scholarly journals simATAC: A Single-cell ATAC-seq Simulation Framework

2020 ◽  
Author(s):  
Zeinab Navidi Ghaziani ◽  
Lin Zhang ◽  
Bo Wang
Keyword(s):  
Single Cell ◽  
In Silico ◽  
Systematic Approach ◽  
R Package ◽  
Chromatin Accessibility ◽  
Simulation Framework ◽  
Library Size ◽  
Cell Groups ◽  
Accessible Chromatin ◽  
Statistical Functions

Single-cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) identifies regulated chromatin accessibility modules at the single-cell resolution. Robust evaluation is critical to the development of scATAC-seq pipelines, which calls for reproducible datasets for benchmarking. We hereby present the simATAC framework, an R package that generates a scATAC-seq count matrix, highly resembling real scATAC-seq datasets in library size, sparsity, and averaged chromatin accessibility signals. simATAC deploys statistical functions derived from analyzing 90 real scATAC-seq cell groups to model read distributions. simATAC provides a robust and systematic approach to generate in silico scATAC-seq samples with cell labels for a comprehensive tool assessment.

scholarly journals simATAC: a single-cell ATAC-seq simulation framework

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zeinab Navidi ◽  
Lin Zhang ◽  
Bo Wang
Keyword(s):  
Single Cell ◽  
Statistical Models ◽  
In Silico ◽  
Systematic Approach ◽  
R Package ◽  
Chromatin Accessibility ◽  
Simulation Framework ◽  
Library Size ◽  
Cell Groups ◽  
Accessible Chromatin

AbstractSingle-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) identifies regulated chromatin accessibility modules at the single-cell resolution. Robust evaluation is critical to the development of scATAC-seq pipelines, which calls for reproducible datasets for benchmarking. We hereby present the simATAC framework, an R package that generates scATAC-seq count matrices that highly resemble real scATAC-seq datasets in library size, sparsity, and chromatin accessibility signals. simATAC deploys statistical models derived from analyzing 90 real scATAC-seq cell groups. simATAC provides a robust and systematic approach to generate in silico scATAC-seq samples with known cell labels for assessing analytical pipelines.

scholarly journals Destin: toolkit for single-cell analysis of chromatin accessibility

2019 ◽  
Vol 35 (19) ◽  
pp. 3818-3820 ◽  
Author(s):  
Eugene Urrutia ◽  
Li Chen ◽  
Haibo Zhou ◽  
Yuchao Jiang
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
New Technology ◽  
R Package ◽  
Chromatin Accessibility ◽  
Supplementary Information ◽  
Cell Type ◽  
Statistical Framework ◽  
Specific Association ◽  
Accessible Chromatin

Abstract Summary Single-cell assay of transposase-accessible chromatin followed by sequencing (scATAC-seq) is an emerging new technology for the study of gene regulation with single-cell resolution. The data from scATAC-seq are unique—sparse, binary and highly variable even within the same cell type. As such, neither methods developed for bulk ATAC-seq nor single-cell RNA-seq data are appropriate. Here, we present Destin, a bioinformatic and statistical framework for comprehensive scATAC-seq data analysis. Destin performs cell-type clustering via weighted principle component analysis, weighting accessible chromatin regions by existing genomic annotations and publicly available regulomic datasets. The weights and additional tuning parameters are determined via model-based likelihood. We evaluated the performance of Destin using downsampled bulk ATAC-seq data of purified samples and scATAC-seq data from seven diverse experiments. Compared to existing methods, Destin was shown to outperform across all datasets and platforms. For demonstration, we further applied Destin to 2088 adult mouse forebrain cells and identified cell-type-specific association of previously reported schizophrenia GWAS loci. Availability and implementation Destin toolkit is freely available as an R package at https://github.com/urrutiag/destin. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Destin: toolkit for single-cell analysis of chromatin accessibility

