Command Line Arguments

Sha Zhu

2024-10-14

#Program parameters and options

Mostly used

You may also try

Example

Data exploration, plot the read count ALT vs REF.

library(DEploid)

vcfFile = system.file("extdata", "PG0390-C.test.vcf.gz", package = "DEploid")
PG0390 = extractCoverageFromVcf(vcfFile)
plotAltVsRef( PG0390$refCount, PG0390$altCount )

Plot the histogram of the observed allele frequency within sample.

obsWSAF = computeObsWSAF( PG0390$altCount, PG0390$refCount )
histWSAF(obsWSAF)

Load prior information: PLAF and reference panel

plafFile = system.file("extdata", "labStrains.test.PLAF.txt", package = "DEploid")
plaf = extractPLAF(plafFile)
panelFile = system.file("extdata", "labStrains.test.panel.txt", package = "DEploid")

Deconvolute the haplotypes

set.seed(1)
PG0390.deconv = dEploid(paste("-vcf", vcfFile, "-plaf", plafFile, "-panel", panelFile))
prop = PG0390.deconv$Proportions[dim(PG0390.deconv$Proportions)[1],]
expWSAF = t(PG0390.deconv$Haps) %*% prop

Plot the allele frequency within sample (observed in red, expected in blue) against the population level allele frequency.

plotWSAFvsPLAF(plaf, obsWSAF, expWSAF)

Plot the history of the MCMC proportion estimates.

plotProportions(PG0390.deconv$Proportions)

Plot the allele frequency within sample, observed against expected.

plotObsExpWSAF(obsWSAF, expWSAF)

Reporting Bugs

If you encounter any problem when using dEploid, please file a short bug report by using the issue tracker on GitHub or email joe.zhu (at) well.ox.ac.uk.

Please include the output of dEploid -v and the platform you are using dEploid on in the report. If the problem occurs while executing dEploid, please also include the command you are using and the random seed.

Thank you!

Citing DEploid

If you use dEploid with the flag -ibd, please cite the following paper:

Zhu, J. S., J. A. Hendry, J. Almagro-Garcia, R. D. Pearson, R. Amato, A. Miles, D. J. Weiss, T. C. D. Lucas, M. Nguyen, P. W. Gething, D. Kwiatkowski, G. McVean, and for the Pf3k Project. (2018) The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria. eLife, 40845, doi: https://doi.org/10.7554/eLife.40845.

If you use dEploid in your work, please cite the program:

Zhu, J. S., J. A. Garcia, G. McVean. (2018) Deconvolution of multiple infections in Plasmodium falciparum from high throughput sequencing data. Bioinformatics 34(1), 9-15. doi: https://doi.org/10.1093/bioinformatics/btx530.

Bibtex record::

@article {Zhu387266, author = {Zhu, Sha Joe and Hendry, Jason A. and Almagro-Garcia, Jacob and Pearson, Richard D. and Amato, Roberto and Miles, Alistair and Weiss, Daniel J. and Lucas, Tim C.D. and Nguyen, Michele and Gething, Peter W. and Kwiatkowski, Dominic and McVean, Gil and ,}, title = {The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria}, year = {2018}, doi = {10.1101/387266}, publisher = {Cold Spring Harbor Laboratory}, URL = {https://www.biorxiv.org/content/10.1101/387266v1}, eprint = {https://www.biorxiv.org/content/biorxiv/early/2018/08/09/387266.full.pdf}, journal = {bioRxiv} }

@article {Zhubtx530, author = {Zhu, Sha Joe and Almagro-Garcia, Jacob and McVean, Gil}, title = {Deconvolution of multiple infections in {{}} from high throughput sequencing data}, year = {2017}, doi = {10.1093/bioinformatics/btx530}, URL = {https://doi.org/10.1093/bioinformatics/btx530}, journal = {Bioinformatics} }