Bioconductor Prostar

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Prostar

3.7 years ago benoit.marchand • 0

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Prostar

updated 3.4 years ago by Wang • 0 • written 3.9 years ago by benoit.marchand • 0

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prostar proteomics

7.3 years ago laural710 • 0

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1.8k

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prostar proteomics rforproteomics annotationforge

updated 7.4 years ago by Samuel Wieczorek ▴ 10 • written 7.4 years ago by lolli.langan ▴ 20

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1.7k

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Prostar Dapar clusterprofiler

updated 7.4 years ago by Samuel Wieczorek ▴ 10 • written 7.4 years ago by laural710 • 0

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1.4k

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install error package installation DAPAR prostar R version 3.4.4

7.5 years ago rita.reig • 0

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1.7k

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Prostar

updated 7.9 years ago by Samuel Wieczorek ▴ 10 • written 9.0 years ago by kamal.fartiyal84 ▴ 10

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1.8k

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Prostar DAPAR software error

updated 7.9 years ago by Samuel Wieczorek ▴ 10 • written 8.0 years ago by van.theodorakis • 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…

Votes

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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