| Title: | 'DEploid' Data Analysis and Results Interpretation |
| Version: | 0.0.1 |
| Description: | 'DEploid' (Zhu et.al. 2018 <doi:10.1093/bioinformatics/btx530>) is designed for deconvoluting mixed genomes with unknown proportions. Traditional phasing programs are limited to diploid organisms. Our method modifies Li and Stephen’s algorithm with Markov chain Monte Carlo (MCMC) approaches, and builds a generic framework that allows haloptype searches in a multiple infection setting. This package provides R functions to support data analysis and results interpretation. |
| Depends: | R (≥ 3.1.0) |
| Imports: | Rcpp (≥ 0.11.2), scales (≥ 0.4.0), magrittr (≥ 1.5), combinat |
| Suggests: | knitr, rmarkdown(≥ 1.6), circlize, testthat (≥ 0.9.0) |
| LinkingTo: | Rcpp |
| RoxygenNote: | 7.3.2 |
| Encoding: | UTF-8 |
| Date: | 2024-11-18 |
| License: | Apache License (≥ 2) |
| NeedsCompilation: | yes |
| Packaged: | 2024-12-18 12:02:05 UTC; rstudio |
| Author: | Joe Zhu  [aut,
cre],
Jacob Almagro-Garcia [aut],
Gil McVean [aut],
University of Oxford [cph],
Yinghan Liu [ctb],
CodeCogs Zyba Ltd [com, cph],
Deepak Bandyopadhyay [com, cph],
Lutz Kettner [com, cph] |
| Maintainer: | Joe Zhu <sha.joe.zhu@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2024-12-19 16:00:18 UTC |
DEploid.utils: 'DEploid' Data Analysis and Results Interpretation
Description
'DEploid' (Zhu et.al. 2018 doi:10.1093/bioinformatics/btx530) is designed for deconvoluting mixed genomes with unknown proportions. Traditional phasing programs are limited to diploid organisms. Our method modifies Li and Stephen’s algorithm with Markov chain Monte Carlo (MCMC) approaches, and builds a generic framework that allows haloptype searches in a multiple infection setting. This package provides R functions to support data analysis and results interpretation.
Traditional phasing programs are limited to diploid organisms. Our method modifies Li and Stephens algorithm with Markov chain Monte Carlo (MCMC) approaches, and builds a generic framework that allows haplotype searches in a multiple infection setting. This package is primarily developed as part of #' the Pf3k project, which is a global collaboration using the latest sequencing technologies to provide a high-resolution view of natural variation in the malaria parasite Plasmodium falciparum. Parasite DNA are extracted from patient blood sample, which often contains more than one parasite strain, with unknown proportions. This package is used for deconvoluting mixed haplotypes, #' and reporting the mixture proportions from each sample.
Author(s)
Maintainer: Joe Zhu sha.joe.zhu@gmail.com (ORCID)
Authors:
Jacob Almagro-Garcia
Gil McVean
Other contributors:
University of Oxford [copyright holder]
Yinghan Liu [contributor]
CodeCogs Zyba Ltd [compiler, copyright holder]
Deepak Bandyopadhyay [compiler, copyright holder]
Lutz Kettner [compiler, copyright holder]
Joe Zhu
Maintainer: Joe Zhu sha.joe.zhu@gmail.com
Compute observed WSAF
Description
Compute observed allele frequency within sample from the allele counts.
Usage
computeObsWSAF(alt, ref)
Arguments
alt |
Numeric array of alternative allele count. |
ref |
Numeric array of reference allele count. |
Value
Numeric array of observed allele frequency within sample.
See Also
histWSAF for histogram.
Examples
# Example 1
refFile <- system.file("extdata", "PG0390-C.test.ref", package = "DEploid.utils")
altFile <- system.file("extdata", "PG0390-C.test.alt", package = "DEploid.utils")
PG0390CoverageTxt <- extractCoverageFromTxt(refFile, altFile)
obsWSAF <- computeObsWSAF(PG0390CoverageTxt$altCount, PG0390CoverageTxt$refCount)
# Example 2
vcfFile <- system.file("extdata", "PG0390-C.test.vcf.gz", package = "DEploid.utils")
PG0390CoverageVcf <- extractCoverageFromVcf(vcfFile, "PG0390-C")
obsWSAF <- computeObsWSAF(PG0390CoverageVcf$altCount, PG0390CoverageVcf$refCount)
Extract read counts from plain text file
Description
Extract read counts from tab-delimited text files of a single sample.
