Systematic data preprocess procedures and factor extraction of multiple phenotypes for one-color microarray
Date Issued
2004
Date
2004
Author(s)
Lin, Wen-Ting
DOI
en-US
Abstract
Microarrays are widely used to monitor gene expressions to yield information for genomes. Though there are many methods and mechanisms proposed to extract information from microarray data, the preprocess of raw expression data determine the accuracy and reliability of the extracted information. The first objective of this research is to implement a systematic procedure to preprocess the raw intensity reading. The proposed data preprocess procedure has 3 steps: rectification of intensity reading, signal normalization and bad spots screening. The rectification of intensity uses coefficient of variation (CV) to assess the consistencies of mean intensity and median intensity from raw intensity readings to decide which one to employ and then test the correlations between foreground intensity and background intensity to correct background intensity effects. Signal normalization transforms the rectified data to remove the chip-to-chip brightness variation and contrast variation by logarithm transformation, median subtraction and deviation division. After signal normalization, the hypothesis T-test is used to screen out bad expressions in replicated spots.
More recently, microarrays have been conducted not only to relate genes with one phenotype, but also inquire relations between gene expression levels and multiple phenotypes. The second objective of this research is to apply Factor Analysis (FA) to extraction of the underlying co-regulating and independent factors of the multiple phenotypes. And then the treated factors can be taken as an individual phenotype for testing differentially expressed genes. Both of the objectives are to prepare experimental readings for accurate, effective biological information mining procedure. Finally, a real case of microarray experiment investigating gene expressions in 24 human blood samples with 19 phenotypes is provided to demonstrate and test the proposed preprocessing procedures.
Subjects
微晶片
預處理
因子萃取
preprocess
microarray data analysis
normalization
multiple phenotypes
Type
thesis
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