ncHMR detector: a computational framework to systematically reveal non-classical functions of histone modification regulators

Hu, Shengen; Huo, Dawei; Yu, Zhaowei; Chen, Yujie; Liu, Jing; Liu, Lin; Wu, Xudong; Zhang, Yong

doi:10.1186/s13059-020-01953-0

Cited by 9 publications

(6 citation statements)

References 69 publications

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“…Processing of ChIP-seq data. ChIP-seq data were collected and processed as described in a previous study 45 . In brief, based on the quality measurements from the Cistrome data browser (CistromeDB) 34,35 , we included only the ChIP-seq datasets that pass at least four out of the first five QC measures (i.e., sequence quality, mapping quality, library complexity, ChIP enrichment, and signal-to-noise ratio).…”

Section: Methodsmentioning

confidence: 99%

“…For single-cell ATAC-seq data in the human hematopoietic cells and human cell line samples, the cell-type information for each individual cell was used as the ground truth, or the gold standard. For single-cell ATAC-seq data in the mouse gut tube sample, the cell-type information was assigned based on label transfer 40 from the single-cell RNA-seq dataset in the same system 48 (GSE136689), as the “pseudo” ground truth, or the silver standard. In detail, we integrated scRNA-seq and scATAC-seq data using the ArchR package 50 (v1.0.1).…”

Section: Methodsmentioning

confidence: 99%

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Accurate estimation of intrinsic biases for improved analysis of bulk and single-cell chromatin accessibility sequencing data using SELMA

Liu

et al. 2021

Preprint

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Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. However, enzymatic DNA cleavage exhibits intrinsic sequence biases that confound chromatin accessibility profiling data analysis. Existing computational tools are limited in their ability to account for such intrinsic biases. Here, we present Simplex Encoded Linear Model for Accessible Chromatin (SELMA), a computational method for systematic estimation of intrinsic cleavage biases from genomic chromatin accessibility profiling data. We demonstrate that SELMA yields accurate and robust bias estimation from both bulk and single-cell DNase-seq and ATAC-seq data. We show that transcription factor binding inference from DNase footprints can be improved by incorporating estimated biases using SELMA. We also demonstrate improved cell clustering of single-cell ATAC-seq data by considering the SELMA-estimated bias effect. SELMA can be applied to existing bioinformatics tools to improve the analysis of chromatin accessibility sequencing data.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Accurate estimation of intrinsic biases for improved analysis of bulk and single-cell chromatin accessibility sequencing data using SELMA

Liu

et al. 2021

Preprint

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“…We also applied penalized regression followed by univariate linear regression as described 52 , to reveal which features contributed to negative or positive Mvalue (log ratio of cohesin peak intensity between E2 and control) in intragenic cohesin (26066 sites). We used 169 features (of the 175 features, 6 were excluded: 5 features related to cohesin position and the Mvalue feature) as independent variables X i = ( X i 1 , X i 2 , …, X ij ), for i = 1, 2, …, 26066 and j = 1, 2, …, 169, whereas the Mvalue was the dependent variable Y i .…”

Section: Methodsmentioning

confidence: 99%

Section: Data Collection and Machine Learningmentioning

confidence: 99%

Large-scale multi-omics analysis suggests specific roles for intragenic cohesin in transcriptional regulation

Wang

Bando

Shirahige

et al. 2021

Preprint

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Cohesin, an essential protein complex for chromosome segregation, regulates transcription through a variety of mechanisms. It is not a trivial task to genome-widely assign the diverse cohesin functions. Moreover, the context-specific roles of cohesin-mediated interactions, especially on intragenic regions, have not been thoroughly investigated. Here we performed a comprehensive characterization of cohesin binding sites in several human cell types. We integrated epigenomic, transcriptomic and chromatin interaction data with and without transcriptional stimulation, to explore context-specific functions of intragenic cohesin related to gene activation. We identified a new subset of cohesin binding sites, decreased intragenic cohesin sites (DICs), which have a different function from previously known ones. The intron-enriched DICs were negatively correlated with transcriptional regulation: a subgroup of DICs were related to enhancer markers and paused RNA polymerase II, whereas others contributed to chromatin architecture. We implemented machine learning and successfully isolated DICs with distinct genomic features. We observed DICs in various cell types, including cells from cohesinopathy patients. These results suggest a previously unidentified function of cohesin at intragenic regions for transcription regulation.

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“…The ChIP-seq data of CAPs were collected from Cistrome Data Browser 46 and filtrated using quality control procedures as described in the previous study 47 . In brief, only ChIP-seq data that met at least four out of the five quality control metrics (sequence quality, mapping quality, library complexity, ChIP-enrichment, and signal-to-noise ratio) available in Cistrome Data Browser were kept.…”

Section: Chip-seq Data Collection and Processingmentioning

confidence: 99%

Decoding the genomic landscape of chromatin-associated biomolecular condensates

Yu,

Wang,

Zhu

et al. 2023

Preprint

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Biomolecular condensates play a significant role in chromatin activities, primarily by concentrating and compartmentalizing proteins and/or nucleic acids. However, their genomic landscapes and compositions remain largely unexplored due to a lack of dedicated computational tools for systematic identification in vivo. To address this, we developed CondSigDetector, a computational framework designed to detect condensate-like chromatin-associated protein co-occupancy signatures (CondSigs), to predict genomic loci and component proteins of distinct chromatin-associated biomolecular condensates. Applying this framework to mouse embryonic stem cells (mESC) and human K562 cells enabled us to depict the high-resolution genomic landscape of chromatin-associated biomolecular condensates, and uncover both known and potentially novel biomolecular condensates. Multi-omics analysis and experimental validation further verified the condensation properties of CondSigs. Additionally, our investigation shed light on the impact of chromatin-associated biomolecular condensates on chromatin activities. Collectively, CondSigDetector provides a novel approach to decode the genomic landscape of chromatin-associated condensates, facilitating a deeper understanding of their biological functions and underlying mechanisms in cells.

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ncHMR detector: a computational framework to systematically reveal non-classical functions of histone modification regulators

Cited by 9 publications

References 69 publications

Accurate estimation of intrinsic biases for improved analysis of bulk and single-cell chromatin accessibility sequencing data using SELMA

Accurate estimation of intrinsic biases for improved analysis of bulk and single-cell chromatin accessibility sequencing data using SELMA

Large-scale multi-omics analysis suggests specific roles for intragenic cohesin in transcriptional regulation

Decoding the genomic landscape of chromatin-associated biomolecular condensates

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