1 research outputs found
RNA-seq data science: From raw data to effective interpretation
RNA-sequencing (RNA-seq) has become an exemplar technology in modern biology
and clinical applications over the past decade. It has gained immense
popularity in the recent years driven by continuous efforts of the
bioinformatics community to develop accurate and scalable computational tools.
RNA-seq is a method of analyzing the RNA content of a sample using the modern
sequencing platforms. It generates enormous amounts of transcriptomic data in
the form of nucleotide sequences, known as reads. RNA-seq analysis enables the
probing of genes and corresponding transcripts which is essential for answering
important biological questions, such as detecting novel exons, transcripts,
gene expressions, and studying alternative splicing structure. However,
obtaining meaningful biological signals from raw data using computational
methods is challenging due to the limitations of modern sequencing
technologies. The need to leverage these technological challenges have pushed
the rapid development of many novel computational tools which have evolved and
diversified in accordance with technological advancements, leading to the
current myriad population of RNA-seq tools. Our review provides a systemic
overview of RNA-seq technology and 235 available RNA-seq tools across various
domains published from 2008 to 2020, discussing the interdisciplinary nature of
bioinformatics involved in RNA sequencing, analysis, and software development