Multimodal single-cell chromatin analysis with Signac
Stuart, T.; Srivastava, A.; Lareau, C.; Satija, R.
Show abstract
The recent development of experimental methods for measuring chromatin state at single-cell resolution has created a need for computational tools capable of analyzing these datasets. Here we developed Signac, a framework for the analysis of single-cell chromatin data, as an extension of the Seurat R toolkit for single-cell multimodal analysis. Signac enables an end-to-end analysis of single-cell chromatin data, including peak calling, quantification, quality control, dimension reduction, clustering, integration with single-cell gene expression datasets, DNA motif analysis, and interactive visualization. Furthermore, Signac facilitates the analysis of multimodal single-cell chromatin data, including datasets that co-assay DNA accessibility with gene expression, protein abundance, and mitochondrial genotype. We demonstrate scaling of the Signac framework to datasets containing over 700,000 cells. AvailabilityInstallation instructions, documentation, and tutorials are available at: https://satijalab.org/signac/
Matching journals
The top 1 journal accounts for 50% of the predicted probability mass.
Similar papers in this journal
- Genome-wide nucleosome and transcription factor responses to genetic perturbations reveal chromatin-mediated mechanisms of transcriptional regulation 95%
- Identifying transcription factor-bound gene activators and silencers in the chromatin accessible human genome using ATAC-STARR-seq 95%
- Comprehensive characterization of tissue-specific chromatin accessibility in L2 Caenorhabditis elegans nematodes 95%
Similar papers in this journal
- Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data. 95%
- A genome-wide nucleosome-resolution map of promoter-centered interactions in human cells corroborates the enhancer-promoter looping model 95%
- Robust and annotation-free analysis of alternative splicing across diverse cell types in mice 93%
Similar papers in this journal
- preciseTAD: A transfer learning framework for 3D domain boundary prediction at base-pair resolution 95%
- A framework for summarizing chromatin state annotations within and identifying differential annotations across groups of samples 95%
- HiCLift: A fast and efficient tool for converting chromatin interaction data between genome assemblies 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.