Single-cell ATAC-seq signal extraction and enhancement with SCATE
نویسندگان
چکیده
منابع مشابه
Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes.
OBJECTIVE Although glucagon-secreting α-cells and insulin-secreting β-cells have opposing functions in regulating plasma glucose levels, the two cell types share a common developmental origin and exhibit overlapping transcriptomes and epigenomes. Notably, destruction of β-cells can stimulate repopulation via transdifferentiation of α-cells, at least in mice, suggesting plasticity between these ...
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Assay for Transposase Accessible Chromatin (ATAC-seq) is an open chromatin profiling assay that is adapted to interrogate chromatin accessibility from small cell numbers. ATAC-seq surmounted a major technical barrier and enabled epigenome profiling of clinical samples. With this advancement in technology, we are now accumulating ATAC-seq samples from clinical samples at an unprecedented rate. T...
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This unit describes Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq), a method for mapping chromatin accessibility genome-wide. This method probes DNA accessibility with hyperactive Tn5 transposase, which inserts sequencing adapters into accessible regions of chromatin. Sequencing reads can then be used to infer regions of increased accessibility, as well as...
متن کاملCombining ATAC-seq with nuclei sorting for discovery of cis-regulatory regions in plant genomes
Chromatin structure plays a pivotal role in facilitating proper control of gene expression. Transcription factor (TF) binding of cis-elements is often associated with accessible chromatin regions. Therefore, the ability to identify these accessible regions throughout plant genomes will advance understanding of the relationship between TF binding, chromatin status and the regulation of gene expr...
متن کاملNonparanormal Distributions & Causal Inference with Single-Cell RNA-Seq Data
Background. Single-cell RNA-Seq is a new technique that can measure gene expression levels in individual cells. We would like to use single-cell RNA-seq data to learn genetic regulatory networks. This is a natural task for causal-model structurelearning algorithms, which aim to learn the causal relationships between the measured variables. Causal algorithms perform poorly in high dimensions unl...
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ژورنال
عنوان ژورنال: Genome Biology
سال: 2020
ISSN: 1474-760X
DOI: 10.1186/s13059-020-02075-3