Bioconductor MicrobiomeData

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Metagenomics dada2 MicrobiomeData

15 months ago • updated 13 months ago abhisek001 • 0

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3.2k

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MicrobiomeData ALDEx2

updated 2.5 years ago by Lucie • 0 • written 2.9 years ago by RvH • 0

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MicrobiomeData R microbiomeutilities Install

2.6 years ago abhisek001 • 0

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MicrobiomeData Microbiome

2.8 years ago Levi Waldron ★ 1.1k

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MicrobiomeData curatedMetagenomicData

2.9 years ago • updated 2.8 years ago Pauline ▴ 20

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Network Transcriptomics MicrobiomeData RNASEQ WCGNA

3.1 years ago Julieta • 0

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1.4k

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MicrobiomeData microbiome offtopic

updated 4.2 years ago by James W. MacDonald 68k • written 4.2 years ago by gwagz8 • 0

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1.3k

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sparcc Microbiome microbiomeExplorer MicrobiomeData

updated 4.3 years ago by Kevin Blighe ★ 4.0k • written 4.3 years ago by GlycineMax • 0

8 results • Page 1 of 1

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Comment: Help with defining groups by Phinney, Brett ▴ 10

I got it working , thank you!!!

Comment: Check removeBatchEffect effectiveness by massimo • 0

I would kindly ask for additional support. When not including the design_timepoint argument in removeBatchEffect and thus keeping the inter…

Comment: Error Loading Experiment from SimBenchData Package by ksankaran • 0

Aha, that was it! The object was class Seurat, but I didn't have it installed. After installing, everything works as expected.

Comment: Streamlining the computing time for MiloDE p-value correction in large dataset? by ATpoint ★ 5.0k

Is a method that is so computationally expensive really beneficial and necessary? You seem to have biological replication, don't you, so ps…

Answer: NA values for DESeq2 p-values and adjusted p-values using large sample sizes by ATpoint ★ 5.0k

Outliers without replacement, independent filtering or all-zero counts for that gene. That's the three options that trigger NAs https://bio…

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Comment: Check removeBatchEffect effectiveness

Gene expression associated with continuous (quantitative) traits (Limma/edgeR/correlation)

Answer: Error Loading Experiment from SimBenchData Package

Comment: incomplete imputation of missing values with LEA impute() function

Answer: Expected memory usage for analyzing large single-cell seq datasets (> 450,000 ce

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