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bowtie
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Multiple alignments (multi-mapped reads) and DESeq/edgeR pipeline
deseq
deseq2
edger
tophat
bowtie
8.9 years ago
ysdel
▴ 40
2
votes
4
replies
1.6k
views
Bowtie % mapped reads for DGE
Bowtie
quasr
rnaseq
updated 8.3 years ago by
Dario Strbenac
★ 1.5k • written 8.3 years ago by
tarek.mohamed
▴ 10
1
vote
4
replies
1.5k
views
Importing Bowtie result into R
r
bowtie
updated 8.9 years ago by
Sean Davis
21k • written 8.9 years ago by
a.afshinfard
▴ 10
0
votes
1
reply
822
views
Is possible to use NOISeq with counts from RSubread?
noiseq
rsubread
tophat
bowtie
bowtie2
4.9 years ago
Marcelo Laia
▴ 450
4 results • Page
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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 …
Answer: package goseq seems to be not available on the latest version of R
by
Gordon Smyth
50k
It is true that goseq isn't available for Bioc 3.19 (as at 4 May 2024). In the meantime, you could consider using the goana() and kegga() …
Answer: limma Intercept vs No-intercept models completely changing DMR results?
by
James W. MacDonald
65k
This part: ``` design_intercept <- model.matrix(~Alt+Sex+Age+PC1, data=targets_Sherpa) colnames(design_intercept) <- c("AltSHP_LA","Al…
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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