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