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feature selection
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How can I fix and run "sigCVError" function ?
sigFeature
svm-rfe
sigCVError
feature selection
4.5 years ago
rekren
▴ 20
0
votes
2
replies
1.3k
views
feature reduction using machine learning
rnaseq
machine learning
feature selection
updated 6.1 years ago by
chris86
▴ 420 • written 6.1 years ago by
marak
• 0
0
votes
5
replies
3.0k
views
Choosing genes for clustering
limma
clustering
differential gene expression
hierarchical clustering
feature selection
7.3 years ago • updated 7.2 years ago
lirongrossmann
▴ 80
2
votes
5
replies
4.1k
views
How to use t.test to select best features out of multiple features?
microarray
biobase
feature selection
t.test
R
updated 9.3 years ago by
svlachavas
▴ 840 • written 9.3 years ago by
babumanish837
▴ 10
4 results • Page
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Answer: Build error on kunpeng2 Linux aarch64
by
James W. MacDonald
67k
This isn't the place for developer questions. Please use the developer listserv at bioc-devel@r-project.org instead. Also, you might wan…
Comment: biomaRt rnorvegicus_gene_ensembl not available anymore
by
James W. MacDonald
67k
You should use `useEnsembl` as the error recommends. ``` > library(biomaRt) > mart <- useEnsembl("ensembl", "rnorvegicus_gene_ensembl") > …
Comment: Deseq2 Design
by
James W. MacDonald
67k
The other thing I forgot to mention is that you need to specify a cell means model to `DESeq`. Here's an example. ``` > library(DESeq2) > …
Comment: biomaRt rnorvegicus_gene_ensembl not available anymore
by
Benjamin
▴ 20
I had access temporarily to the rat genome, but now it looks like ensemble 113 is completely down as I have this error: Error : Your q…
Comment: Deseq2 Design
by
pm_25
• 0
Thanks James for the prompt answer! your explanation makes more sense. in your example, when creating the interactions: ```r results(dds,…
Votes
DiffBind giving different results from dba.report() and dba.analyze(..., bRetrieveAnalysis=TRUE)
Answer: Deseq2 Design
Answer: Fold change calculation in Diffbind vs. DESEQ2?
Fold change calculation in Diffbind vs. DESEQ2?
FeatureCounts Output Counts at Exon Level Using Default Settings, want gene level
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