In whitneysu/QuantitativePooledTesting: Pooled Testing Strategies with Quantitative Assays
Type Package
Title Quantitative Pooled Testing
Version 0.2.3
Date "r Sys.Date()"
Authors Wanning Su, Tao Liu
Maintainer Wanning Su (wanning_su@brown.edu)
Description This package implements pooled testing with quantitative assays.
License MIT
URL https://github.com/whitneysu/QuantitativePooledTesting
Depends R (>= 3.2.0)
LazyData true
ecdf_pool
empirical cdf calculation
Description
Generates an empirical cdf for quantitative pooled testing
Usage
ecdf_pool(v, N = length(v), cutoff = max(v), ...)
Arguments
- v the numeric vector of the observations for calculating ecdf.For quantitative pooling strategies, only CDF on the support of v<cutoff is needed.
- N the number of observations.
- cutoff cutoff value of the quantitative assay that defines test positivity.
Value
a list of two items: (1) a matrix and (2) a numeric value. The matrix has 3 columns: the support consisting of values of such that v < cutoff, the empirical PMF, and the empirical CDF. The second item in the list output is a numeric value that represents the proportion of total observations that are less than cutoff value v.
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
ecdf_pool(round(runif(100, 0, 20)), cutoff = 18)
to_ecdf_class
Create a ecdf class for ecdf_pool function output
Description
Create an ecdf class object.
Usage
to_ecdf_class(x)
Arguments
- x Output object from the \code{ecdf_pool()} function
Value
An object of class ecdf
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
to_ecdf_class(ecdf_pool(round(runif(100, 0, 20)), cutoff = 18))
convol.dens
convoluting two empirical distributions
Description
This function calculates the convolution of two empirical distributions up to the value of \code{cutoff} (on the sum of two random variables).
Usage
convol.dens(ecdf1, ecdf2, N1, N2, cutoff)
Arguments
- ecdf1 An ecdf that is the matrix output object from the function \code{convol.dens()} itself or from the function
\code{ecdf_pool()}.
- ecdf2 An ecdf that is the matrix output object from the function \code{convol.dens()} itself or from the function
\code{ecdf_pool()}.
- N1 The size of the empirical support of \code{ecdf1}.
- N2 The size of the empirical support of \code{ecdf2}.
- cutoff Cutoff of the support of the resulting convolution distribution.
Value
Returns a list of two items: (1) a matrix and (2) a numeric value. The matrix has 3 columns: the support consisting of values of such that v < cutoff, the empirical PMF, and the empirical CDF. The second item in the list output is a numeric value that represents the proportion of total observations that are less than cutoff value v.
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
ecdf1 <- ecdf_pool(round(runif(100, 0, 20)), cutoff = 18)$out
ecdf2 <- ecdf_pool(round(runif(100, 0, 20)), cutoff = 17)$out
cutoff <- 18
convol.dens(ecdf1, ecdf2, N1, N2, cutoff)
foo_atr
Intermediate Function used by MPA
Description
This function allows you to compute the calculate the ATR for MPA for a range of pool sizes (from 2 to pool size specified)
Usage
foo_atr(v, N = length(v), max_K = 5, cutoff = 1000, quietly = TRUE)
Arguments
- v the numeric vector of the observations for calculating ecdf.For quantitative pooling strategies, only CDF on the support of v<cutoff is needed.
- N the number of observations.
- cutoff cutoff value of the quantitative assay that defines test positivity.
- max_K Maximum pool size that is under consideration.
- quietly Logical value; whether the results print to screen or not.
Value
Returns a three column matrix of 1)pool size, 2)convolution CDF, and the 3)ATR for MPA.
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
v = c(200, 1500, 1900, 800, 950)
max_K = 9
cutoff = 2000
foo_atr(v, N = length(v), max_K, cutoff, quietly = TRUE)
mp_atr
ATR required by MiniPooling(MP)
Description
This function calculates the ATR needed by MP for a range of pool sizes (from 2 to a pool size specified).
Usage
mp_atr(v, N = length(v), max_K = 5, cutoff = 1000, quietly = TRUE)
Arguments
- v the numeric vector of the observations for calculating ecdf.For quantitative pooling strategies, only CDF on the support of v<cutoff is needed.
- N the number of observations.
- cutoff cutoff value of the quantitative assay that defines test positivity.
- max_K Maximum pool size that is under consideration.
- quietly Logical value; whether the results print to screen or not.
Value
The function returns a matrix of two columns: The pool size from 2:max_K and the Average Tests Required by MP given that pool size (MP_ATR).
