Bioconductor 10X

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530

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CellRanger emptyDrops scRNAseq 10X

7 months ago rocanja ▴ 60

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907

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SingleCell emptyDrops 10X

updated 17 months ago by Peter Hickey ▴ 740 • written 18 months ago by sandra.garces.19 • 0

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874

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RNAseq 10X

19 months ago wt215 • 0

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3.0k

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DropletUtils emptyDrops scRNA scRNAseq 10x

2.2 years ago Peter Hickey ▴ 740

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1.2k

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DropletUtils emptyDrops 10x

updated 3.8 years ago by Aaron Lun ★ 28k • written 3.8 years ago by Peter Hickey ▴ 740

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1.6k

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deseq2 zinbwave 10X scRNA-seq Differential expression

updated 4.3 years ago by Michael Love 42k • written 4.3 years ago by vincent.croset ▴ 20

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2.8k

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10x scrna-seq

updated 5.5 years ago by Aaron Lun ★ 28k • written 5.5 years ago by jma1991 ▴ 70

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7.7k

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single-cell 10X Cell calling DropletUtils cellranger

updated 5.6 years ago by Aaron Lun ★ 28k • written 5.6 years ago by xingxd16 ▴ 20

8 results • Page 1 of 1

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Answer: Deseq to output continous sequencing data by Michael Love 42k

This what VST is for? Have you see the `rnaseqGene` workflow?

Answer: Adjusted p-values become NA when sub-setting samples by Michael Love 42k

One thing to do is just turn off `independentFiltering` altogether. If you know what are reasonable filters that maintain power by discardi…

Comment: Adjusted p-values become NA when sub-setting samples by Michael Love 42k

Just saw this post, for some reason I didn't get it the first time.

Comment: RNA-seq: samples form different experiments, how to do DGEs? by Philippine • 0

Thank you, indeed I called them lab but their name should be Batch 1, 2, 3, 4, 5 and 6. Thank you again for your help! :D

Comment: Adjusted p-values become NA when sub-setting samples by txema.heredia • 0

I have been back to this after a break. I have run a series of pairwise comparisons using either all the samples together, or only a subset…

Votes

Answer: BiocParallel error when running DiffBind

Answer: Robust way of dealing with low number of samples for Differential Gene Expressio

Comment: DiffBind GreyListChIP error: Error: BiocParallel errors

Answer: Robust way of dealing with low number of samples for Differential Gene Expressio

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