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Passing in Command Line Arguments and Parallel Cluster/Multicore Batching in R with batch.

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|November 29, 2014
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Summary
This summary is machine-generated.

The R package batch simplifies running R scripts with varied parameters and enables parallel processing across clusters or local machines. It also facilitates aggregating results from these parallel computations for efficient workflow management.

Keywords:
Rbatchclustercommand line argumentsparallel

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Data Science

Background:

  • R scripts often require re-execution with modified parameters for simulations or data processing.
  • Managing multiple runs and parallel computations can be complex and time-consuming.

Purpose of the Study:

  • To introduce the R package batch for streamlined command-line R script execution.
  • To facilitate easy parameter passing, including vectors, into R scripts.
  • To simplify parallel batch processing and result aggregation.

Main Methods:

  • The batch package allows passing multiple command-line options directly into R scripts.
  • It supports parallel execution by distributing script runs across cluster or multicore systems using R-like syntax.
  • Automated syntax for popular cluster types is included.

Main Results:

  • Users can efficiently rerun R scripts with varying parameters.
  • Parallel execution of R scripts on distributed systems is simplified.
  • Automated aggregation of results from multiple parallel processes is provided.

Conclusions:

  • The batch package offers a robust solution for managing and executing R scripts in batch mode.
  • It enhances computational efficiency by simplifying parameter management and parallel processing.
  • This package is valuable for researchers and data scientists working with R.