Usage
extractCoverageFromTxt(refFileName, altFileName)
Arguments
refFileName |
Path of the reference allele count file. |
altFileName |
Path of the alternative allele count file. |
Value
A data.frame contains four columns: chromosomes, positions, reference allele count, alternative allele count.
Note
The allele count files must be tab-delimited. The allele count files contain three columns: chromosomes, positions and allele count.
Examples
refFile <- system.file("extdata", "PG0390-C.test.ref", package = "DEploid.utils")
altFile <- system.file("extdata", "PG0390-C.test.alt", package = "DEploid.utils")
PG0390 <- extractCoverageFromTxt(refFile, altFile)
Extract VCF information
Description
Extract VCF information
Usage
extractCoverageFromVcf(filename, samplename)
Arguments
filename |
VCF file name. |
samplename |
Sample name |
Value
A dataframe list with members of haplotypes, proportions and log likelihood of the MCMC chain.
-
CHROMSNP chromosomes. -
POSSNP positions. -
refCountreference allele count. -
altCountalternative allele count.
See Also
-
extractCoverageFromVcf -
extractCoverageFromTxt
Examples
vcfFile = system.file("extdata", "PG0390-C.test.vcf.gz", package = "DEploid.utils")
vcf = extractCoverageFromVcf(vcfFile, "PG0390-C")
Extract PLAF
Description
Extract population level allele frequency (PLAF) from text file.
Usage
extractPLAF(plafFileName)
Arguments
plafFileName |
Path of the PLAF text file. |
Value
A numeric array of PLAF
Note
The text file must have header, and population level allele frequency recorded in the "PLAF" field.
Examples
plafFile <- system.file("extdata", "labStrains.test.PLAF.txt", package = "DEploid.utils")
plaf <- extractPLAF(plafFile)
Painting haplotype according the reference panel
Description
Plot the posterior probabilities of a haplotype given the refernece panel.
Usage
haplotypePainter(
posteriorProbabilities,
title = "",
labelScaling,
numberOfInbreeding = 0
)
Arguments
posteriorProbabilities |
Posterior probabilities matrix with the size of number of loci by the number of reference strain. |
title |
Figure title. |
labelScaling |
Scaling parameter for plotting. |
numberOfInbreeding |
Number of inbreading strains |
Value
No return value called for side effects
WSAF histogram
Description
Produce histogram of the allele frequency within sample.
Usage
histWSAF(
obsWSAF,
exclusive = TRUE,
title = "Histogram 0<WSAF<1",
cex.lab = 1,
cex.main = 1,
cex.axis = 1
)
Arguments
obsWSAF |
Observed allele frequency within sample |
exclusive |
When TRUE 0 < WSAF < 1; otherwise 0 <= WSAF <= 1. |
title |
Histogram title |
cex.lab |
Label size. |
cex.main |
Title size. |
cex.axis |
Axis text size. |
Value
histogram
Examples
# Example 1
refFile <- system.file("extdata", "PG0390-C.test.ref", package = "DEploid.utils")
altFile <- system.file("extdata", "PG0390-C.test.alt", package = "DEploid.utils")
PG0390CoverageTxt <- extractCoverageFromTxt(refFile, altFile)
obsWSAF <- computeObsWSAF(PG0390CoverageTxt$altCount, PG0390CoverageTxt$refCount)
histWSAF(obsWSAF)
myhist <- histWSAF(obsWSAF, FALSE)
# Example 2
vcfFile <- system.file("extdata", "PG0390-C.test.vcf.gz", package = "DEploid.utils")
PG0390CoverageVcf <- extractCoverageFromVcf(vcfFile, "PG0390-C")
obsWSAF <- computeObsWSAF(PG0390CoverageVcf$altCount, PG0390CoverageVcf$refCount)
histWSAF(obsWSAF)
myhist <- histWSAF(obsWSAF, FALSE)
Plot coverage
Description
Plot alternative allele count vs reference allele count at each site.
