Proper: Simulation for low gene counts Results yield NaN
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Carl • 0
@f7c2710a
Last seen 3.5 years ago
United States

Good morning,

I would like to ask for help when running PROPER. When I set the ngenes 600, the results table returns NaN. for higher countsof ~16k or more I get results just fine.

Are there any adjustments that i can make when using gene counts in the 100's?

Thank you,

Carl

# References to Bioconductor

# Manual              https://www.bioconductor.org/packages/release/bioc/manuals/PROPER/man/PROPER.pdf
# Article & Samples   https://www.bioconductor.org/packages/release/bioc/vignettes/PROPER/inst/doc/PROPER.pdf

#options(pkgType = "binary")
#if (!requireNamespace("BiocManager", quietly = TRUE))
#  install.packages("BiocManager")
#options(pkgType = "binary")
#BiocManager::install("PROPER")


library(PROPER)

## specify some parameters: generate baseline expression and
## dispersion from Bottom data, and specify a function for
## alternative log fold changes.
fun.lfc=function(x) rnorm(x, mean= 12, sd= 1.5)

# Key points
# Use the latest Bioconductor release version. Ensure that your packages are up-to-date.

# Post all of your R code.

# Include a copy of any error or warning messages that appeared in R.

# If your question involves experimental data, include an example of the sample-level covariate data (one row per sample, one column per covariate). If it would help answer your technical question, and can be shared, explain the motivation behind your experiment.

# Always paste the output of sessionInfo() at the end of your post.

# If possible, provide a minimal, self-contained example that someone else can cut-and-paste into a new R session to reproduce your problem.

#If the example produces an error, provide the output of traceback() after the error occurs.
# 16000

simOptions=RNAseq.SimOptions.2grp(ngenes= 600, seqDepth=2000000,lBaselineExpr= "cheung",
                                  lOD="cheung", p.DE=0.05, lfc=fun.lfc)
summary(simOptions)

simRes = runSims(Nreps=c(2,3,4,5), sim.opts = simOptions, nsims=500,
                 DEmethod= "edgeR")


powers = comparePower(simRes)
power.seqDepth(simRes, powers)


#plotPower(powers)
plotAll(powers)



######## SS=2,2 SS=3,3 SS=4,4 SS=5,5
# 0.2    NaN    NaN    NaN    NaN
# 0.5    NaN    NaN    NaN    NaN
# 1      NaN    NaN    NaN    NaN
# 2      NaN    NaN    NaN    NaN
# 5      NaN    NaN    NaN    NaN
# 10     NaN    NaN    NaN    NaN



# sessionInfo()
# R version 4.0.2 (2020-06-22)
# Platform: x86_64-apple-darwin17.0 (64-bit)
# Running under: macOS  10.16
# 
# Matrix products: default
# LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
# 
# locale:
#   [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
# 
# attached base packages:
#   [1] stats     graphics  grDevices utils     datasets  methods   base     
# 
# other attached packages:
#   [1] edgeR_3.30.3  limma_3.44.3  PROPER_1.20.0
# 
# loaded via a namespace (and not attached):
#   [1] Rcpp_1.0.6          locfit_1.5-9.4      lattice_0.20-44     packrat_0.6.0       digest_0.6.27       grid_4.0.2          HDInterval_0.2.2   
# [8] evaluate_0.14       rlang_0.4.11        rmarkdown_2.8       tools_4.0.2         xfun_0.22           yaml_2.2.1          compiler_4.0.2     
# [15] BiocManager_1.30.15 htmltools_0.5.1.1   knitr_1.33 #
PROPER • 558 views
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