Tim Kosfeld will present his MSE thesis "Supervised linear modeling and integration of ATAC-seq" on Monday, April 27th, 2026 in Bendheim House 103 at 10:30am. Advisor: Yuri Pritykin Reader: Ben Raphael All are welcome to attend. Abstract: Single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq) has been widely used to profile chromatin accessibility and explore the epigenomic properties in heterogeneous cell populations. Moreover, transcription factors (TFs) bind to accessible sites, and scATAC-seq analysis could associate TF binding specificities, typically available as sequence motifs, with variance in chromatin accessibility. Here we present a new supervised TF motif regression method, MotifReg, for computational analysis and interpretation of scATAC-seq data. We comprehensively compare MotifReg with other popular methods for motif and sequence analysis in scATAC-seq data and demonstrate superior performance and benefits of MotifReg. MotifReg can efficiently analyze large-scale scATAC-seq datasets and learn interpretable associations between TF motifs and accessible peaks. The resultant low-dimensional cell representations in the TF activity space facilitate downstream cell type-specific analyses of scATAC-seq data. The supervised formulation in MotifReg enables ranking TF motifs by significance of their association with chromatin accessibility, implicating cell type-specific TFs. Furthermore, by comparing MotifReg performance across data analysis settings, we develop guidelines and best practices for scATAC-seq peak calling, data preprocessing and normalization. In sum, MotifReg is a convenient and statistically sound new open source computational method for scATAC-seq data analysis and characterization of genome-wide TF activities.