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lfc
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6
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4
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2.7k
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Identification of DEGs through limma analysis
limma
microarray
DEGs
p values
lfc
6.9 years ago
rkp
• 0
0
votes
7
replies
1.5k
views
LRT test followed by filtering based on LFC
deseq2
LFC
LRT
written 5.2 years ago by
sally.badawi
• 0
4
votes
14
replies
17k
views
standard error value (lfcSE) returned by DeSeq2
deseq2
deseq
lfc
lfcse
standard error
updated 7.1 years ago by
rraadd_8
• 0 • written 7.2 years ago by
tootiki
• 0
17
votes
7
replies
13k
views
DESeq2 lfcShrink() usage of coef vs. usage of contrast
deseq2
lfc
coef
contrast
updated 6.8 years ago by
Michael Love
41k • written 6.8 years ago by
Anke Busch
▴ 10
1
vote
1
reply
783
views
Gene wise dispersion estimate Process - From the prior to the posterior
GLM
prior
DESeq
LFC
updated 22 months ago by
Michael Love
41k • written 23 months ago by
stew
• 0
0
votes
6
replies
1.5k
views
large range of LFC in DESeq2
deseq2
lfc
betaprior
updated 18 months ago by
Michael Love
41k • written 5.4 years ago by
Mariaxi
• 0
0
votes
1
reply
1.1k
views
Filtering DESeq2 results for | LFC | > 1 genes
RNAseq
LFC
DEseq
2.9 years ago
ayy2110
• 0
2
votes
1
reply
2.2k
views
Using Limma to identify any differences between multiple treatment groups (without making pairwise comparisons)
microarray
limma
multiple treatments
lfc
updated 8.0 years ago by
Aaron Lun
★ 28k • written 8.0 years ago by
brionyk9
• 0
8 results • Page
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Comment: SGSeq: moving toward diffex from SGSeq analysis
by
Sara
• 0
Thank you for your response. I have another question about saving the sgvc result as a CSV file. I would appreciate your help, please. ``` …
Comment: How to use bootRanges to bootstrap small RNA loci (nullranges package)
by
Poonam
• 0
I tried different block lengths first and considered 100000 to be ideal because of the almost similar inter-range distance. S1= bootRange…
Comment: How to use bootRanges to bootstrap small RNA loci (nullranges package)
by
Michael Love
41k
The segmentation and block length are key parameters. We recommend for example blocks of length ~500kb. It would help if you would post yo…
Answer: Handling multiple differential expression comparisons
by
Michael Love
41k
It's typical that results are presented with each group having its own FDR control. So presenting each comparison with the adjusted p-va…
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…
Votes
Print Differentially Expressed Exons From Dexseq Results
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
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