| Main use-cases | MOI estimation |
| Authors | Meraj Hashemi, Kristan Shneider |
| Latest version | 70fd9fd |
| License | none |
| Website | https://github.com/Maths-against-Malaria/MOI-Bias-correction |
| Code repository | https://github.com/Maths-against-Malaria/MOI-Bias-correction |
| Publication | https://doi.org/10.1371/journal.pone.0261889 |
| Tutorial authors | Alfred Simkin |
| Tutorial date | 11-Dec-23 |
MLMOI
Summary sheet
Purpose
The purpose of MLMOI is to estimate complexity of infection with various corrections for unobservable states. The program also generates simulated datasets. The approach seems to involve simulating datasets and checking to see if the observed data correlates well with the simulated datasets derived by a given model. We were unable to install the package as it has been removed from the R-CRAN library, and had difficulty following the vignettes in the archived package. More specifically, We had difficulty interpreting unitless numbers associated with a given locus for a given sample, and understanding why some missing samples (no sample name) had filled in values and other named samples had missing values). Manual installation (with no package available) was also difficult to follow.
Existing resources
- Any existing online tutorials?
- Any important papers?
Citation
BibTeX style citation. For an R package, you can get this using citation(package = "name"):
Here is an example for DRpower, using citation(package = "DRpower"):
@Manual{,
title = {DRpower: Study design and analysis for pfhrp2/3 deletion prevalence studies},
author = {Bob Verity and Shazia Ruybal},
note = {R package version 1.0.2},
}