Bioconductor Big data

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1.6k

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NGS R statistics genomics big data Job

6.7 years ago • updated 5.9 years ago Luo Weijun ★ 1.6k

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1.2k

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computational genomic big data bioinformatics Job

6.4 years ago jmaanaki • 0

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computational biology biostatistics big data data science drug discovery Job

6.7 years ago Thomas Girke ★ 1.7k

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big data methylmix memory problem

updated 7.1 years ago by Martin Morgan 25k • written 7.1 years ago by perdedorium • 0

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Rle Big data coverageByTranscript

7.5 years ago hauken_heyken ▴ 80

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wgcna transcriptome big data metagenomics gene expression

7.7 years ago jol.espinoz ▴ 40

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roadmap project annotationhub epigenomics big data

updated 9.5 years ago by Valerie Obenchain ★ 6.8k • written 9.5 years ago by kevin.rue ▴ 350

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Probabilistic Algorithms Big Data Job

10.5 years ago Doe, Aimee ▴ 40

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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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