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
v = c(200, 1500, 1900, 800, 950)
max_K = 9
cutoff = 2000
mp_atr(v, N = length(v), max_K, cutoff, quietly = TRUE)
mpa_atr
ATR required by MPA
Description
This function calculates the ATR needed by MP for a range of pool sizes (from 2 to a pool size specified).
Usage
mpa_atr(v, N = length(v), max_K = 5, cutoff = 1000, quietly = TRUE)
Arguments
- v the numeric vector of the observations for calculating ecdf.For quantitative pooling strategies, only CDF on the support of v<cutoff is needed.
- N the number of observations.
- cutoff cutoff value of the quantitative assay that defines test positivity.
- max_K Maximum pool size that is under consideration.
- quietly Logical value; whether the results print to screen or not.
Value
The function returns a matrix of two columns: The pool size from 2:max_K and the Average Tests Required by MPA given that pool size (MPA_ATR).
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
v = c(200, 1500, 1900, 800, 950)
max_K = 9
cutoff = 2000
mpa_atr(v, N = length(v), max_K, cutoff, quietly = TRUE)
mmpa_atr
ATR required by MMPA
Description
This function calculates the ATR needed by MMPA for a range of pool sizes (from 2 to a pool size specified).
Usage
mmpa_atr(v, N = length(v), max_K = 5, cutoff = 1000, quietly = TRUE, s = )
Arguments
- v the numeric vector of the observations for calculating ecdf.For quantitative pooling strategies, only CDF on the support of v<cutoff is needed.
- N the number of observations.
- cutoff cutoff value of the quantitative assay that defines test positivity.
- max_K Maximum pool size that is under consideration.
- quietly Logical value; whether the results print to screen or not.
- s Risk score that is used for ranked testing
Value
The function returns a matrix of two columns: The pool size from 2:max_K and the Average Tests Required by MMPA given that pool size (MMPA_ATR).
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
v = c(200, 1500, 1900, 800, 950)
max_K = 9
cutoff = 2000
s = c(5, 3, 1, 2, 4)
mmpa_atr(v, s, max_K, cutoff = 2000, quietly = TRUE)
devtools::check_win_devel()
whitneysu/QuantitativePooledTesting documentation built on Feb. 2, 2021, 12:46 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Type Package
Title Quantitative Pooled Testing
Version 0.2.3
Date "r Sys.Date()"
Authors Wanning Su, Tao Liu
Maintainer Wanning Su (wanning_su@brown.edu)
Description This package implements pooled testing with quantitative assays.
License MIT
URL https://github.com/whitneysu/QuantitativePooledTesting
Depends R (>= 3.2.0)
LazyData true
ecdf_pool
empirical cdf calculation
Description
Generates an empirical cdf for quantitative pooled testing
Usage
ecdf_pool(v, N = length(v), cutoff = max(v), ...)
Arguments
- v the numeric vector of the observations for calculating ecdf.For quantitative pooling strategies, only CDF on the support of v<cutoff is needed.
- N the number of observations.
- cutoff cutoff value of the quantitative assay that defines test positivity.
Value
a list of two items: (1) a matrix and (2) a numeric value. The matrix has 3 columns: the support consisting of values of such that v < cutoff, the empirical PMF, and the empirical CDF. The second item in the list output is a numeric value that represents the proportion of total observations that are less than cutoff value v.
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
ecdf_pool(round(runif(100, 0, 20)), cutoff = 18)
to_ecdf_class
Create a ecdf class for ecdf_pool function output
Description
Create an ecdf class object.
Usage
to_ecdf_class(x)
Arguments
- x Output object from the \code{ecdf_pool()} function
Value
An object of class ecdf
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
to_ecdf_class(ecdf_pool(round(runif(100, 0, 20)), cutoff = 18))
convol.dens
convoluting two empirical distributions
Description
This function calculates the convolution of two empirical distributions up to the value of \code{cutoff} (on the sum of two random variables).
Usage
convol.dens(ecdf1, ecdf2, N1, N2, cutoff)
Arguments
- ecdf1 An ecdf that is the matrix output object from the function \code{convol.dens()} itself or from the function \code{ecdf_pool()}.
- ecdf2 An ecdf that is the matrix output object from the function \code{convol.dens()} itself or from the function \code{ecdf_pool()}.
- N1 The size of the empirical support of \code{ecdf1}.
- N2 The size of the empirical support of \code{ecdf2}.
- cutoff Cutoff of the support of the resulting convolution distribution.
