I am starting to analyze publicly available ATAC seq data sets. Does anyone have any suggestions as to how to go about this? Any suggested reading, GitHub pages or tutorials are welcome!
Krishnapriya Vinod wonderful to see your interest in this powerful epigenomics technique! Analyzing public ATAC-seq datasets is an excellent way to learn best practices. Here are some recommendations to get started:
- The ENCODE project portal hosts many quality ATAC-seq datasets with metadata on cell types, experimental variables, etc. Helpful for grasping real-world applications.
- Cromwell lab’s ATAqv software is a popular ATAC-seq data quality control and visualization toolkit. Good first step.
- Kent Riemondy’s lectures on YouTube provide accessible introductions to ATAC-seq computational analysis methods and concepts.
- Kundaje lab’s ATAC-seq training notebooks walk through data loading, peak calling, motif analysis, visualization, and more using Python. Very hands-on.
- Tsang lab’s resources including R tutorials on analyzing epigenomics data with a focus on reproducibility and rigor.
I’d be happy to demonstrate analysis on a sample dataset to provide orientation. Feel free to reach out with any questions! Wishing you all the best advancing skills in this dynamic field. The future holds much promise for leveraging epigenomic insights in sha Allah.
Thank you so much. I shall start and get back in case it gets stuck. I really appreciate this
- Badges
- Science topic
- Similar topics
- Methodology
- Research Methodology
- Research Papers