APEC: an accesson-based method for single-cell chromatin accessibility analysis

Li, Bin; Li, Young; Li, Kun; Zhu, Lianbang; Yu, Qiaoni; Cai, Pengfei; Fang, Jingwen; Zhang, Wen; Du, Pengcheng; Jiang, Chen; Lin, Jun; Qu, Kun

doi:10.1186/s13059-020-02034-y

Cited by 13 publications

(17 citation statements)

References 88 publications

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“…The libraries were sequenced using a HiSeq X-10 Sequencing System (Illumina). scATAC-seq experiments were performed as previously described [ 15 ].…”

Section: Methodsmentioning

confidence: 99%

“…We used the general mapping, alignment, peak calling, and motif searching procedures to process the scATAC-seq data from APEC [ 15 ] and ATAC-pipe [ 20 ]. We also implemented a Python script in ATAC-pipe to trim adapters in the raw data (in paired-end FASTQ files for each single-cell sample).…”

Section: Methodsmentioning

confidence: 99%

“…APEC calculates the number of fragments and the percent of reads mapped to the transcriptional start site (TSS) region (±2000 bp) in each cell and filters out high-quality cells. Finally, we obtained 1933 cells with 600 accessons [ 15 ] (peak group with a similar pattern). TF enrichment in each cell was obtained for downstream analysis.…”

Section: Methodsmentioning

confidence: 99%

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Development of double-positive thymocytes at single-cell resolution

Zhu

et al. 2021

Genome Med

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Background T cells generated from thymopoiesis are essential for the immune system, and recent single-cell studies have contributed to our understanding of the development of thymocytes at the genetic and epigenetic levels. However, the development of double-positive (DP) T cells, which comprise the majority of thymocytes, has not been well investigated. Methods We applied single-cell sequencing to mouse thymocytes and analyzed the transcriptome data using Seurat. By applying unsupervised clustering, we defined thymocyte subtypes and validated DP cell subtypes by flow cytometry. We classified the cell cycle phases of each cell according to expression of cell cycle phase-specific genes. For immune synapse detection, we used immunofluorescent staining and ImageStream-based flow cytometry. We studied and integrated human thymocyte data to verify the conservation of our findings and also performed cross-species comparisons to examine species-specific gene regulation. Results We classified blast, rearrangement, and selection subtypes of DP thymocytes and used the surface markers CD2 and Ly6d to identify these subtypes by flow cytometry. Based on this new classification, we found that the proliferation of blast DP cells is quite different from that of double-positive cells and other cell types, which tend to exit the cell cycle after a single round. At the DP cell selection stage, we observed that CD8-associated immune synapses formed between thymocytes, indicating that CD8sp selection occurred among thymocytes themselves. Moreover, cross-species comparison revealed species-specific transcription factors (TFs) that contribute to the transcriptional differences of thymocytes from humans and mice. Conclusions Our study classified DP thymocyte subtypes of different developmental stages and provided new insight into the development of DP thymocytes at single-cell resolution, furthering our knowledge of the fundamental immunological process of thymopoiesis.

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“…The libraries were sequenced using a HiSeq X-10 Sequencing System (Illumina). scATAC-seq experiments were performed as previously described [ 15 ].…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Development of double-positive thymocytes at single-cell resolution

Zhu

et al. 2021

Genome Med

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“…Applying 10 × scATAC-seq, researchers achieved a more excellent mapping of differential open chromatin in immune cells within the tumor microenvironment [54]. To interpret the scATAC-seq data, which are more sparse compared to single-cell RNA-seq data, scientists have developed a variety of computational tools such as chrom-VAR [55], Cicero [56], cisTopic [57], APEC [58], etc.…”

Section: The Development Of Atac-seqmentioning

confidence: 99%

Profiling chromatin regulatory landscape: insights into the development of ChIP-seq and ATAC-seq

Zhang

2020

Mol Biomed

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Chromatin regulatory landscape plays a critical role in many disease processes and embryo development. Epigenome sequencing technologies such as chromatin immunoprecipitation sequencing (ChIP-seq) and assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) have enabled us to dissect the pan-genomic regulatory landscape of cells and tissues in both time and space dimensions by detecting specific chromatin state and its corresponding transcription factors. Pioneered by the advancement of chromatin immunoprecipitation-chip (ChIP-chip) technology, abundant epigenome profiling technologies have become available such as ChIP-seq, DNase I hypersensitive site sequencing (DNase-seq), ATAC-seq and so on. The advent of single-cell sequencing has revolutionized the next-generation sequencing, applications in single-cell epigenetics are enriched rapidly. Epigenome sequencing technologies have evolved from low-throughput to high-throughput and from bulk sample to the single-cell scope, which unprecedentedly benefits scientists to interpret life from different angles. In this review, after briefly introducing the background knowledge of epigenome biology, we discuss the development of epigenome sequencing technologies, especially ChIP-seq & ATAC-seq and their current applications in scientific research. Finally, we provide insights into future applications and challenges.

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“…Many existing scATAC-seq analytical pipelines assessed their performance solely based on real datasets [8][9][10][11][12][13][14]. Some studies generated simulated data by downsampling reads from bulk ATAC-seq data [15][16][17][18][19] or deploying ad-hoc simulation methods [20][21][22][23]. However, these simulation methods were implemented as part of the development or evaluation of scATAC-seq pipelines and were usually incompletely documented, resulting in a lack of reproducibility.…”

Section: Introductionmentioning

confidence: 99%

simATAC: a single-cell ATAC-seq simulation framework

Ghaziani

Zhang

Wang

2020

Preprint

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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.

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APEC: an accesson-based method for single-cell chromatin accessibility analysis

Cited by 13 publications

References 88 publications

Development of double-positive thymocytes at single-cell resolution

Development of double-positive thymocytes at single-cell resolution

Profiling chromatin regulatory landscape: insights into the development of ChIP-seq and ATAC-seq

simATAC: a single-cell ATAC-seq simulation framework

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