding information from the UCSC Genome Browser, NCBI Build 36.1 (http://genome.UCSC.edu).

ShowCentrValue

Controls the display of the centromere positions as vertical dashed lines in the frequency plot. Choices are true (default) or false.

    Tip   The centromere positions are obtained from ChrominfoValue.

ColorValue

Color scheme for the vertical lines in the plot, indicating the frequency of the gains and losses, specified by either of the following:

  • Name of or handle to a function that returns a colormap

  • M-by-3 matrix containing RGB values. If M equals 1, then that single color is used for all gains and losses. If M equals 2 or more, then the first row is used for gains, the second row is used for losses, and remaining rows are ignored. For example, [0 1 0;1 0 0] specifies green for gain and red for loss.

The default color scheme is a range of colors from pure green (gain = 1) through yellow (0) to pure red (loss = –1).

YLimValueTwo-element vector specifying the minimum and maximum values on the vertical axis. Default is [1, -1].
TitlesValueSingle string or a cell array of strings that specifies titles for the group(s), which are added to the tops of the plot(s).

Output Arguments

FreqStructStructure containing frequency data in the following fields:
  • Group — Structure array, with each structure representing a group of samples. Each structure contains the following fields:

    • Sample — Cell array containing names of samples within the group.

    • GainFrequency — Column vector containing the average gain for each clone for a group of samples.

    • LossFrequency — Column vector containing the average loss for each clone for a group of samples.

  • Chromosome — Column vector containing the chromosome numbers on which the clones are located.

  • GenomicPosition — Column vector containing the genomic positions of the clones.

    Tip   You can use this output structure as input to the cghfreqplot function.

Description

FreqStruct = cghfreqplot(CGHData) displays the frequency of copy number gain or loss across multiple samples for each clone on an array against their genomic position along the chromosomes.

FreqStruct = cghfreqplot(CGHData, ...'PropertyName', PropertyValue, ...) calls cghfreqplot with optional properties that use property name/property value pairs. You can specify one or more properties in any order. Each PropertyName must be enclosed in single quotation marks and is case insensitive. These property name/property value pairs are as follows:


FreqStruct = cghfreqplot(CGHData, ...'Threshold', ThresholdValue, ...)
specifies the gain/loss threshold. A clone is considered to be a gain if its log2 ratio is above ThresholdValue, and a loss if its log2 ratio is below negative ThresholdValue.

The ThresholdValue is applied as follows:

  • If a positive scalar, it is the gain and loss threshold for all the samples.

  • If a two-element vector, the first element is the gain threshold for all samples, and the second element is the loss threshold for all samples.

  • If a vector of the same length as the number of samples, each element in the vector is considered as a unique gain and loss threshold for each sample.

Default is 0.25.

FreqStruct = cghfreqplot(CGHData, ...'Group', GroupValue, ...) specifies the sample groups to calculate the frequency from. Choices are:

  • A vector of sample column indices (for data with only one group). The samples specified in the vector are considered a group.

  • A cell array of vectors of sample column indices (for data divided into multiple groups). Each element in the cell array is considered a group.

Default is a single group of all the samples in CGHData.

FreqStruct = cghfreqplot(CGHData, ...'Subgrp', SubgrpValue, ...) controls the analysis of samples by subgroups. Choices are true (default) or false.

FreqStruct = cghfreqplot(CGHData, ...'Subplot', SubplotValue, ...) controls the display of all plots in one Figure window when more than one subgroup is analyzed. Choices are true (default) or false (displays plots in separate windows).

FreqStruct = cghfreqplot(CGHData, ...'Cutoff', CutoffValue, ...) specifies a cutoff value, which controls the plotting of only the clones with frequency gains or losses greater than or equal to CutoffValue. CutoffValue is a scalar or two-element numeric vector. If a two-element numeric vector, the first element is the cutoff for gains, and the second element is for losses. Default is 0.

FreqStruct = cghfreqplot(CGHData, ...'Chromosome', ChromosomeValue, ...) displays the frequency plots only of chromosome(s) specified by ChromosomeValue, which can be a single chromosome number or a vector of chromosome numbers. Default is all chromosomes in CGHData.

FreqStruct = cghfreqplot(CGHData, ...'IncludeX', IncludeXValue, ...) controls the inclusion of the X chromosome in the analysis. Choices are true (default) or false.

FreqStruct = cghfreqplot(CGHData, ...'IncludeY', IncludeYValue, ...) controls the inclusion of the Y chromosome in the analysis. Choices are true or false (default).

FreqStruct = cghfreqplot(CGHData, ...'Chrominfo', ChrominfoValue, ...) specifies the cytogenetic banding information for the chromosomes. ChrominfoValue can be either of the following

  • Structure returned by the cytobandread function

  • String specifying the file name of an NCBI ideogram text file or a UCSC Genome Browser cytoband text file

Default is Homo sapiens cytogenetic banding information from the UCSC Genome Browser, NCBI Build 36.1 (http://genome.UCSC.edu).

FreqStruct = cghfreqplot(CGHData, ...'ShowCentr', ShowCentrValue, ...) controls the display of the centromere positions as vertical dashed lines in the frequency plot. Choices are true (default) or false.

