RNA sequencing is a cornerstone of modern transcriptomics, yet its accuracy is fundamentally challenged by biases introduced during library preparation.
Bulk RNA-seq is a cornerstone of modern transcriptomics, yet its accuracy hinges on appropriate data normalization to overcome significant technical biases.
Low mapping rates in RNA-seq analysis present a significant challenge that can compromise the validity of transcriptomic studies, from basic research to clinical applications.
This article provides a comprehensive, decision-oriented guide to RNA-seq quality control using FastQC and Trimmomatic, tailored for researchers and drug development professionals.
Batch effects represent one of the most significant technical challenges in bulk RNA-sequencing analysis, capable of obscuring true biological signals and leading to irreproducible findings.
This article provides a comprehensive guide for researchers and drug development professionals on determining optimal sequencing depth and read length for bulk RNA-Seq experiments.
This article provides a complete framework for understanding, troubleshooting, and correcting RNA degradation in bulk RNA-seq experiments.
This article provides a comprehensive guide to RNA sequencing library preparation, a critical step that profoundly impacts data quality and biological interpretation.
This article provides a comprehensive overview of allele-specific expression (ASE) analysis using RNA sequencing (RNA-seq), a powerful approach for identifying cis-regulatory variation with significant implications for genetics, disease research, and...
This article provides a comprehensive guide for researchers and bioinformaticians on addressing batch effects in bulk RNA-sequencing data.