Project description:We generated Multiome RNA+ATAC data from the same cell from human PBMC. This served as a gold benchmark for a novel integration method for multi-omics data that we developed.
Project description:We generated Multiome RNA+ATAC data from the same cell from human PBMC. This served as a gold benchmark for a novel integration method for multi-omics data that we developed.
Project description:Here, we performed multiome sequencing (snRNA-seq + snATAC-seq) of human fetal liver samples from 3 trisomy 21 (Ts21) and 3 healthy foetuses (median age 14 post-conception weeks). The data set is composed of approximately 60,000 CD45+ foetal liver cells.
Project description:This study used droplet-based snATAC-seq to profile the chromatin accessibility landscape of 91,922 nuclei in the mouse cerebellum across eleven developmental stages, from the beginning of neurogenesis (e10.5) till adulthood (P63). The study included two biological replicates per stage, one from each sex. Cerebelli were dissected as whole or in two halves, nuclei were extracted and profiled using 10x single-cell ATAC reagent kit (v1.0) and a Chromium controller. Libraries were sequenced using paired-reads on Illumina NextSeq 550 and initial data processing was performed using Cellranger ATAC (1.1).
Project description:Mouse retina is heterogeneous, composed of multiple neuronal and non-neuronal cell types. Among them, bipolar cells (BC), which connect photoreceptors (cones and rods) to inner retina, are traditionally dissected into rare subtypes of subtle functional and morphological differences. While high-resolution single-cell transcriptomic profiles of BCs are availabl, little is known about the corresponding single-cell chromatin landscapes. Although it is now possible to directly generate multiome data, there are often restrictions on cost, feasibility, and data quality. Therefore, integrating single-cell ATAC and RNA profiles obtained independently from the same retina sample may provide an exciting opportunity to comprehensively characterize these rare cell subtypes and discover transcription factors (TFs) important in establishing or maintaining the cell identities
Project description:Using Multiome and previously published sc/snRNA-seq data, we studied eight anatomical regions of the human heart including left and right ventricular free walls (LV and RV), left and right atria (LA and RA), left ventricular apex (AX), interventricular septum (SP), sino-atrial node (SAN) and atrioventricular node (AVN). For the first time, we profile the cells of the human cardiac conduction system, revealing their distinctive repertoire of ion channels, G-protein coupled receptors and cell-cell interactions. We map the identified cells to spatial transcriptomic data to discover cellular niches within the eight regions of the heart.