Single RNA-Seq Transcriptome Data Used for Retrieving Diverse Molecular Functions

RNA sequencing and microarray methods, which produce RNA from plant or animal tissue and transform it into complementary DNA (cDNA) to construct a sequencing library, are the methods used to produce transcriptome data. Transcriptome (RNA-seq) data is used for various molecular functions. Many bioinformatics tools and techniques have been developed for transcriptome data analysis and retrieving more than ten functional information. This review paper describes almost all possible tools that are used to gain scientific knowledge from a single transcriptome (RNA-seq) data analysis, including data collection from the public domain, quality control, read alignment and count, differential gene or transcript isoform expression, hub genes, specific gene identification like transcription factor, CAZyme, resistance genes, alternatively spliced genes, protein-protein interaction, pathway analysis, or functional analysis. Furthermore, non-coding RNA identifications, alternative polyadenylation, and transposable elements can be identified from transcriptome data. We highlighted all challenges and came to proceed with the steps of tools. In conclusion, we discuss the viewpoint for new analysis and technologies that are fluctuating to retrieve information from single transcriptome data.