A Critical Approach to R Programming in the Analysis of lncRNA in Bioinformatics Study

Abstract

Bioinformatics is a multidisciplinary field of scientific research which analyse biological data using computer science knowledge. Bioinformatics is normally used in laboratories for wet lab practices. This field of study covers genomics, proteomics, and metabolomics. Each of these deals with various databases created by world-famous organizations like NCBI, EMBL, etc. Various levels of students, Academicians, Corporate people extract information from well-known databases like ENA, Ensembl, UniProt, PDB, etc. Depending on requirements the extracted data need to be transformed for analysis and Graph Plotting. Based on the analytics and graphical results, scientists and researchers draw a conclusion or take critical decisions to establish certain biological facts. Now extraction of biological data from gigantic biological databases is a humongous task. It requires a very efficient tool that will not only extract information but also provide data analytics and graph plotting amenities. There are numerous programming tools available in the technological domain with their weaknesses and strengths. For example language tools like C, C++, Perl, Ruby, JavaScript or PHP, Java, R, Python, Bash, etc. Researchers in bioinformatics are broadly divided into two groups: the first one who doesn’t want to make their own software and the others who do. Both will do data analysis; execute statistical tests, draws plots and use bioinformatics software made by other programmers. But the second group might be interested in writing their own scripts or build software for their own use or to help other researchers. For me, R programming will be the best choice for both of the mentioned groups. Because it has an ample collection of biological packages that support deep analysis of lncRNA in the field of Bioinformatics study.