Bioinformatics Toolbox

manorm

Normalize microarray data

Syntax

XNorm = manorm(X) XNorm = manorm(MAStruct, FieldName) [XNorm, ColVal] = manorm(...) manorm(..., 'Method', MethodValue) manorm(..., 'Extra_Args', Extra_ArgsValue) manorm(..., 'LogData', LogDataValue) manorm(..., 'Prctile', PrctileValue) manorm(..., 'Global', GlobalValue), manorm(..., 'StructureOutput', StructureOutputValue) manorm(..., 'NewColumnName', NewColumnNameValue)

Description

XNorm = manorm(X) scales the values in each column of microarray data (X) by dividing by the mean column intensity.

X: Microarray data. Enter a vector or matrix.

XNorm = manorm(MAStruct, FieldName) scales the data for a field (FieldName) for each block or print-tip by dividing by the mean column intensity for each block. The output is a matrix with each column corresponding to the normalized data for each block.

MAStruct: Microarray structure.

[XNorm, ColVal] = manorm(...) returns the values used to normalize the data.

manorm(..., 'Method', MethodValue) allows you to choose the method for scaling or centering the data. MethodValue can be 'Mean' (default), 'Median', 'STD' (standard deviation), 'MAD' (median absolute deviation), or a function handle. If you pass a function handle, then the function should ignore NaNs and must return a single value per column of the input data.

manorm(..., 'Extra_Args', Extra_ArgsValue) allows you to pass extra arguments to the function MethodValue. Extra_ArgsValue must be a cell array.

manorm(..., 'LogData', LogDataValue), when LogDataValue is true, works with log ratio data in which case the mean (or MethodValue) of each column is subtracted from the values in the columns, instead of dividing the column by the normalizing value.

manorm(..., 'Prctile', PrctileValue) only uses the percentile (PrctileValue) of the data preventing large outliers from skewing the normalization. If PrctileValue is a vector containing two values, then the range from the PrctileValue(1) percentile to the PrctileValue(2) percentile is used. The default value is 100, that is to use all the data in the data set.

manorm(..., 'Global', GlobalValue), when GlobalValue is true, normalizes the values in the data set by the global mean (or MethodValue) of the data, as opposed to normalizing each column or block of the data independently.

manorm(..., 'StructureOutput', StructureOutputValue), when StructureOutputValue is true, the input data is a structure returns the input structure with an additional data field for the normalized data.

manorm(..., 'NewColumnName', NewColumnNameValue), when using StructureOutput, allows you to specify the name of the column that is appended to the list of ColumnNames in the structure. The default behavior is to prefix 'Block Normalized' to the FieldName string.

Examples

 maStruct = gprread('mouse_a1wt.gpr');
 % Extract some data of interest.
 Red = maStruct.Data(:,4);
 Green = maStruct.Data(:,13);
 % Create a log-log plot.
 maloglog(Red,Green,'factorlines',true)
 % Center the data.
 normRed = manorm(Red);
 normGreen = manorm(Green);
 % Create a log-log plot of the centered data.
 figure
 maloglog(normRed,normGreen,'title','Normalized','factorlines',true)
 
 % Alternatively, you can work directly with the structure
 normRedBs = manorm(maStruct,'F635 Median - B635');
 normGreenBs = manorm(maStruct,'F532 Median - B532');
 % Create a log-log plot of the centered data. This includes some
 % zero values so turn off the warning.
 figure
 w = warning('off','Bioinfo:MaloglogZeroValues');
 maloglog(normRedBs,normGreenBs,'title',...
 'Normalized Background-Subtracted Median Values',...
                'factorlines',true)
 warning(w);

manorm

Syntax

Description

Examples

See Also