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gene set testing
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637
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Interpretation of mroast p-value results for gene set testing of specific molecular signatures using microarray data
mroast
camera
gene set testing
3.6 years ago
svlachavas
▴ 830
4
votes
11
replies
2.0k
views
Dealing with duplicated genes in camera gene set testing
limma
camera
gene set testing
ensembl
updated 4.4 years ago by
Robert Castelo
★ 3.3k • written 4.4 years ago by
Jeremy Beales
▴ 10
2
votes
3
replies
1.4k
views
Perform limma based gene-set testing for a two-group comparison in a microarray dataset regarding specific biological processes
limma
agilent microarrays
mroast
fry gene tests
gene set testing
updated 5.6 years ago by
Gordon Smyth
50k • written 5.6 years ago by
svlachavas
▴ 830
7
votes
2
replies
1.4k
views
Pre-ranked camera gene set testing with edgeR results
limma
camera
cameraPR
edgeR
gene set testing
updated 5.7 years ago by
Gordon Smyth
50k • written 5.7 years ago by
jamie.gearing
▴ 60
1
vote
4
replies
1.3k
views
Do the gene set statistics of the ROAST paper correspond to those implemented in the .roastEffects R function?
limma
roast
statistics
source code
gene set testing
5.8 years ago • updated 5.7 years ago
Andrea Carenzo
• 0
0
votes
1
reply
1.3k
views
GAGE function and the same.dir option
gage
gene set testing
updated 6.0 years ago by
Luo Weijun
★ 1.6k • written 6.0 years ago by
Aurora
▴ 20
2
votes
4
replies
1.7k
views
EGSEA usage with microarray data (with vooma)?
EGSEA
gene set testing
vooma
limma voom
gsea
updated 13 days ago by
Chris
▴ 10 • written 7.4 years ago by
Pekka Kohonen
▴ 190
4
votes
6
replies
2.0k
views
Gene set Testing with Limma for Agilent IDs probes?
limma
agilent microarrays
gene set testing
annotation
7.3 years ago
Bouzid.a
▴ 20
7
votes
13
replies
2.3k
views
Test whether expression levels of two gene sets are significantly different
R
DESeq2
gene set testing
gene expression
7.5 years ago
Jon Bråte
▴ 250
3
votes
4
replies
1.6k
views
Competitive gene set testing between two sets of genes
gene set testing
camera
edger
updated 7.9 years ago by
Gordon Smyth
50k • written 7.9 years ago by
le2336
▴ 20
1
vote
0
replies
1.3k
views
Gene Set Testing or GSEA for functional annotation of co-expressed ncRNA and coding genes
gsea
ncrna
coexpression
gene set analysis
gene set testing
8.1 years ago
m.fletcher
▴ 20
1
vote
5
replies
2.1k
views
Confused by results from CAMERA gene set testing
limma
camera
gene set testing
8.1 years ago
claire.n.levy
▴ 10
7
votes
6
replies
3.2k
views
Interpretation of mroast gene set analysis in R and appropriate use of the function barcode plot regarding a microarray dataset
limma
mroast
barcodeplot
KEGG
gene set testing
updated 8.5 years ago by
Gordon Smyth
50k • written 8.5 years ago by
svlachavas
▴ 830
6
votes
10
replies
1.8k
views
Possible implementation of roast/mroast for testing common DE patterns across two different experiments
gene set testing
roast
mroast
differential gene expression
bioconductor
9.0 years ago
svlachavas
▴ 830
14 results • Page
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Comment: Slightly different count plots from R and spreadsheet
by
Michael Love
42k
Change timepoint to an integer in the data frame: ``` as.numeric(as.character( <factor> )) ``` Then it should make points instead of boxe…
Answer: WGNCA kME vs. kIM
by
Vitor
• 0
You can compare kIM and kME within module assignments. The plot below is for my network (I used Pearson correlation and signed network). …
Comment: ChAMP installation issue
by
James W. MacDonald
66k
If you have beta values, try the `DSS` package. An alternative is to compute the logit transform (to M-values), which are amenable to analy…
Answer: pathview error
by
James W. MacDonald
66k
The obvious would be to check that you have genes that map to that pathway. It's unusual to have so many NA values for your NCBI gene IDs, …
Comment: ChAMP installation issue
by
Tahirah
• 0
Thanks a lot. But unfortunately it didn't work. I guess I will have to wait until ChAMP becomes available for version 3.19 In the meantime …
Votes
Including squared covariates to account for non-linear dependencies in differential gene expression analysis
DESeq2 DE gene expression of scRNA-seq pseudobulk
Answer: Multiple factor DSEq2 result generates weird volcano plot
DESeq2 for single cell pseudobulk processing
Simultaneously adding two different covariates in the model gives error in DESeq2.
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