ATAC-seq Data Analysis and Quality Control
ATAC-seq is the most current method for probing chromatin accesibility. However, due to its relative novelty, little research has been done into how ATAC-seq data analysis should be conducted. I am currently investigating and developing data analysis pipelines for ATAC-seq in order to give a better understanding of what information this data gives us and its possible implications.
Transcription Factor Footprinting
During Drosophila development, cells from distinct imaginal discs (wing, leg, haltere) have seemingly identical open chromatin profiles at the same time point. This is surprising due to these cells resulting in very different structures. Thus, I am interested in ways of viewing chromatin accessibility at higher resolutions to see if these profiles are, in fact, identical. Specifically, I am using de novo transcription factor footprinting with ATAC-seq data to find if subtle differences in DNA-binding protein interactions could reveal insight into how these cells differentiate.
Directed by Dr. David Gotz, I built software prototypes for new data visualization and analysis methods developed by the Visual Analysis and Communication Laboratory (VACLab).
David Gotz, Brandon A. Price, Annie Chen. Visual Model validation via Inline Replication. Submitted to IEEE Visual Analytics Science and Technology (2015)