CLoops2: a full-stack comprehensive analytical tool for chromatin interactions
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA741910 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14929800_1.fastq.gz | Fastqsanger.gz | |||
| SRR14929800_2.fastq.gz | Fastqsanger.gz | |||
| SRR14929801_1.fastq.gz | Fastqsanger.gz | |||
| SRR14929801_2.fastq.gz | Fastqsanger.gz | |||
| SRR14929802_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 16 |
Similar Datasets
Project description:Investigating chromatin interactions between regulatory regions such as enhancer and promoter elements is pivotal for a deeper understanding of gene expression regulation. The emerging 3D mapping technologies focusing on enriched signals such as Hi-TrAC/Trac-looping and HiChIP, compared to Hi-C, reduce the sequencing cost, and provide higher interaction resolution for cis-regulatory elements and more comprehensive information such as chromatin accessibility. A robust pipeline is needed for the comprehensive interpretation of these data, especially for loop-centric analysis. Therefore, we have developed a new versatile tool named cLoops2 for the full-stack analysis of the 3D chromatin interaction data. cLoops2 consists of core modules of peak-calling, loop-calling, differentially enriched loops calling and loops annotation. Additionally, it also contains multiple modules to carry out interaction resolution estimation, data similarity estimation, features quantification and aggregation analysis, and visualization. cLoops2 with documentation and example data are open source and freely available at GitHub: https://github.com/YaqiangCao/cLoops2
2021-11-29 | GSE179010 | GEO
Project description:Investigating chromatin interactions between regulatory regions such as enhancer and promoter elements is vital for understanding the regulation of gene expression. Compared to Hi-C and its variants, the emerging 3D mapping technologies focusing on enriched signals, such as TrAC-looping, reduce the sequencing cost and provide higher interaction resolution for cis-regulatory elements. A robust pipeline is needed for the comprehensive interpretation of these data, especially for loop-centric analysis. Therefore, we have developed a new versatile tool named cLoops2 for the full-stack analysis of these 3D chromatin interaction data. cLoops2 consists of core modules for peak-calling, loop-calling, differentially enriched loops calling and loops annotation. It also contains multiple modules for interaction resolution estimation, data similarity estimation, features quantification, feature aggregation analysis, and visualization. cLoops2 with documentation and example data are open source and freely available at GitHub: https://github.com/KejiZhaoLab/cLoops2.
| S-EPMC8754654 | biostudies-literature
Project description:Comprehensive mapping of SARS-CoV-2 interactions in vivo reveals virus-snoRNA interactions
| PRJNA692757 | ENA
Project description:Biospecimen Pre-analytical Variables (BPV)
| PRJNA376469 | ENA
Project description:This SuperSeries is composed of the following subset Series: GSE14694: Computational and Analytical Framework for Small RNA Profiling by High-Throughput Sequencing (reproducibility) GSE14695: Computational and Analytical Framework for Small RNA Profiling by High-Throughput Sequencing (standards) Refer to individual Series
2009-06-02 | E-GEOD-14696 | biostudies-arrayexpress
Project description:Stem cell-based embryo models offer unprecedented experimental tools for studying early human development. The usefulness of embryo models hinges on their molecular, cellular and structural fidelities to their in vivo counterparts. To authenticate human embryo models, single-cell RNA-sequencing has been utilised for unbiased transcriptional profiling of human embryo models. However, a well-organised and integrated human single-cell RNA-sequencing dataset, serving as a universal reference tool for benchmarking human embryo models, remains unavailable. Herein, we developed such a reference, through integration of six published human datasets covering developmental stages from the zygote to the gastrula. Lineage annotations are contrasted and validated with available human and non-human primate datasets. Using stabilised UMAP we constructed a web tool, where query datasets can be projected on the reference and annotated with predicted cell identities. Using this reference tool, we examined several recent human embryo models, highlighting the risk of misannotation when relevant references are lacking.
2024-07-16 | GSE254641 | GEO
Project description:MeDIP-Seq for assessment of the effect of pre-analytical variables on DNA methylation
2024-10-07 | GSE278575 | GEO
Project description:Higher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged through promoter-promoter interactions. Most genes with promoter-promoter interactions were active and transcribed cooperatively, and some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls. Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. Furthermore, genetically-identified disease-associated noncoding elements were found to be spatially engaged with corresponding genes through long-range interactions. Overall, our study provides insights into transcription regulation by three-dimensional chromatin interactions for both housekeeping and cell-specific genes in human cells. RNA polymerase II (RNAPII) bound chromatin interactions were extracted with Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing, in order to study the transcription regulations with RNAPII-associated long-range chromatin interactions. Five cell lines, namely MCF7 (ATCC# HTB-22), K562 (ATCC# CCL-243), HCT116 (ATCC# CCL-247), HeLa (ATCC# CCL-2.2), and NB4 (Roussel and Lanotte, 2001) (provided by Dr. Sherman Weissman, Yale University), were grown under standard culture conditions and harvested at log phase. Harvested cells were cross-linked using 1% formaldehyde followed by neutralization with 0.2M glycine. Chromatin was isolated and subjected to ChIA-PET protocol as described in Fullwood et al (Fullwood et al: An oestrogen-receptor-alpha-bound human chromatin interactome. Nature 2009, 462(7269):58-64). The ChIA-PET sequence reads were processed and analyzed using ChIA-PET Tool (Li et al: ChIA-PET tool for comprehensive chromatin interaction analysis with paired-end tag sequencing. Genome Biol 2010, 11(2):R22).
2012-01-20 | E-GEOD-33664 | biostudies-arrayexpress
Project description:Tandem promoters are common in nature, but investigations on their dynamics have so far largely relied on synthetic constructs. Thus, their regulation and potentially unique dynamics remain unexplored. We first performed a comprehensive exploration of the conservation of genes regulated by these promoters in E. coli and the properties of their input transcription factors. We then measured protein and RNA levels expressed by 30 Escherichia coli tandem promoters, to establish an analytical model of the expression dynamics of genes controlled by such promoters. We show that start site occlusion and downstream RNAP occupancy can be realistically captured by a model with RNAP binding affinity, the time length of open complex formation, and the nucleotide distance between transcription start sites. This study contributes to a better understanding of the unique dynamics tandem promoters can bring to the dynamics of gene networks and will assist in their use in synthetic genetic circuits.
2022-01-17 | GSE183139 | GEO
Project description:The purpose of this work was to describe a computational and analytical methodology for profiling small RNA by high-throughput sequencing. The datasets here were used to develop synthetic oligoribonucleotides as spike-in standards.
2009-06-03 | GSE14695 | GEO