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Published on: August 10, 2017
A concise guide to essential R packages for analyses of DNA, RNA, and proteins
Eng Wee Chua1, Der Jiun Ooi2, Nor Azlan Nor Muhammad3
1Centre for Drug and Herbal Development, Faculty of Pharmacy, Universiti Kebangsaan Malaysia, 50300 Kuala Lumpur, Malaysia.
Abstract:
R is widely regarded as unrivaled by other high-level programming languages for its statistical functions. The popularity of R as a statistical language has led many to overlook its applications outside the statistical realm. In this brief review, we present a list of R packages for supporting projects that entail analyses of DNA, RNA, and proteins. These R packages span the gamut of important molecular techniques, from routine quantitative polymerase chain reaction (qPCR) and Western blotting to high-throughput sequencing and proteomics generating very large datasets. The text-mining power of R can also be harnessed to facilitate literature reviews and predict future research trends and avenues. We encourage researchers to make full use of R in their work, given the versatility of the language, as well as its straightforward syntax which eases the initial learning curve.
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