2018 ◽  
Author(s):  
Eugene Urrutia ◽  
Li Chen ◽  
Haibo Zhou ◽  
Yuchao Jiang
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
New Technology ◽  
R Package ◽  
Chromatin Accessibility ◽  
Data Sets ◽  
Cell Type ◽  
Statistical Framework ◽  
Specific Association ◽  
Accessible Chromatin

AbstractSummarySingle-cell assay of transposase-accessible chromatin followed by sequencing (scATAC-seq) is an emerging new technology for the study of gene regulation with single-cell resolution. The data from scATAC-seq are unique sparse, binary, and highly variable even within the same cell type. As such, neither methods developed for bulk ATAC-seq nor single-cell RNA-seq data are appropriate. Here, we present Destin, a bioinformatic and statistical framework for comprehensive scATAC-seq data analysis. Destin performs cell-type clustering via weighted principle component analysis, weighting accessible chromatin regions by existing genomic annotations and publicly available regulomic data sets. The weights and additional tuning parameters are determined via model-based likelihood. We evaluated the performance of Destin using downsampled bulk ATAC-seq data of purified samples and scATAC-seq data from seven diverse experiments. Compared to existing methods, Destin was shown to outperform across all data sets and platforms. For demonstration, we further applied Destin to 2,088 adult mouse forebrain cells and identified cell type-specific association of previously reported schizophrenia GWAS loci.AvailabilityDestin toolkit is freely available as an R package at https://github.com/urrutiag/[email protected].

scholarly journals Diversification of reprogramming trajectories revealed by parallel single-cell transcriptome and chromatin accessibility sequencing

2020 ◽  
Vol 6 (37) ◽  
pp. eaba1190
Author(s):  
Q. R. Xing ◽  
C. A. El Farran ◽  
P. Gautam ◽  
Y. S. Chuah ◽  
T. Warrier ◽  
...  
Keyword(s):  
Single Cell ◽  
Chromatin Accessibility ◽  
Human Cells ◽  
Cellular Reprogramming ◽  
Surface Markers ◽  
Low Efficiency ◽  
Cell Transcriptome ◽  
Intermediate Cells ◽  
Single Cell Transcriptome ◽  
Accessible Chromatin

Cellular reprogramming suffers from low efficiency especially for the human cells. To deconstruct the heterogeneity and unravel the mechanisms for successful reprogramming, we adopted single-cell RNA sequencing (scRNA-Seq) and single-cell assay for transposase-accessible chromatin (scATAC-Seq) to profile reprogramming cells across various time points. Our analysis revealed that reprogramming cells proceed in an asynchronous trajectory and diversify into heterogeneous subpopulations. We identified fluorescent probes and surface markers to enrich for the early reprogrammed human cells. Furthermore, combinatory usage of the surface markers enabled the fine segregation of the early-intermediate cells with diverse reprogramming propensities. scATAC-Seq analysis further uncovered the genomic partitions and transcription factors responsible for the regulatory phasing of reprogramming process. Binary choice between a FOSL1 and a TEAD4-centric regulatory network determines the outcome of a successful reprogramming. Together, our study illuminates the multitude of diverse routes transversed by individual reprogramming cells and presents an integrative roadmap for identifying the mechanistic part list of the reprogramming machinery.

scholarly journals Enhancement and Imputation of Peak Signal Enables Accurate Cell-Type Classification in scATAC-seq

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhe Cui ◽  
Ya Cui ◽  
Yan Gao ◽  
Tao Jiang ◽  
Tianyi Zang ◽  
...  
Keyword(s):  
Single Cell ◽  
Mononuclear Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Support Vector ◽  
Cell Type ◽  
Peripheral Blood Mononuclear ◽  
Copy Numbers ◽  
Genome Wide ◽  
Accessible Chromatin

