Weighted Sample Gene Network Analysis (WSCNA)

syn26532573

Created By Mette Peters Mette

url: https://www.synapse.org/#!Synapse:syn25944427
grant: U01AG046170 RF1AG054014 RF1AG057440 R01AG057907 U01AG052411 R01AG068030
program: AMP-AD
summary: WSCNA identifies sample clusters by analyzing gene expression correlations between sample pairs to build a correlation network which is used to calculate a TOM score that groups similar samples together via k-means clustering. WSCNA extends the WINA algorithm to samples by transposing the input matrix so that sample-sample correlations are compared. See https://doi.org/10.1126/sciadv.abb5398 for more information about WSCNA and https://doi.org/10.1186/s13073-016-0355-3 for information about WINA
contributor: Ryan Neff, Minghui Wang, Bin Zhang
displayName: Weighted Sample Gene Network Analysis (WSCNA)
softwareType: Algorithm

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