Gene Ontology Analysis：基因本体论分析.pdf

Lecture 21 Gene Ontology Analysis MCB 416A/516A Statistical Bioinformatics and Genomic Analysis Prof. Lingling An Univ of Arizona Last time: §? R code for cluster analysis ?? Why need do scaling? ?? Advanced heatmap 2 Outline §? Introduction to Gene Ontology §? Gene set enrichment 3 After detect significant genes in differential expression analysis… Data on n genes for m hybridizations results in a nxm gene-by-array data matrix Array1 Array2 Array3 Array4 Array5 … Gene1 0.46 0.30 0.80 1.51 0.90 ... Gene2 -0.10 0.49 0.24 0.06 0.46 ... Gene3 0.15 0.74 0.04 0.10 0.20 ... Gene4 -0.45 -1.03 -0.79 -0.56 -0.32 ... Gene5 -0.06 1.06 1.35 1.09 -1.09 ... … … … … … … ... Preprocessing-normalization-summarization-testing= List of differentially expressed genes 4 How to interprete the data? §? Driven by experimental questions, but with a long list of siginficant genes ?? which genes are of interest? ?? what’s special about the differentially expressed genes? §? Solution: pooling of genes into functional classes ?? provides a general overview §? Gene Ontology database provides such a functional classification 5 After clustering genes, then what? §? Assign (or hypothesize about) biological meanings to clu