Single-cell Assay Transposase Accessible Chromatin sequencing (scATAC-seq) has been widely used in profiling genome-wide chromatin accessibility in thousands of individual cells. However, compared with single-cell RNA-seq, the peaks of scATAC-seq are much sparser due to the lower copy numbers (diploid in humans) and the inherent missing signals, which makes it more challenging to classify cell type based on specific expressed gene or other canonical markers. Here, we present svmATAC, a support vector machine (SVM)-based method for accurately identifying cell types in scATAC-seq datasets by enhancing peak signal strength and imputing signals through patterns of co-accessibility. We applied svmATAC to several scATAC-seq data from human immune cells, human hematopoietic system cells, and peripheral blood mononuclear cells. The benchmark results showed that svmATAC is free of literature-based markers and robust across datasets in different libraries and platforms. The source code of svmATAC is available at https://github.com/mrcuizhe/svmATAC under the MIT license.

scholarly journals Terminal selectors organize postmitotic chromatin accessibility for acquisition of serotonergic identity

2021 ◽  
Author(s):  
Xinrui L Zhang ◽  
William C Spencer ◽  
Nobuko Tabuchi ◽  
Evan S Deneris
Keyword(s):  
Single Cell ◽  
Chromatin Accessibility ◽  
Open Chromatin ◽  
Regulatory Sequences ◽  
Early Maturation ◽  
Accessible Chromatin

Assembly of transcriptomes encoding unique neuronal identities requires selective accessibility of regulatory inputs to cis-regulatory sequences in nucleosome-embedded chromatin. Yet the mechanisms involved in shaping postmitotic neuronal chromatin are poorly understood. Here we used ATAC-seq, ChIPmentation, and single-cell analyses to show that unique distal enhancers and super-enhancers define the Pet1 neuron lineage that generates serotonin (5-HT) neurons. Heterogeneous single cell chromatin landscapes are established early in postmitotic Pet1 neurons and reveal the regulatory programs driving Pet1 neuron subtype identities. Terminal selectors, Pet1 and Lmx1b, control chromatin accessibility in Pet1 neurons to select enhancers for 5-HT neurotransmission and synaptogenesis. In addition, these factors are required to maintain chromatin accessibility during early maturation suggesting that postmitotic open chromatin is unstable and requires continuous terminal selector input. Together our findings reveal a previously unrecognized function of terminal selectors in organizing postmitotic accessible chromatin for the development of specialized neuronal identities.

scholarly journals A deep generative model for multi-view profiling of single-cell RNA-seq and ATAC-seq data

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Gaoyang Li ◽  
Shaliu Fu ◽  
Shuguang Wang ◽  
Chenyu Zhu ◽  
Bin Duan ◽  
...  
Keyword(s):  
Single Cell ◽  
Regulatory Element ◽  
Chromatin Accessibility ◽  
Generative Model ◽  
Developmental Trajectory ◽  
Differential Analysis ◽  
Sequencing Data ◽  
Cell Clustering ◽  
Cell Groups ◽  
Latent Representations

AbstractHere, we present a multi-modal deep generative model, the single-cell Multi-View Profiler (scMVP), which is designed for handling sequencing data that simultaneously measure gene expression and chromatin accessibility in the same cell, including SNARE-seq, sci-CAR, Paired-seq, SHARE-seq, and Multiome from 10X Genomics. scMVP generates common latent representations for dimensionality reduction, cell clustering, and developmental trajectory inference and generates separate imputations for differential analysis and cis-regulatory element identification. scMVP can help mitigate data sparsity issues with imputation and accurately identify cell groups for different joint profiling techniques with common latent embedding, and we demonstrate its advantages on several realistic datasets.

scholarly journals ShinyArchR.UiO: User-friendly, integrative and open-source tool for visualisation of single-cell ATAC-seq data using ArchR

2021 ◽  
Author(s):  
Ankush Sharma ◽  
Akshay Akshay ◽  
Marie Rogne ◽  
Ragnhild Eskeland
Keyword(s):  
Single Cell ◽  
Open Source ◽  
Cell Fate ◽  
Single Cells ◽  
Chromatin Accessibility ◽  
Data Accessibility ◽  
Shiny App ◽  
User Friendly ◽  
Collaborative Efforts ◽  
Accessible Chromatin

