GenoGAM

GenoGAM is a statistical modeling tool for analyzing ChIP-Seq data with flexible factorial design experiments. However, its previous implementation had large runtime and memory requirements, making it impractical for gigabase-scale genomes. GenoGAM 2.0 is a scalable and efficient implementation that is 2 to 3 orders of magnitude faster than the previous version, achieved by exploiting the sparsity of the model and using the SuperLU direct solver for parameter fitting, and sparse Cholesky factorization and the sparse inverse subset algorithm for computing standard errors. Whole-genome fits for human ChIP-seq datasets could be obtained in less than 9 hours on a standard 60-core server. GenoGAM 2.0 is implemented as an open-source R package and could be used in all types of organisms. Additionally, the algorithmic improvements made for fitting large GAMs may be useful to the statistical community beyond genomics.