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multifactorial
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deseq2 nested multifactorial analysis
DESeq2
multifactorial
nested
updated 2.6 years ago by
Basti
▴ 780 • written 2.6 years ago by
jd
• 0
0
votes
1
reply
1.1k
views
Log2FC in LRT vs Wald in multifactorial design
DESeq2
LRT
multifactorial
up/down-reg
log2FC
updated 2.8 years ago by
James W. MacDonald
68k • written 2.8 years ago by
Laia
▴ 10
0
votes
1
reply
984
views
Interpreting results from DESeq2 time-series multifactorial data analysis
DESeq2
time-series
timecoursedata
timecourse
multifactorial
updated 2.9 years ago by
Michael Love
43k • written 2.9 years ago by
arshad1292
• 0
0
votes
2
replies
1.5k
views
DESeq2 interaction terms in 2x2x2 factorial design
Interactions
design
Multifactorial
DESeq2
updated 3.9 years ago by
swbarnes2
★ 1.4k • written 3.9 years ago by
Marie
• 0
4 results • Page
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Comment: Help with defining groups
by
Phinney, Brett
▴ 10
I got it working , thank you!!!
Comment: Check removeBatchEffect effectiveness
by
massimo
• 0
I would kindly ask for additional support. When not including the design_timepoint argument in removeBatchEffect and thus keeping the inter…
Comment: Error Loading Experiment from SimBenchData Package
by
ksankaran
• 0
Aha, that was it! The object was class Seurat, but I didn't have it installed. After installing, everything works as expected.
Comment: Streamlining the computing time for MiloDE p-value correction in large dataset?
by
ATpoint
★ 5.0k
Is a method that is so computationally expensive really beneficial and necessary? You seem to have biological replication, don't you, so ps…
Answer: NA values for DESeq2 p-values and adjusted p-values using large sample sizes
by
ATpoint
★ 5.0k
Outliers without replacement, independent filtering or all-zero counts for that gene. That's the three options that trigger NAs https://bio…
Votes
Comment: Check removeBatchEffect effectiveness
Gene expression associated with continuous (quantitative) traits (Limma/edgeR/correlation)
Answer: Error Loading Experiment from SimBenchData Package
Comment: incomplete imputation of missing values with LEA impute() function
Answer: Expected memory usage for analyzing large single-cell seq datasets (> 450,000 ce
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