Trailmaker is a flexible, user-friendly tool that supports a wide range of single cell RNA sequencing analysis workflows, whether you’re starting from scratch or integrating with existing pipelines.
With Trailmaker, both wet-lab scientists and bioinformaticians are empowered to streamline their single cell analysis from data upload to visualization through an intuitive, collaborative platform.
To keep up with the complexity of immune research, newer single cell technologies like combinatorial barcoding offer a robust alternative to droplet-based techniques.
Single cell RNA sequencing is transforming cancer research by uncovering hidden complexities like drug resistance and tumor heterogeneity, highlighting the need for continued innovation to outpace cancer’s evolution and improve patient outcomes.
With the development of new multi-omics technologies, researchers can explore new avenues for therapeutic interventions and precision medicine in cancer research.
As the scientific community faces challenges such as funding uncertainty and policy changes, we remember to look to history, proving that science has always thrived in uncertainty. Even in the face of setbacks, it endures through those who keep asking questions.
Discover how single-cell RNA sequencing is transforming drug development, reducing costs and timelines while improving success rates. Learn about the latest breakthroughs in pharmaceutical research.
Learn key steps and best practices for analyzing single cell RNA-sequencing data with meaningful insights from processing FASTQ files to thorough quality control checks and addressing batch effects.
Best practices and considerations for library preparation for single cell, library sequencing, and sequencing quality control (QC). Learn about the proper methods to help maximize data quality and effectively address complex biological questions.
Key considerations for single-cell RNA-seq design: applications, challenges, and practical tips. Learn to prepare cell/nuclei suspensions from diverse samples for optimal scRNA-seq results.