Cluster analysis and pathway-based characterization of differentially expressed genes and proteins from integrated proteomics. Cluster analysis and pathway-based.

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Cluster analysis and pathway-based characterization of differentially expressed genes and proteins from integrated proteomics. Cluster analysis and pathway-based characterization of differentially expressed genes and proteins from integrated proteomics.A, Venn diagrams of the number of total mRNAs/proteins identified by 2D-DIGE, iTRAQ, and DNA array. B, Venn diagrams of the number of up/down-regulated proteins identified by iTRAQ. In total, 3239 proteins were identified with a confidence limit of 95% by MALDI and ESI. The fold change of each protein expression ratio (NF1 siRNA/control siRNA) was calculated by average iTRAQ ratio in MALDI and ESI analyses at each time point. Proteins quantified with a fold change more than 20% (average iTRAQ ratio >1.20 or <0.83) were identified as differentially expressed proteins. For cluster analysis, continuously up/down-regulated proteins were selected by Venn diagrams (yellow area, 62 up-regulated proteins; 35 down-regulated proteins). C, Hierarchical clustering of the 97 continuously up/down-regulated proteins. Each vertical column represents a sample map, whereas each horizontal row represents an individual protein, with relative expression values displayed as an expression matrix (heat map) using a standardized log abundance scale ranging from −0.5 (blue) to +0.5 (red). Blue and red colors indicate decreased and increased expression, respectively: the brighter the color, the stronger the change. Mio Hirayama et al. Mol Cell Proteomics 2013;12:1377-1394 © 2013 by The American Society for Biochemistry and Molecular Biology, Inc.