Bioconductor Glmnet

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glmnet cox LOOCV k-fold cross validation

updated 6.1 years ago by chris86 ▴ 420 • written 6.1 years ago by Talip ▴ 10

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tcga rnaseq glmnet voom deseq2

8.6 years ago panagiotis.mokos ▴ 40

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rnaseq glmnet limma voom deseq2

8.6 years ago panagiotis.mokos ▴ 40

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glmnet deseq2

updated 8.7 years ago by Michael Love 43k • written 8.7 years ago by panagiotis.mokos ▴ 40

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adaptive-lasso snv biomarkers cv glmnet

8.9 years ago crichard • 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 by teamardigen • 0

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

Join BOC Sciences at Drug Discovery Chemistry

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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