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preprocessQuantile
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Normalization in methylation analysis
Methylation
minfi
preprocessQuantile
MethylationArrayData
preprocessFunnorm
22 months ago
kyj2226
• 0
1
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3
replies
4.0k
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normalization combination of noob + BMIQ/Quantile
minfi
bmiq
noob
preprocessQuantile
champ
updated 5.1 years ago by
James W. MacDonald
68k • written 5.1 years ago by
Lin
▴ 50
0
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2.5k
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getSex error even when sex is provided
minfi
estimatecellcounts
getSex
preprocessQuantile
updated 7.3 years ago by
Kasper Daniel Hansen
★ 6.5k • written 7.3 years ago by
fgc
• 0
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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…
Comment: Join BOC Sciences at Drug Discovery Chemistry
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teamardigen
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Sounds like an exciting event for anyone passionate about small molecule innovation. The focus on discovery and optimization really drives …
Comment: Best practice for handling large data (matrix with >2^31-1 non-zero elements) in
by
dan.gatti
• 0
I am, but perhaps I'm not understanding how it should work. > sse = DropletUtils::read10xCounts(curr_files[1], mtx.class = 'SVT_Sparse…
Comment: Best practice for handling large data (matrix with >2^31-1 non-zero elements) in
by
James W. MacDonald
68k
Did you use the development version as Aaron suggested? There is an argument to read the market matrix file directly into an `SVT_SparseMat…
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DESeq2 for candidate gene analysis
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Drug datasets for RNA-seq
Comment: Check removeBatchEffect effectiveness
Comment: Streamlining the computing time for MiloDE p-value correction in large dataset?
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