| Type: | Package |
| Title: | Calculate 4 Key Reporting Measures |
| Version: | 1.0.2 |
| Maintainer: | Jacob Dehinsilu <jacobdehinsilu@outlook.com> |
| Description: | Perform calculations for the WHO International Reference Reagents for the microbiome. Using strain, species or genera abundance tables generated through analysis of 16S ribosomal RNA sequencing or shotgun sequencing which included a reference reagent. This package will calculate measures of sensitivity, False positive relative abundance, diversity, and similarity based on mean average abundances with respect to the reference reagent. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.2.3 |
| Imports: | readxl, vegan |
| Suggests: | testthat, knitr, rmarkdown |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2024-09-13 00:02:10 UTC; Jacob |
| Author: | Jacob Dehinsilu 
[aut, cre],
Ravneet Bhuller [aut] |
| Depends: | R (≥ 3.5.0) |
| Repository: | CRAN |
| Date/Publication: | 2024-09-16 07:20:02 UTC |
MQC_testdata
Description
Data used for demonstrating the functionality of the microbiomeMQC package.
Usage
data(MQC_testdata)
Format
An object of class data.frame with 26 rows and 6 columns:
- Column1
species
- Column2
DNA_hilo_RR
- Column3
perfect result
- Column4
high FPRA example
- Column5
high diversity example
- Column6
low sensitivity example
Source
Generated by the package authors for demonstration purposes.
Calculate 4 key reporting measures
Description
Calculate the 4 key reporting measures for the WHO International Reference Reagents for the microbiome
Usage
microbiomeMQC(input, taxonomic_level, output)
Arguments
input |
Path to the .xlsx or .csv file.e.g. "C:\Users\joeblogs\Desktop\data.xlsx" |
taxonomic_level |
The taxonomic level ("strain", "species", or "genus") that you are using. |
output |
Path to save the output CSV file (file path must end with the file name e.g. "C:\Users\joeblogs\Desktop\MQC.csv" |
Details
The 4 key reporting measures (using the example of species) are:
Sensitivity: How many species from the reagent are correctly identified.
Diversity: The total number of species detected.
FPRA: The relative abundance of false positives.
Similarity: The Bray-Curtis dissimilarity in composition between the species profile reported and the 'ground truth' profile of the reagent.
To see how the data should be formatted do: data(MQC_testdata) FP = false positive i.e. those bacteria that do not appear in the reagent
Value
No return value. The function writes the results to the specified CSV file.
Examples
input <- system.file("extdata", "MQC_testdata.csv", package = "microbiomeMQC")
output <- tempfile(fileext = ".csv")
microbiomeMQC(input, "species", output)