Usage
plotAltVsRef(
ref,
alt,
title = "Alt vs Ref",
exclude.ref = c(),
exclude.alt = c(),
potentialOutliers = c(),
cex.lab = 1,
cex.main = 1,
cex.axis = 1
)
Arguments
ref |
Numeric array of reference allele count. |
alt |
Numeric array of alternative allele count. |
title |
Figure title, "Alt vs Ref" by default |
exclude.ref |
Numeric array of reference allele count at sites that are not deconvoluted. |
exclude.alt |
Numeric array of alternative allele count at sites that are not deconvoluted |
potentialOutliers |
Potential outliers |
cex.lab |
Label size. |
cex.main |
Title size. |
cex.axis |
Axis text size. |
Value
No return value called for side effects
Examples
# Example 1
refFile <- system.file("extdata", "PG0390-C.test.ref", package = "DEploid.utils")
altFile <- system.file("extdata", "PG0390-C.test.alt", package = "DEploid.utils")
PG0390CoverageTxt <- extractCoverageFromTxt(refFile, altFile)
plotAltVsRef(PG0390CoverageTxt$refCount, PG0390CoverageTxt$altCount)
# Example 2
vcfFile <- system.file("extdata", "PG0390-C.test.vcf.gz", package = "DEploid.utils")
PG0390CoverageVcf <- extractCoverageFromVcf(vcfFile, "PG0390-C")
plotAltVsRef(PG0390CoverageVcf$refCount, PG0390CoverageVcf$altCount)
Plot WSAF
Description
Plot observed alternative allele frequency within sample against expected WSAF.
Usage
plotObsExpWSAF(
obsWSAF,
expWSAF,
title = "WSAF(observed vs expected)",
cex.lab = 1,
cex.main = 1,
cex.axis = 1
)
Arguments
obsWSAF |
Numeric array of observed WSAF. |
expWSAF |
Numeric array of expected WSAF. |
title |
Figure title. |
cex.lab |
Label size. |
cex.main |
Title size. |
cex.axis |
Axis text size. |
Value
No return value called for side effects
Plot proportions
Description
Plot the MCMC samples of the proportion, indexed by the MCMC chain.
Usage
plotProportions(
proportions,
title = "Components",
cex.lab = 1,
cex.main = 1,
cex.axis = 1
)
Arguments
proportions |
Matrix of the MCMC proportion samples. The matrix size is number of the MCMC samples by the number of strains. |
title |
Figure title. |
cex.lab |
Label size. |
cex.main |
Title size. |
cex.axis |
Axis text size. |
Value
No return value called for side effects
Plot WSAF vs PLAF
Description
Plot allele frequencies within sample against population level.
Usage
plotWSAFvsPLAF(
plaf,
obsWSAF,
expWSAF = c(),
potentialOutliers = c(),
title = "WSAF vs PLAF",
cex.lab = 1,
cex.main = 1,
cex.axis = 1
)
Arguments
plaf |
Numeric array of population level allele frequency. |
obsWSAF |
Numeric array of observed altenative allele frequencies within sample. |
expWSAF |
Numeric array of expected WSAF from model. |
potentialOutliers |
Potential outliers |
title |
Figure title, "WSAF vs PLAF" by default |
cex.lab |
Label size. |
cex.main |
Title size. |
cex.axis |
Axis text size. |
Value
No return value called for side effects
Examples
# Example 1
refFile <- system.file("extdata", "PG0390-C.test.ref", package = "DEploid.utils")
altFile <- system.file("extdata", "PG0390-C.test.alt", package = "DEploid.utils")
PG0390CoverageTxt <- extractCoverageFromTxt(refFile, altFile)
obsWSAF <- computeObsWSAF(PG0390CoverageTxt$altCount, PG0390CoverageTxt$refCount)
plafFile <- system.file("extdata", "labStrains.test.PLAF.txt", package = "DEploid.utils")
plaf <- extractPLAF(plafFile)
plotWSAFvsPLAF(plaf, obsWSAF)
# Example 2
vcfFile <- system.file("extdata", "PG0390-C.test.vcf.gz", package = "DEploid.utils")
PG0390CoverageVcf <- extractCoverageFromVcf(vcfFile, "PG0390-C")
obsWSAF <- computeObsWSAF(PG0390CoverageVcf$altCount, PG0390CoverageVcf$refCount)
plafFile <- system.file("extdata", "labStrains.test.PLAF.txt", package = "DEploid.utils")
plaf <- extractPLAF(plafFile)
plotWSAFvsPLAF(plaf, obsWSAF)