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TimeCourse
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6
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Can I use EdgeR log2(cpm) instead of voom log2(cpm) to be analyzed as microarray data?
limma
edger
timecourse
without replicate
voom
written 7.5 years ago by
Camila Orellana
▴ 10
1
vote
6
replies
941
views
Time-series RNA-seq analysis using DESeq2
time-series
DESeq2
RNASeq
timecoursedata
TimeCourse
updated 8 months ago by
ATpoint
★ 4.1k • written 8 months ago by
Debebe
• 0
3
votes
5
replies
1.4k
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DESeq2, time-course interpretation
Transcriptomics
TimeCourse
DESeq2
updated 9 months ago by
Michael Love
42k • written 10 months ago by
smac97
• 0
0
votes
2
replies
1.4k
views
DE genes over time with DESeq2
deseq2
timecourse
design and contrast matrix
updated 9 weeks ago by
ta_awwad
▴ 10 • written 8.5 years ago by
Assa Yeroslaviz
★ 1.5k
0
votes
2
replies
174
views
What to the log 2 fold changes mean using LRT on time course in DESeq2
DESeq2
timecourse
DifferentialExpression
updated 4 weeks ago by
James W. MacDonald
65k • written 4 weeks ago by
joshua.mannheimer
• 0
0
votes
1
reply
565
views
DESeq2 + analysis question for design with uneven time point design
timecourse
KEGG
DESeq2
updated 11 months ago by
Michael Love
42k • written 11 months ago by
Fred
• 0
0
votes
1
reply
516
views
DESeq2, Timecourse using fitted splines
timecoursedata
RNASeqData
TimeCourse
DESeq2
updated 10 months ago by
Michael Love
42k • written 10 months ago by
georgii.vdovin
• 0
0
votes
1
reply
247
views
Behavior of most genes in Ribosome-footprints dataset deviates from expected
DESeq2
timecourse
time
updated 3 months ago by
Michael Love
42k • written 3 months ago by
Anastasiia
• 0
0
votes
1
reply
273
views
DESeq Design for Time-Series Analysis
RNASeq
DESeq2
timecourse
4 months ago
WS
• 0
9 results • Page
1 of 1
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Comment: deseq2 results
by
sajadahmad41454
• 0
thank you for your response, should i remove or discard that sample? since the red outlier on left represents one of healthy samples.
Comment: deseq2 results
by
swbarnes2
★ 1.4k
It looks like the PCA plot of a real RNASeq experiment. The red outlier on the left might be the mathematical reason why you have few vali…
Comment: Multi-factorial, longitudinal disease progression analysis with unbalanced patie
by
Dylan.Sheerin
• 0
Thank you very much, Gordon. I'll give voomLmFit a go!
Answer: Multi-factorial, longitudinal disease progression analysis with unbalanced patie
by
Gordon Smyth
50k
Including subjectID in the design matrix always accounts for unbalanced sampling and patient variation but subjects with incomplete records…
Comment: Log-cpm values from limma
by
Gordon Smyth
50k
No, it does not mean that. `voom()` uses the design matrix with the W covariates, to compute precision weights but not to adjust the log-cp…
Votes
Comment: deseq2 results
Comment: deseq2 results
Answer: Multi-factorial, longitudinal disease progression analysis with unbalanced patie
Answer: Extremely small p-values using Limma for proteomic data
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