Description Usage Arguments Value References See Also Examples

View source: R/pooling-basic-funs.R

This function uses Monte Carlo (MC) to simulate different orders in
which the samples would be collected to form pools. Unlike the
function `minipool`

, `mpa`

, and `mmpa`

that calculate
the number of assays
needed for pools that are formed following the exact order
of the samples that are listed in the data, this function
`pooling_mc`

permutes the data many (`perm_num`

) times
so as to estimate the average number of
assays required (ATR) per individual. Using MC avoids the dependence
on any
specific ordering of forming pools.

1 2 | ```
pooling_mc(v, s = NULL, K = 5, vf_cut = 1000, lod = 0,
method = "mmpa", perm_num = 100, msg = F)
``` |

`v` |
A vector of non-negative numerical assay results. |

`s` |
A vector of risk scores; |

`K` |
Pool size; default is |

`vf_cut` |
Cutoff value for defining positive cases;
default is |

`lod` |
A vector of lower limits of detection or a scalar if the limits are the
same; default is |

`method` |
Method that is used for pooled testing; must be one of |

`perm_num` |
The number of permutation to be used for the calculation;
default is |

`msg` |
Message generated during calculation; default is |

The outcome is a matrix of dimension `num_pool`

by `perm_num`

.
The row number is the number of pools (`num_pool`

) from each permutation
of the data, which is
determined by the sample size `N`

and pool size `K`

; ```
num_pool
= N%/%K
```

. The column number is the number of
permutations (`num_pool`

).

Liu T, Hogan JW, Daniels, MJ, Coetzer M, Xu Y, Bove G, et al. Improved HIV-1 Viral Load Monitoring Capacity Using Pooled Testing with Marker-Assisted Deconvolution. Journal of AIDS. 2017;75(5): 580-587.

Bilder CR, Tebbs JM, Chen P. Informative retesting. Journal of the American Statistical Association. 2010;105(491):942-955.

May S, Gamst A, Haubrich R, Benson C, Smith DM. Pooled nucleic acid testing to identify antiretroviral treatment failure during HIV infection. Journal of Acquired Immune Deficiency Syndromes. 2010;53(2):194-201.

Dorfman R. The detection of defective members of large populations. The Annals of Mathematical Statistics. 1943;14(4):436-440.

minipool, mpa, mmpa

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | ```
### sample size = 300
n = 300;
set.seed(100)
pvl = rgamma(n, shape = 2.8, scale = 150)
summary(pvl)
# Min. 1st Qu. Median Mean 3rd Qu. Max.
# 53 225 392 424 564 1373
riskscore = (rank(pvl)/n) * 0.5 + runif(n) * 0.5
cor(pvl, riskscore, method = "spearman")
# [1] 0.69
### Pool size K is set to 5
K=5;
### so, the number of pools = 60
n.pool = n/K; n.pool
# [1] 60
foo = pooling_mc(pvl, riskscore, perm_num = 100)
### Average number of assays needed per pool for each of the 100
### permutations of the data
apply(foo, 2, mean)
# [1] 3.43 3.33 3.35 3.47 3.37 3.33 3.37 3.27 3.43 3.28 3.32 3.35 3.35 3.37
# [15] 3.38 3.37 3.30 3.43 3.28 3.38 3.42 3.35 3.35 3.48 3.30 3.47 3.40 3.35
# [29] 3.25 3.30 3.38 3.43 3.25 3.45 3.35 3.33 3.42 3.38 3.40 3.33 3.32 3.38
# [43] 3.33 3.37 3.37 3.33 3.35 3.38 3.38 3.30 3.30 3.33 3.37 3.32 3.30 3.40
# [57] 3.37 3.42 3.30 3.37 3.38 3.32 3.45 3.38 3.37 3.50 3.33 3.40 3.28 3.37
# [71] 3.23 3.33 3.23 3.42 3.32 3.32 3.45 3.35 3.32 3.32 3.33 3.33 3.30 3.38
# [85] 3.37 3.33 3.33 3.20 3.37 3.33 3.30 3.40 3.40 3.32 3.33 3.37 3.40 3.38
# [99] 3.30 3.33
### Estimated average number of assays needed per pool
mean(foo)
# 3.35
### Estimated average number of assays needed per individual
mean(foo)/K
# [1] 0.67
``` |

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