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Job:
Postdoc+PhD position: Spatial & Single-Cell Computational Immunogenomics for Cancer Diagnosis
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CuratedAtlasQueryR
MoleculeExperiment
SingleCellExperiment
SpatialExperiment
15 months ago
Stefano Mangiola
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News:
Interested in the analysis of Spatial Omics data?
tidySpatialExperiment
SpatialExperiment
MoleculeExperiment
17 months ago
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DESeq with multiple condition
MoleculeExperiment
DifferentialExpression
DESeq2
updated 21 months ago by
ATpoint
★ 5.0k • written 21 months ago by
michelafrancesconi8
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Missing genes in the differentially expressed gene list which otherwise are expected to show expression post treatment.
MoleculeExperiment
updated 2.1 years ago by
ATpoint
★ 5.0k • written 2.1 years ago by
irenekokosaikia
• 0
4 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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