Integrative analysis of ATAC-seq and RNA-seq for cells infected by human T-cell leukemia virus type 1.

Human T-cell leukemia virus type 1 (HTLV-1) causes adult T-cell leukemia (ATL) and HTLV-1-associated myelopathy (HAM) after a long latent period in a fraction of infected individuals. These HTLV-1-infected cells typically have phenotypes similar to that of CD4+T cells, but the cell status is not well understood. To extract the inherent information of HTLV-1-infected CD4+ cells, we integratively analyzed the ATAC-seq and RNA-seq data of the infected cells.

Emergent centrality in rank-based supplanting process.

We propose a stochastic process of interacting many agents, which is inspired by rank-based supplanting dynamics commonly observed in a group of Japanese macaques. In order to characterize the breaking of permutation symmetry with respect to agents' rank in the stochastic process, we introduce a rank-dependent quantity, overlap centrality, which quantifies how often a given agent overlaps with the other agents. We give a sufficient condition in a wide class of the models such that overlap centrality shows perfect correlation in terms of the agents' rank in the zero-supplanting limit.

Systematic clustering algorithm for chromatin accessibility data and its application to hematopoietic cells.

The huge amount of data acquired by high-throughput sequencing requires data reduction for effective analysis. Here we give a clustering algorithm for genome-wide open chromatin data using a new data reduction method. This method regards the genome as a string of 1s and 0s based on a set of peaks and calculates the Hamming distances between the strings.