[Bioc-devel] benchdamic TIMEOUT in merida1 and kunpeng2

Levi Waldron |w@|dron@re@e@rch @end|ng |rom gm@||@com
Mon Jul 17 11:44:42 CEST 2023


It looks to me like benchdamic doesn't actually use the HMP16SData package,
but a repackaged example dataset placed in the data/ directory. I do notice
that the vignette takes very long to run, especially the chunks below. My
guess is that you are seeing differences in speed or number of available
cores on the build machines, one of which can't build the vignette within
the 10-minute time limit (e.g. it takes more than 10 minutes to build on my
laptop). Can you reduce the number of rows or columns in your example
dataset, or reduce permutations, to speed up the computation while still
demonstrating how the package should be used?

```{r runMocks}
bpparam <- BiocParallel::SerialParam()
# Random grouping each time
Stool_16S_mockDA <- runMocks(
    mocks = my_mocks,
    method_list = my_methods,
    object = ps_stool_16S,
    weights = zinbweights,
    verbose = FALSE,
    BPPARAM = bpparam)
```

```{r runSplits}
# Set the parallel framework
# Remember that ANCOMBC based methods are compatible only with SerialParam()
bpparam <- BiocParallel::SerialParam()

# Make sure the subject ID variable is a factor
phyloseq::sample_data(ps_plaque_16S)[, "RSID"] <- as.factor(
    phyloseq::sample_data(ps_plaque_16S)[["RSID"]])

Plaque_16S_splitsDA <- runSplits(
    split_list = my_splits,
    method_list = my_methods_noWeights,
    normalization_list = my_normalizations,
    object = ps_plaque_16S,
    min_counts = 0, min_samples = 2,
    verbose = TRUE,
    BPPARAM = bpparam)
```

(returns lots of "Warning: Computed variance-covariance matrix problem: not
a positive definite matrix (and positive semidefiniteness is not
checked); returning
NA matrixboundary (singular) fit: see help('isSingular')" warnings)


-- 

Levi Waldron

Associate Professor

Department of Epidemiology and Biostatistics

CUNY Graduate School of Public Health and Health Policy

Institute for Implementation Science in Population Health

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https://waldronlab.io

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