Project description:A scalable, cost-effective method that combines CRISPR perturbations with a single-cell indexing assay for transposase-accessible chromatin (CRISPR-sciATAC). This method links genome-wide chromatin accessibility to genetic perturbations through simultaneous capture of ATAC-seq fragments and CRISPR guide RNAs from single cells using a 96-well plate combinatorial indexing approach.
Project description:We performed single-cell combinatorial indexing ATAC-seq on the basal-like TNBC cell line HCC1143 under MEK, PI3K, BET and combination treatments as well as DMSO controls
Project description:We report a high depth single-cell combinatorial indexing (sci-)ATAC-seq map of the murine hippocampus from fresh and frozen tissue as well as cultured neurons
Project description:We describe sciMET-ATAC, a combinatorial indexing-based technique that is capable of producing single-cell DNA methylation plus chromatin accessibility datasets.
Project description:Cell atlas projects and high-throughput perturbation screens require single-cell sequencing at a scale that is challenging with current technology. To enable cost-effective single-cell sequencing for millions of individual cells, we developed “single-cell combinatorial fluidic indexing” (scifi). The scifi-RNA-seq assay combines one-step combinatorial pre-indexing of entire transcriptomes inside permeabilized cells with subsequent single-cell RNA-seq using microfluidics. Pre-indexing allows us to load multiple cells per droplet and bioinformatically demultiplex their individual expression profiles. Thereby, scifi-RNA-seq massively increases the throughput of droplet-based single-cell RNA-seq, and it provides a straightforward way of multiplexing thousands of samples in a single experiment. Compared to multi-round combinatorial indexing, scifi-RNA-seq provides an easier, faster, and more efficient workflow. In contrast to cell hashing methods, which flag and discard droplets containing more than one cell, scifi-RNA-seq resolves and retains individual transcriptomes from overloaded droplets.
Project description:We developed a combinatorial indexing strategy to profile the transcriptomes of large numbers of single cells or nuclei (Single cell Combinatorial Indexing RNA-seq or sci-RNA-seq). We applied sci-RNA-seq to profile nearly 50,000 cells from C. elegans at the L2 stage, effectively ~56-fold “shotgun cellular coverage” of its somatic cell composition.
