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fittimeseries
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time series RNA-seq allowing time offset between individuals
edgeR
deseq2
rna-seq
timecourse
fittimeseries
updated 7.2 years ago by
Aaron Lun
★ 29k • written 7.2 years ago by
jpsf
• 0
1
vote
4
replies
1.8k
views
error using fitTimeSeries in metagenomeSeq
metagenomeseq
fittimeseries
updated 9.0 years ago by
Joseph Nathaniel Paulson
▴ 280 • written 9.0 years ago by
wijera81
• 0
0
votes
1
reply
1.3k
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fitTimeSeries possible error
metagenomeseq
fittimeseries
updated 9.2 years ago by
Joseph Nathaniel Paulson
▴ 280 • written 9.2 years ago by
giulia.masetti
• 0
0
votes
2
replies
1.7k
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edge, timeseries analysis, model specification question
edge
timecourse
fittimeseries
updated 9.9 years ago by
Andrew Bass
• 0 • written 10.0 years ago by
warren.anderson
• 0
2
votes
2
replies
1.7k
views
no timeInterval output using fitTimeSeries
metagenomeSeq
fitTimeSeries
microbiome
10.8 years ago
noelle.noyes
▴ 30
5 results • Page
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Comment: Interpretation of output of AffyRNAdeg and hist commands
by
debasainalsa
• 0
When working with AffyRNAdeg output it helps to think of the table like browsing a HEYTEA Menu each row shows a feature of your slides and …
Comment: DESeq2 for candidate gene analysis
by
piffelpaff
▴ 20
thank you so much for answering Dr. Love!
Answer: DESeq2 for candidate gene analysis
by
Michael Love
43k
Your plan 1 is reasonable. Run DESeq2 on the whole dataset to obtain size factors and moderated dispersion estimates and then extract the u…
Comment: Best practice for handling large data (matrix with >2^31-1 non-zero elements) in
by
James W. MacDonald
68k
Oh. ``` > z <- read10xCounts(c(tmpdir, tmpdir), mtx.class = "SVT_SparseMatrix", delayed = TRUE) > class(counts(z)) [1] "DelayedMatrix" att…
Comment: Best practice for handling large data (matrix with >2^31-1 non-zero elements) in
by
James W. MacDonald
68k
That's weird. Using the example data works for me. ``` > example(read10xCounts) rd10xC> # Mocking up some 10X genomics output. rd10xC> ex…
Votes
Answer: DESeq2 for candidate gene analysis
DESeq2 for candidate gene analysis
Answer: DESeq2 for candidate gene analysis
DESeq2 for candidate gene analysis
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