Dhanalakshmi Jothi

In RNA-seq workflows, hidden batch effects, technical noise, or unknown sources of variation can silently degrade downstream analyses, leading to weaker PCA separation, misleading trajectories, and less reliable signal detection. We have developed a web-based preprocessing tool for bulk RNA-seq datasets that improves data quality and reduces technical variation, helping researchers achieve more reliable downstream results. We are inviting researchers, students, and labs to pilot this tool. Participants can: Test preprocessing on a small sample of their data Observe improvements in PCA clustering and trajectory analyses Receive a concise summary of the preprocessing results and resulting images can be used for publications No setup or full data upload is required. The pilot can be explored in a short 15–20 minute session, and a summary slide deck can be provided for convenience. If you are interested in improving RNA-seq data quality and exploring the potential of AI-assisted preprocessing, please reach out to schedule a session. Contact: dhana@feedai.bio, Dhanalakshmi Jothi, PhD (FSU Jena, Germany)