call_DA_DESeq2: Evaluate differential abundance with DESeq2 (via Seurat)
In kimberlyroche/codaDE: What the Package Does in One 'Title Case' Line
call_DA_DESeq2 R Documentation
Evaluate differential abundance with DESeq2 (via Seurat)
Description
Evaluate differential abundance with DESeq2 (via Seurat)
Usage
call_DA_DESeq2(data, groups, control_indices = NULL)
Arguments
data
simulated data set (samples x features)
groups
group (cohort) labels
control_indices
if specified, these features are used as the stable
features against which to normalize observed abundances (DESeq2-only)
Value
unadjusted p-values and "effect sizes" for DA for all features
kimberlyroche/codaDE documentation built on May 11, 2022, 12:40 a.m.
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| call_DA_DESeq2 | R Documentation |
Evaluate differential abundance with DESeq2 (via Seurat)
Description
Evaluate differential abundance with DESeq2 (via Seurat)
Usage
call_DA_DESeq2(data, groups, control_indices = NULL)
Arguments
data |
simulated data set (samples x features) |
groups |
group (cohort) labels |
control_indices |
if specified, these features are used as the stable features against which to normalize observed abundances (DESeq2-only) |
Value
unadjusted p-values and "effect sizes" for DA for all features
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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