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An additional k-means clustering step improves the biological features of WGCNA gene co-expression networks.

Juan A BotíaJana VandrovcovaPaola ForaboscoSebastian GuelfiKarishma D'Sanull nullJohn HardyCathryn M LewisMina RytenMichael E Weale
Published in: BMC systems biology (2017)
The results obtained from our investigations indicate that our k-means method, applied as an adjunct to standard WGCNA, results in better network partitions. These improved partitions enable more fruitful downstream analyses, as gene modules are more biologically meaningful.
Keyphrases
  • copy number
  • genome wide
  • poor prognosis
  • genome wide identification
  • single cell
  • dna methylation
  • gene expression
  • rna seq
  • transcription factor