Package: coiaf 0.1.2

Aris Paschalidis

coiaf: Complexity of Infection Estimation with Allele Frequencies

Provides a direct method for estimating complexity of infection using easily calculated measures from sequence read depth data.

Authors:Aris Paschalidis [aut, cre], OJ Watson [aut]

coiaf_0.1.2.tar.gz
coiaf_0.1.2.zip(r-4.7-any)coiaf_0.1.2.zip(r-4.6-any)coiaf_0.1.2.zip(r-4.5-any)
coiaf_0.1.2.tgz(r-4.6-any)coiaf_0.1.2.tgz(r-4.5-any)
coiaf_0.1.2.tar.gz(r-4.7-any)coiaf_0.1.2.tar.gz(r-4.6-any)
coiaf_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
coiaf/json (API)

# Install 'coiaf' in R:
install.packages('coiaf', repos = c('https://plasmogenepi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bailey-lab/coiaf/issues

Pkgdown/docs site:https://bailey-lab.github.io

Datasets:

On CRAN:

Conda:

allele-frequenciescoicomplexity-of-infectionestimation

4.13 score 4 stars 17 scripts 23 exports 67 dependencies

Last updated from:3df5509ceb. Checks:9 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develOK167
source / vignettesOK209
linux-releaseOK155
macos-releaseOK173
macos-oldrelOK143
windows-develOK145
windows-releaseOK82
windows-oldrelOK120
wasm-releaseOK110

Exports::=.data%>%as_labelas_namebootstrap_cicompute_coicompute_coi_regressioncont_sensitivitydisc_sensitivityenquoenquoserror_plotlikelihoodoptimize_coioptimize_coi_regressionprocess_realprocess_simsensitivity_plotsim_biallelictheme_coiaftheoretical_coiworld_map

Dependencies:backportsbase64encbootbroombslibcachemcheckmatecliclustercolorspacecpp11data.tabledigestdplyrevaluatefarverfastmapfontawesomeforeignFormulafsgenericsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglifecyclemagrittrmathjaxrmemoisemimennetpillarpkgconfigpurrrR6rappdirsRColorBrewerrlangrmarkdownrpartrstudioapiS7sassscalesstringistringrtibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

Continuous sensitivity analysis
Introduction | Default parameters | Setting our PLMAF | Overall performance | Simulation parameters | Coverage | Loci | Alpha | Overdispersion | Relatedness | Epsilon | Estimation parameters | COI | Sequencing error | Bins | Bin size

Last update: 2023-04-13
Started: 2021-12-27

Discrete sensitivity analysis
Introduction | Default parameters | Setting our PLMAF | Overall performance | Simulation parameters | Coverage | Loci | Alpha | Overdispersion | Relatedness | Epsilon | Estimation parameters | COI | Sequencing error | Bins | Bin size

Last update: 2023-04-13
Started: 2021-12-27

Real data example
Data structure | Estimate the COI | Data visualization

Last update: 2022-12-15
Started: 2020-07-08

Simulator details
Example simulation

Last update: 2022-03-08
Started: 2022-03-08

Readme and manuals

Help Manual

Help pageTopics
Generate bootstrapped CIbootstrap_ci bootstrap_ci.default bootstrap_ci.sim
Predict the COIcompute_coi
Compute COI based on residuals of all loci against theoretical curvescompute_coi_regression
Continuous sensitivity analysiscont_sensitivity
Discrete Sensitivity analysisdisc_sensitivity
Error ploterror_plot
Example real dataexample_real_data
Likelihood of a COIlikelihood
Optimize the COIoptimize_coi
Compute COI based on all points fitted to best fitting curve for COIoptimize_coi_regression
Plot simulated dataautoplot.sim plot-simulation plot.sim
Process real dataprocess_real
Process simulated dataprocess_sim
Sensitivity plotsensitivity_plot
Simulate biallelic datasim_biallelic
Custom ggplot2 themetheme_coiaf
Theoretical COItheoretical_coi
World map plotworld_map