runForeachLoop: The runForeachLoop function
In mpru/ConsensusClustering: An R Package for Consensus Clustering

Internal. Wrapper function to call foreach, to keep the code tidy.

1 2	runForeachLoop(nIters, propSamples, dataMatrix, K, clusterAlgorithm, verbose, seed)

`nIters`	number of iterations (bootstrap samples).
`propSamples`	proportion of items to sample in each bootstrap sample.
`dataMatrix`	matrix or data frame with data to cluster, samples/items in the columns and features in the rows.
`K`	vector of integers representing numbeer of clusters to evaluate. It can be of length 1 and it does not need to consist of consecutive integers. For example, either of `K = 4`, `K = 2:5` or `K = c(5, 10, 15)` would work.
`clusterAlgorithm`	algorithm to perform the clustering, for the moment only K-means is available.
`verbose`	logical, print progress messages to screen. During the bootstrap iterations, a report to monitor the progress is created in `pathOutput`.
`seed`	numerical value to set random seed for reproducible results. It uses `doRNG` package to guarantee reproducible results even when running in parallel.