The key programming language used in the field of data science is R programming, because of the free availability and ability to handle huge data. Packages developed in the R are used widely by scientists to obtain solutions for various real-world problems in several disciplines like healthcare, agriculture, and information technology. Next-generation sequencing data requires various bioinformatics analyses like quality checking, differential gene expression studies, and annotation which is facilitated by R packages and software. Bioconductorprojectremains a hub of R packages that are open access and move the researchers to the comfort zone for various kinds of analysis. In this review, we briefly discussed various packages useful for NGS data analysis and also explained how to use the packages for basic level analysis that benefits researchers having less exposure to R programming.
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