Motivation: Mapping of chromatin accessibility landscapes in single-cells and the integration with gene expression enables a better understanding of gene regulatory mechanisms defining cell identities and cell-fate determination in development and disease. Generally, raw data generated from single-cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) are deposited in reposito-ries that are inaccessible due to lack of in-depth knowledge of computational programming. Results: We have developed ShinyArchR.UiO, an R-based shiny app, that facilitates scATAC-seq data accessibility and visualisation in a user-friendly, interactive, and open-source web interface. ShinyArchR.UiO is a tool that can streamline collaborative efforts for interpretation of massive chro-matin accessible data and promotes open access data sharing for wider audiences.

scholarly journals Single-cell multimodal profiling of proteins and chromatin accessibility using PHAGE-ATAC

2020 ◽  
Author(s):  
Evgenij Fiskin ◽  
Caleb A Lareau ◽  
Gökcen Eraslan ◽  
Leif S Ludwig ◽  
Aviv Regev
Keyword(s):  
Single Cell ◽  
Protein Detection ◽  
Chromatin Accessibility ◽  
Surface Proteins ◽  
Phage Library ◽  
Single Domain Antibody ◽  
Protein Levels ◽  
Multimodal Analysis ◽  
Cell Measurement ◽  
Accessible Chromatin

AbstractMulti-modal measurements of single cell profiles are a powerful tool for characterizing cell states and regulatory mechanisms. While current methods allow profiling of RNA along with either chromatin or protein levels, connecting chromatin state to protein levels remains a barrier. Here, we developed PHAGE-ATAC, a method that uses engineered camelid single-domain antibody (‘nanobody’)-displaying phages for simultaneous single-cell measurement of surface proteins, chromatin accessibility profiles, and mtDNA-based clonal tracing through a massively parallel droplet-based assay of single-cell transposase-accessible chromatin with sequencing (ATAC-seq). We demonstrate PHAGE-ATAC for multimodal analysis in primary human immune cells and for sample multiplexing. Finally, we construct a synthetic high-complexity phage library for selection of novel antigen-specific nanobodies that bind cells of particular molecular profiles, opening a new avenue for protein detection, cell characterization and screening with single-cell genomics.

scholarly journals Single-Cell RNA Sequencing and Assay for Transposase-Accessible Chromatin Using Sequencing Reveals Cellular and Molecular Dynamics of Aortic Aging in Mice

2021 ◽  
Author(s):  
Wenhui Xie ◽  
Yilang Ke ◽  
Qinyi You ◽  
Jing Li ◽  
Lu Chen ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Single Cell ◽  
Rna Sequencing ◽  
Chromatin Accessibility ◽  
Open Chromatin ◽  
Vascular Aging ◽  
Chromatin States ◽  
Single Cell Rna Sequencing ◽  
The Impact ◽  
Accessible Chromatin

Objective: The impact of vascular aging on cardiovascular diseases has been extensively studied; however, little is known regarding the cellular and molecular mechanisms underlying age-related vascular aging in aortic cellular subpopulations. Approach and Results: Transcriptomes and transposase-accessible chromatin profiles from the aortas of 4-, 26-, and 86-week-old C57/BL6J mice were analyzed using single-cell RNA sequencing and assay for transposase-accessible chromatin sequencing. By integrating the heterogeneous transcriptome and chromatin accessibility data, we identified cell-specific TF (transcription factor) regulatory networks and open chromatin states. We also determined that aortic aging affects cell interactions, inflammation, cell type composition, dysregulation of transcriptional control, and chromatin accessibility. Endothelial cells 1 have higher gene set activity related to cellular senescence and aging than do endothelial cells 2. Moreover, construction of senescence trajectories shows that endothelial cell 1 and fibroblast senescence is associated with distinct TF open chromatin states and an mRNA expression model. Conclusions: Our data provide a system-wide model for transcriptional and epigenetic regulation during aortic aging at single-cell resolution.

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