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hub genes
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WGCNA with distance matrix only from newick data.
WGCNA
eigengene
hub genes
7.9 years ago
yifangt
▴ 20
3
votes
2
replies
3.0k
views
Finding nearest neighbors of given hub gene in a co-expression network module
wgcna
rbgl
graph
coexpression
hub genes
updated 9.5 years ago by
Peter Langfelder
★ 3.0k • written 9.5 years ago by
Alan Smith
▴ 150
0
votes
1
reply
2.9k
views
question on visANT after WGCNA
wgcna
visant
module
hub genes
updated 9.5 years ago by
etycksen
• 0 • written 9.6 years ago by
agattorosso
• 0
14
votes
4
replies
17k
views
WGCNA Hub Gene Selection Method
WGCNA
Hub Genes
KmE
Intramodular Connectivity
updated 10.2 years ago by
Peter Langfelder
★ 3.0k • written 10.2 years ago by
brohawndg
▴ 150
4 results • Page
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Comment: Check removeBatchEffect effectiveness
by
massimo
• 0
I would kindly ask for additional support. When not including the design_timepoint argument in removeBatchEffect and thus keeping the inter…
Comment: Error Loading Experiment from SimBenchData Package
by
ksankaran
• 0
Aha, that was it! The object was class Seurat, but I didn't have it installed. After installing, everything works as expected.
Comment: Streamlining the computing time for MiloDE p-value correction in large dataset?
by
ATpoint
★ 5.0k
Is a method that is so computationally expensive really beneficial and necessary? You seem to have biological replication, don't you, so ps…
Answer: NA values for DESeq2 p-values and adjusted p-values using large sample sizes
by
ATpoint
★ 5.0k
Outliers without replacement, independent filtering or all-zero counts for that gene. That's the three options that trigger NAs https://bio…
Comment: R course in Boston December 19-20
by
eja.gaasa2e.r.m
• 0
The upcoming XLSolutions R course in Boston on December 19 20 is a great opportunity to enhance your data skills. Whether you re a beginner…
Votes
Comment: Check removeBatchEffect effectiveness
Gene expression associated with continuous (quantitative) traits (Limma/edgeR/correlation)
Comment: Error Loading Experiment from SimBenchData Package
Comment: incomplete imputation of missing values with LEA impute() function
Answer: Expected memory usage for analyzing large single-cell seq datasets (> 450,000 ce
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