A hitchhiker's guide to single-cell transcriptomics and data analysis pipelines.

A hitchhiker's guide to single-cell transcriptomics and data analysis pipelines.
Genomics. 2021 Jan 21;:
Authors: Nayak R, Hasija Y
Abstract
Single-cell transcriptomics (SCT) is a tour de force in the era of big omics data that has led to the accumulation of massive cellular transcription data at an astounding resolution of single cells. It provides valuable insights into cells previously unachieved by bulk cell analysis and is proving crucial in uncovering cellular heterogeneity, identifying rare cell populations, distinct cell-lineage trajectories, and mechanisms involved in complex cellular processes. SCT data is highly complex and necessitates advanced statistical and computational methods for analysis. This review provides a comprehensive overview of the steps in a typical SCT workflow, starting from experimental protocol to data analysis, deliberating various pipelines used. We discuss recent trends, challenges, machine learning methods for data analysis, and future prospects. We conclude by listing the multitude of scRNA-seq data applications and how it shall revolutionize our understanding of cellular biology and diseases.
PMID: 33485955 [PubMed - as supplied by publisher]

Source: Genomics - January 21, 2021 Category: Genetics & Stem Cells Authors: Nayak R, Hasija Y Tags: Genomics Source Type: research