Bioconductor GOslim

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GO.db GOslim

23 months ago amanda • 0

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gseabase go gene ontology goslim

5.7 years ago • updated 2.6 years ago samwhite ▴ 20

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5.3k

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go GSEABase GOslim gene ontology

5.7 years ago • updated 2.6 years ago samwhite ▴ 20

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GSEA GO goSlim

8.1 years ago maeva.mollion • 0

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biomaRt goslim go

updated 8.9 years ago by Mike Smith ★ 6.6k • written 8.9 years ago by rubi ▴ 110

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gene ontology goslim enrichment analysis gene annotation

9.5 years ago mirko • 0

6 results • Page 1 of 1

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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

Aaron already answered your question. If you have an HDF5 file, it will be read in as a `TENxMatrix` object, which isn't actually read in -…

Comment: Best practice for handling large data (matrix with >2^31-1 non-zero elements) in by dan.gatti • 0

Very strange. We have the same package versions. I tried adding the mtx.class, type, and delayed arguments, but it's still making the coun…

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…

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A: Multi-level experiments in Limma

Answer: Should voomWithQualityWeights still be used when the sample-specific weights var

Answer: DESeq2 for candidate gene analysis

DESeq2 for candidate gene analysis

Answer: DESeq2 for candidate gene analysis

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