baRcodeR: An open-source R package for sample labelling

Yihan Wu

doi:10.1111/2041-210X.13405

baRcodeR: An open-source R package for sample labelling

2020-06-22

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DOI：10.1111/2041-210X.13405

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Repeatable experiments with accurate data collection and reproducible analyses are fundamental to the scientific method but may be difficult to achieve in practice. Open-source tools aid the reproducibility of data analysis, but analogous tools are generally lacking for sample collection and other early stages of scientific inquiry. We introduce the R packagebaRcodeRfor generating informative identifier (ID) codes with digitally encoded linear or 2D barcodes. Codes can be imported from an existing dataset (e.g. CSV file) or generated rapidly inbaRcodeR, producing scannable barcodes with customizable page layouts for printing and scanning with consumer-grade printers and scanners. User-defined ID codes may contain a simple sequence (e.g.SAMPLE-0427) or encode more meaningful sample information such as individual subjects, treatment groups, sample populations, time points, spatial coordinates, subsamples or other associations (e.g.Pop22-Ind08-Time40). In addition to command-line functions, a graphical-user-interface (GUI) is available from the 'Addins' menu of R Studio or online at to assist with ID code and barcode label creation. baRcodeRcan help biologists apply principles of open and reproducible science to collect and manage biological samples.

Keyword:

asset tracking

barcodes

biological samples

QR codes

reproducible science

baRcodeR: An open-source R package for sample labelling

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