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ctc
•
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0
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908
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ctc::hc2Newick branch length errors?
ctc
ctc
11.1 years ago
Narayanan, Manikandan NIH/NIAID [E]
▴ 60
0
votes
2
replies
1.2k
views
Finding coding SNPs with predictCoding
SNP
Annotation
BSgenome
ctc
BSgenome
cycle
genomes
SNP
Annotation
BSgenome
ctc
BSgenome
updated 12.1 years ago by
Thomas Girke
★ 1.7k • written 12.1 years ago by
Valerie Obenchain
★ 6.8k
0
votes
5
replies
1.4k
views
Finding coding SNPs with predictCoding
SNP
ctc
SNP
ctc
updated 12.2 years ago by
Thomas Girke
★ 1.7k • written 12.2 years ago by
Valerie Obenchain
★ 6.8k
0
votes
1
reply
829
views
Query regarding Clustering
Clustering
ctc
Clustering
ctc
updated 14.0 years ago by
varpal singh
▴ 120 • written 14.0 years ago by
Sean Davis
21k
0
votes
0
replies
884
views
Queries on the 4x44PreProcess Package
Normalization
ctc
limma
Agi4x44PreProcess
Normalization
ctc
limma
Agi4x44PreProcess
15.2 years ago
Pedro López Romero
▴ 360
0
votes
0
replies
1.1k
views
Xcluster
Microarray
ctc
Microarray
ctc
18.8 years ago
Antoine Lucas
▴ 100
0
votes
0
replies
779
views
:Export 1 way cluster to treeview
Clustering
ctc
Clustering
ctc
19.4 years ago
Anthony Bosco
▴ 500
0
votes
0
replies
1.1k
views
problems with getBioC() and getBioC(develOK=TRUE) on R 2.0.0
aCGH
GO
Biobase
DynDoc
annotate
edd
genefilter
geneplotter
rhdf5
multtest
ctc
ROC
affy
19.6 years ago
rgentleman
★ 5.5k
0
votes
0
replies
1.1k
views
problems with getBioC() and getBioC(develOK=TRUE) on R 2.0.0
aCGH
GO
Biobase
DynDoc
annotate
edd
genefilter
geneplotter
rhdf5
multtest
ctc
ROC
affy
19.6 years ago
Goeman, J.J. MSTAT
▴ 150
0
votes
1
reply
1.1k
views
Errors w/ getBioC(develOK =TRUE) with R2.0 devel
aCGH
GO
Biobase
DynDoc
annotate
edd
genefilter
geneplotter
rhdf5
multtest
ctc
ROC
affy
19.7 years ago
Matthew Hannah
▴ 940
0
votes
0
replies
1.0k
views
Errors w/ getBioC()
aCGH
GO
Biobase
DynDoc
annotate
edd
genefilter
geneplotter
rhdf5
multtest
ctc
ROC
affy
19.7 years ago
Matthew Hannah
▴ 940
0
votes
0
replies
1.0k
views
Updated ctc package available
ctc
ctc
21.3 years ago
Jeff Gentry
★ 3.9k
12 results • Page
1 of 1
Recent ...
Replies
Comment: Too many significant genes when integrating gtex and tcga
by
ATpoint
★ 4.1k
These two datasets are from completely different experiments / batches. It is utterly meaningless to compare them. I would suggest comparat…
Answer: fgsea significant result
by
ATpoint
★ 4.1k
Set a fixed seed before running this. Note that a FDR of 0.25 in fgsea is wildly and overly lenient. See https://support.bioconductor.o…
Answer: How to use bootRanges to bootstrap small RNA loci (nullranges package)
by
Poonam
• 0
Hi Michael, I think there is something wrong with the generation of nullranges. I was working with small RNA and methylation overlaps. …
Answer: Once again a "Model matrix not full rank"
by
swbarnes2
★ 1.3k
Replicate numbers, like the 1 in control_1 are fine in sample names, but never add them to anything else in colData. From the computer's p…
Answer: limma Intercept vs No-intercept models completely changing DMR results?
by
Gordon Smyth
50k
I'll add a little bit of general advice to James' answer. You seem to have the misunderstanding that you can change the design matrix but …
Votes
Answer: Why does GSEA on edgeR results for randomized samples give highly significant p-
Answer: limma Intercept vs No-intercept models completely changing DMR results?
Answer: CombineArrays for EPIC and EPIC V2
Answer: Too many significant genes when integrating gtex and tcga
Comment: Too many significant genes when integrating gtex and tcga
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