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Which one is more trustable for Cox Proportional Hazard Model with Lasso penalty? LOOCV or K-fold cross-validation?
glmnet
cox
LOOCV
k-fold
cross validation
updated 6.1 years ago by
chris86
▴ 420 • written 6.2 years ago by
Talip
▴ 10
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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…
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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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