pooling_mc: Monte Carlo Simulation for Estimating the Number of Assays...
In taotliu/mMPA: Implementation of Marker-Assisted Mini-Pooling with Algorithm

Description Usage Arguments Value References See Also Examples

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; `s` must be provided if `method = "mmpa"` and have the same length as `v`. The risk score `s` needs to be positively associated with `v`; othewise an error message will be generated.
`K`	Pool size; default is `K = 5`.
`vf_cut`	Cutoff value for defining positive cases; default is `vf_cut = 1000`.
`lod`	A vector of lower limits of detection or a scalar if the limits are the same; default is `lod = 0`.
`method`	Method that is used for pooled testing; must be one of `minipool`, `mpa`, and `mmpa`. By default, `method = "mmpa"`.
`perm_num`	The number of permutation to be used for the calculation; default is `100`.
`msg`	Message generated during calculation; default is `FALSE`.

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).

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.

Our manuscript; to be added.

minipool, mpa, mmpa

### 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