Bioconductor Lme4

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limma lme4 mixed

3.0 years ago leandro • 0

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variancepartition lme4 mixedmodel

updated 6.1 years ago by gabriel.hoffman ▴ 170 • written 6.2 years ago by c.taylor • 0

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limma caret lm lmer lme4

updated 6.3 years ago by Aaron Lun ★ 29k • written 6.3 years ago by Sindre ▴ 110

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limma edger lme4

updated 8.7 years ago by Aaron Lun ★ 29k • written 8.7 years ago by bensimon.ariel • 0

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rna-seq edger mixed model random effects lme4

updated 9.3 years ago by Gordon Smyth 53k • written 9.3 years ago by Ekarl2 ▴ 80

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illumina450k limma lme4 lmer

updated 9.5 years ago by Aaron Lun ★ 29k • written 9.5 years ago by DSP • 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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