    Tip   The centromere positions are obtained from ChrominfoValue.

FreqStruct = cghfreqplot(CGHData, ...'Color', ColorValue, ...) specifies a color scheme for the vertical lines in the plot, indicating the frequency of the gains and losses. Choices are:

  • Name of or handle to a function that returns a colormap.

  • M-by-3 matrix containing RGB values. If M equals 1, then that single color is used for all gains and losses. If M equals 2 or more, then the first row is used for gains, the second row is used for losses, and remaining rows are ignored. For example, [0 1 0;1 0 0] specifies green for gain and red for loss.

The default color scheme is a range of colors from pure green (gain = 1) through yellow (0) to pure red (loss = –1).

FreqStruct = cghfreqplot(CGHData, ...'YLim', YLimValue, ...) specifies the y vertical limits for the frequency plot. YLimValue is a two-element vector specifying the minimum and maximum values on the vertical axis. Default is [1, -1].

FreqStruct = cghfreqplot(CGHData, ...'Titles', TitlesValue, ...) specifies titles for the group(s), which are added to the tops of the plot(s). TitlesValue can be a single string or a cell array of strings.

Examples

Plotting Data from the Coriell Cell Line Study

  1. Load a MAT-file, included with the Bioinformatics Toolbox™ software, which contains coriell_data, a structure of array-based CGH data.

    load coriell_baccgh
  2. Display a frequency plot of the copy number alterations across all samples in the Coriell aCGH data.

    Struct = cghfreqplot(coriell_data);

  3. View data tips for the data, chromosomes, and centromeres by clicking the Data Cursor button on the toolbar, then clicking data, a blue chromosome boundary line, or a dotted centromere line in the plot. To delete this data tip, right-click it, then select Delete Current Datatip.

  4. Display a color bar indicating the degree of gain or loss by clicking the Insert Colorbar button on the toolbar.

The coriell_baccgh.mat file used in this example contains data from Snijders et al., 2001.

Plotting Pancreatic Cancer Study Data Using a Green and Red Color Scheme

  1. Load a MAT-file, included with the Bioinformatics Toolbox software, which contains pancrea_data, a structure of array-based CGH data from a pancreatic cancer study.

    load pancrea_oligocgh
  2. Display a frequency plot of the copy number alterations across all samples in the pancreatic cancer data, using a green and red color scheme.

    cghfreqplot(pancrea_data, 'Color', [0 1 0; 1 0 0])

The pancrea_oligocgh.mat file used in this example contains data from Aguirre et al., 2004.

Plotting Groups of aCGH Data, Specifying a Frequency Value Cutoff, and Adding a Chromosome Ideogram

  1. Load a MAT-file, included with the Bioinformatics Toolbox software, which contains pancrea_data, a structure of array-based CGH data from a pancreatic cancer study.

    load pancrea_oligocgh
  2. Define two groups of data.

    grp1 = strncmp('PA.C', pancrea_data.Sample,4);
    grp1_ind = find(grp1);
    grp2 = strncmp('PA.T', pancrea_data.Sample,4);
    grp2_ind = find(grp2);
  3. Display a frequency plot of the copy number alterations across all samples in the two groups and limit the plotting to only the clones with frequency gains or losses greater than or equal to 0.25.

    SP = cghfreqplot(pancrea_data, 'Group', {grp1_ind, grp2_ind},...
                     'Title', {'CL', 'PT'}, 'Cutoff', 0.25);

  4. Display a frequency plot of the copy number alterations across all samples in the first group and limit the plot to chromosome 4 only.

    SP = cghfreqplot(pancrea_data, 'Group', grp1_ind, ...
                     'Title', 'CL Group on Chr 4', 'Chromosome', 4);

  5. Use the chromosomeplot function with the 'addtoplot' property to add the ideogram of chromosome 4 for Homo sapiens to this frequency plot. Because the plot of the frequency data from the pancreatic cancer study is in kb units, use the 'Unit' property to convert the ideogram data to kb units.

    chromosomeplot('hs_cytoBand.txt', 4, 'addtoplot', gca, 'unit', 2);

The pancrea_oligocgh.mat file used in this example contains data from Aguirre et al., 2004.

References

[1] Snijders, A.M., Nowak, N., Segraves, R., Blackwood, S., Brown, N., Conroy, J., Hamilton, G., Hindle, A.K., Huey, B., Kimura, K., Law, S., Myambo, K., Palmer, J., Ylstra, B., Yue, J.P., Gray, J.W., Jain, A.N., Pinkel, D., and Albertson, D.G. (2001). Assembly of microarrays for genome-wide measurement of DNA copy number. Nature Genetics 29, 263–264.

[2] Aguirre, A.J., Brennan, C., Bailey, G., Sinha, R., Feng, B., Leo, C., Zhang, Y., Zhang, J., Gans, J.D., Bardeesy, N., Cauwels, C., Cordon-Cardo, C., Redston, M.S., DePinho, R.A., and Chin, L. (2004). High-resolution characterization of the pancreatic adenocarcinoma genome. PNAS 101, 24, 9067–9072.

See Also

| |

Was this topic helpful?