My Experience with Single Cell RNA Seq Analysis Courses I recently embarked on a quest to find a suitable course for single cell RNA seq analysis My main goal was to efficiently examine my data without struggling too much on the software side, as I had a project deadline looming
Practical bioinformatics pipelines for single-cell RNA-seq . . . We detail the steps of a typical scRNA-seq analysis, including experimental design, pre-processing and quality control, feature selection, dimensionality reduction, cell clustering and annotation, and downstream analysis including batch correction, trajectory inference and cell–cell communication
Overcoming Bioinformatics Skill Gaps in Single-Cell Research This article addresses the bioinformatics skill gap in single-cell research, highlighting challenges faced by wet-lab scientists in analyzing scRNA-seq data It explores solutions to make data analysis more accessible to researchers without extensive computational expertise
Mastering Single Cell RNA-Seq Data Analysis: From Novice to . . . This learning journey empowers you to enhance your confidence and skills in analyzing single-cell RNA-seq data, deriving meaningful insights, and contributing more effectively to your research projects
A beginners guide to building confidence in single cell RNA-seq What is single cell RNA-seq? What can single cell do for my research? What are the advantages of single cell RNA-seq? How can single cell enhance my research without added complexity or cost? What single cell assays are available from 10x? What more can I learn?
Single-Cell RNA Sequencing Analysis: A Step-by-Step Overview Here we provide an overview of the currently available single-cell technologies for cell isolation and library preparation and a step by step guide that covers the entire canonical analytic workflow to analyse scRNA-seq data including read mapping, quality controls, gene expression quantification, normalization, feature selection
A practical guide to single-cell RNA-sequencing for . . . In this review, we present a practical guide to help researchers design their first scRNA-seq studies, including introductory information on experimental hardware, protocol choice, quality control, data analysis and biological interpretation