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Fig. 8 | BMC Genomics

Fig. 8

From: Protein complex-based analysis is resistant to the obfuscating consequences of batch effects --- a case study in clinical proteomics

Fig. 8

Expression or network score-based (y-axis) side-by-side boxplots stratified by class and batch for top three variables: Rank-based network algorithms, SNET and FSNET, can capture the class effects while robust against batch effects. Both class and batch variability is present in the top variables selected by SP and HE (Abbreviations: Single Protein t-test, SP; Hypergeometric Enrichment, HE; SubNETs, SNET; Fuzzy SubNETs; FSNET)

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BMC Genomics

ISSN: 1471-2164

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