Tutorial Three: In this section we will focus on differential peak identification, motif footprinting, and annotation of nearby genomic features. Workflow for sc-ATAC Sequencing (submodule 4). Tutorial Four: In this section we will demonstrate a single cell ATAC-Seq analysis workflow. GCP Architectu...
Single-cell RNA sequencing (scRNA-seq) technologies allow the dissection of gene expression at single-cell resolution, which improves the detection of known and novel cell types and the understanding of cell-specific molecular processes [1, 2]. The extension of the basic scRNA-seq technology with...
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc. - seandavi/awesome-single-cell
The purpose of cell QC is to make sure all the ‘cells’ being analyzed are single and intact cells. Damaged cells, dying cells, stressed cells and doublets need to be discarded [57,58]. In ultrahigh-throughput scRNA-seq, quantitative metrics used for bulk RNA-seq QC, including read mappa...
Benchmarking single-cell RNA-seq (scRNA-seq) and single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) computational tools demands simulators to generate realistic sequencing reads. However, none of the few read simulators
A major drawback of single-cell ATAC-seq (scATAC-seq) is its sparsity, i.e., open chromatin regions with no reads due to loss of DNA material during the scATAC-seq protocol. Here, we propose scOpen, a computational method based on regularized non-negative matrix factorization for imputing ...
awesome-single-cell List of software packages (and the people developing these methods) for single-cell data analysis, including RNA-seq, ATAC-seq, etc.Contributions welcome... Software packages RNA-seq anchor- [Python] - ⚓ Find bimodal, unimodal, and multimodal features in your data ...
ArchR is a full-featured R package for processing and analyzing single-cell ATAC-seq data. ArchR provides the most extensive suite of scATAC-seq analysis tools of any software available. Additionally, ArchR excels in both speed and resource usage, making it possible to analyze 1 million cells ...
Single-cell chromatin accessibility assays, such as scATAC-seq, are increasingly employed in individual and joint multi-omic profiling of single cells. As the accumulation of scATAC-seq and multi-omics datasets continue, challenges in analyzing such spar
Sequence-based Modeling of single-cell ATAC-seq using Convolutional Neural Networks. scBasset is a sequence-based convolutional neural network method to model single cell ATAC-seq data. We show that by leveraging the DNA sequence information underlying accessibility peaks and the expressiveness of a ...