call_DA_ANCOMBC: Evaluate differential abundance with ANCOM-BC
In kimberlyroche/codaDE: What the Package Does in One 'Title Case' Line
call_DA_ANCOMBC R Documentation
Evaluate differential abundance with ANCOM-BC
Description
Evaluate differential abundance with ANCOM-BC
Usage
call_DA_ANCOMBC(data, groups)
Arguments
data
simulated data set
groups
group (cohort) labels
use_TMM
if TRUE, uses the trimmed mean of M-values normalization
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_ANCOMBC | R Documentation |
Evaluate differential abundance with ANCOM-BC
Description
Evaluate differential abundance with ANCOM-BC
Usage
call_DA_ANCOMBC(data, groups)
Arguments
data |
simulated data set |
groups |
group (cohort) labels |
use_TMM |
if TRUE, uses the trimmed mean of M-values normalization |
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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