estimate_p_hat: 'estimate_p_hat' Estimates probability of linkage between two...

Description Usage Arguments Details Value Methods (by class) References See Also Examples

View source: R/driver_estimate_transmissision_flows.r

Description

This function computes the probability that pathogen sequences from two individuals randomly sampled from their respective population groups (e.g. communities) are linked.

Usage

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estimate_p_hat(df_counts, ...)

## Default S3 method:
estimate_p_hat(df_counts, ...)

Arguments

df_counts

A data.frame returned by the function: prep_p_hat()

...

Further arguments.

Details

For a population group pairing (u,v), p_hat is computed as the fraction of distinct possible pairs between samples from groups u and v that are linked. Note: The number of distinct possible (u,v) pairs in the sample is the product of sampled individuals in groups u and u. If u = v, then the distinct possible pairs is the number of individuals sampled in population group u choose 2. See bumblebee website for more details https://magosil86.github.io/bumblebee/.

Value

Returns a data.frame containing:

Methods (by class)

References

  1. Magosi LE, et al., Deep-sequence phylogenetics to quantify patterns of HIV transmission in the context of a universal testing and treatment trial – BCPP/ Ya Tsie trial. To submit for publication, 2021.

  2. Carnegie, N.B., et al., Linkage of viral sequences among HIV-infected village residents in Botswana: estimation of linkage rates in the presence of missing data. PLoS Computational Biology, 2014. 10(1): p. e1003430.

See Also

See prep_p_hat to prepare input data to estimate p_hat

Examples

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library(bumblebee)
library(dplyr)

# Estimate the probability of linkage between two individuals randomly sampled from
# two population groups of interest.

# We shall use the data of HIV transmissions within and between intervention and control
# communities in the BCPP/Ya Tsie HIV prevention trial. To learn more about the data 
# ?counts_hiv_transmission_pairs and ?sampling_frequency

# Prepare input to estimate p_hat

# View counts of observed directed HIV transmissions within and between intervention 
# and control communities
counts_hiv_transmission_pairs

# View the estimated number of individuals with HIV in intervention and control 
# communities and the number of individuals sampled from each
sampling_frequency

results_prep_p_hat <- prep_p_hat(group_in = sampling_frequency$population_group, 
                                 individuals_sampled_in = sampling_frequency$number_sampled, 
                                 individuals_population_in = sampling_frequency$number_population, 
                                 linkage_counts_in = counts_hiv_transmission_pairs, 
                                 verbose_output = FALSE)

# View results
results_prep_p_hat

# Estimate p_hat
results_estimate_p_hat <- estimate_p_hat(df_counts = results_prep_p_hat)

# View results 
results_estimate_p_hat

bumblebee documentation built on May 11, 2021, 5:06 p.m.