Value
Returns a list of two items: (1) a matrix and (2) a numeric value. The matrix has 3 columns: the support consisting of values of such that v < cutoff, the empirical PMF, and the empirical CDF. The second item in the list output is a numeric value that represents the proportion of total observations that are less than cutoff value v.
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
ecdf1 <- ecdf_pool(round(runif(100, 0, 20)), cutoff = 18)$out ecdf2 <- ecdf_pool(round(runif(100, 0, 20)), cutoff = 17)$out cutoff <- 18 convol.dens(ecdf1, ecdf2, N1, N2, cutoff)
foo_atr
Intermediate Function used by MPA
Description
This function allows you to compute the calculate the ATR for MPA for a range of pool sizes (from 2 to pool size specified)
Usage
foo_atr(v, N = length(v), max_K = 5, cutoff = 1000, quietly = TRUE)
Arguments
- v the numeric vector of the observations for calculating ecdf.For quantitative pooling strategies, only CDF on the support of v<cutoff is needed.
- N the number of observations.
- cutoff cutoff value of the quantitative assay that defines test positivity.
- max_K Maximum pool size that is under consideration.
- quietly Logical value; whether the results print to screen or not.
Value
Returns a three column matrix of 1)pool size, 2)convolution CDF, and the 3)ATR for MPA.
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
v = c(200, 1500, 1900, 800, 950) max_K = 9 cutoff = 2000 foo_atr(v, N = length(v), max_K, cutoff, quietly = TRUE)
mp_atr
ATR required by MiniPooling(MP)
Description
This function calculates the ATR needed by MP for a range of pool sizes (from 2 to a pool size specified).
Usage
mp_atr(v, N = length(v), max_K = 5, cutoff = 1000, quietly = TRUE)
Arguments
- v the numeric vector of the observations for calculating ecdf.For quantitative pooling strategies, only CDF on the support of v<cutoff is needed.
- N the number of observations.
- cutoff cutoff value of the quantitative assay that defines test positivity.
- max_K Maximum pool size that is under consideration.
- quietly Logical value; whether the results print to screen or not.
Value
The function returns a matrix of two columns: The pool size from 2:max_K and the Average Tests Required by MP given that pool size (MP_ATR).
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
v = c(200, 1500, 1900, 800, 950) max_K = 9 cutoff = 2000 mp_atr(v, N = length(v), max_K, cutoff, quietly = TRUE)
mpa_atr
ATR required by MPA
Description
This function calculates the ATR needed by MP for a range of pool sizes (from 2 to a pool size specified).
Usage
mpa_atr(v, N = length(v), max_K = 5, cutoff = 1000, quietly = TRUE)
Arguments
- v the numeric vector of the observations for calculating ecdf.For quantitative pooling strategies, only CDF on the support of v<cutoff is needed.
- N the number of observations.
- cutoff cutoff value of the quantitative assay that defines test positivity.
- max_K Maximum pool size that is under consideration.
- quietly Logical value; whether the results print to screen or not.
Value
The function returns a matrix of two columns: The pool size from 2:max_K and the Average Tests Required by MPA given that pool size (MPA_ATR).
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
v = c(200, 1500, 1900, 800, 950) max_K = 9 cutoff = 2000 mpa_atr(v, N = length(v), max_K, cutoff, quietly = TRUE)
mmpa_atr
ATR required by MMPA
Description
This function calculates the ATR needed by MMPA for a range of pool sizes (from 2 to a pool size specified).
Usage
mmpa_atr(v, N = length(v), max_K = 5, cutoff = 1000, quietly = TRUE, s = )
Arguments
- v the numeric vector of the observations for calculating ecdf.For quantitative pooling strategies, only CDF on the support of v<cutoff is needed.
- N the number of observations.
- cutoff cutoff value of the quantitative assay that defines test positivity.
- max_K Maximum pool size that is under consideration.
- quietly Logical value; whether the results print to screen or not.
- s Risk score that is used for ranked testing
Value
The function returns a matrix of two columns: The pool size from 2:max_K and the Average Tests Required by MMPA given that pool size (MMPA_ATR).
Author(s)
Wanning Su (wanning_su@brown.edu), Tao Liu, Joseph Hogan
References
Liu T, Hogan JW, Daniels MJ, et al. (2017). "Improved HIV-1 viral load monitoring capacity using pooled testing with marker-assisted deconvolution." J Acquir Immune Defic Syndr 75(5):580-587.
Examples
v = c(200, 1500, 1900, 800, 950) max_K = 9 cutoff = 2000 s = c(5, 3, 1, 2, 4) mmpa_atr(v, s, max_K, cutoff = 2000, quietly = TRUE)
devtools::check_win_devel()
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