Standardized Methods for Transcriptomic Analysis

TOPICAL COLLECTIONS

Guest Editors

Yao Geng

The First Affiliated Hospital with Nanjing Medical University

Yao Geng holds a master’s degree in neurology and is currently a physical therapist at the Rehabilitation Medicine Center of Jiangsu Provincial People’s Hospital in China. He also serves as the deputy secretary of the Youth League Committee within the Surgery Department of the same hospital. Regarding academic research, he has published several papers as either the first author or corresponding author, focusing on neural mechanisms and transcriptomics.

Ying Shen

The First Affiliated Hospital with Nanjing Medical University

Professor Ying Shen holds a Doctor of Medicine and serves as the deputy director of the Rehabilitation Medicine Department at the First Affiliated Hospital of Nanjing Medical University in China. He is also the director of the Physical Therapy Department at the Rehabilitation Medical College. Professor Shen has published over 50 papers as the first or corresponding author, including four papers in journals with an impact factor exceeding 10. His research primarily focuses on the mechanisms underlying neurological diseases and bioinformatics.

Kezhong Zhang

The First Affiliated Hospital with Nanjing Medical University

Professor Kezhong Zhang, PhD, is the director of the Department of Neurology at the First Affiliated Hospital of Nanjing Medical University in China. His expertise includes neurological diagnosis and treatment, as well as research on disease mechanisms and bioinformatics. He has published more than 80 academic papers to date.

Collection Overview

Transcriptomic analysis is fundamental to understanding gene expression dynamics across biological processes, disease mechanisms, and therapeutic development. However, rapid technological evolution (e.g., single-cell, spatial, long-read sequencing) and fragmented analytical pipelines challenge reproducibility and cross-study comparison, hindering scientific progress.

This Methods Collection aims to curate authoritative, standardized protocols and analytical workflows for the full transcriptomics lifecycle—from experimental design and library preparation to computational analysis and interpretation. Each method will be rigorously validated, benchmarked, and include open-source code/parameters.

This collection supports the research community in the following ways:

Improving reproducibility through carefully vetted, step-by-step guidelines that reduce technical variability
Accelerating the adoption of emerging technologies, such as spatial transcriptomics, by making best practices readily accessible.
Fostering collaboration through standardized outputs that allow for smooth data integration and meta-analyses.
Minimizing resource waste by addressing inefficiencies in experimental pipeline development.