
Cell Metabolism, Journal Year: 2022, Volume and Issue: 34(3), P. 473 - 486.e9
Published: Feb. 3, 2022
Language: Английский
Cell Metabolism, Journal Year: 2022, Volume and Issue: 34(3), P. 473 - 486.e9
Published: Feb. 3, 2022
Language: Английский
The Science of The Total Environment, Journal Year: 2020, Volume and Issue: 751, P. 141727 - 141727
Published: Aug. 18, 2020
Language: Английский
Citations
412Nucleic Acids Research, Journal Year: 2022, Volume and Issue: 51(D1), P. D1425 - D1431
Published: Nov. 2, 2022
Abstract The Tumor Immune Single Cell Hub 2 (TISCH2) is a resource of single-cell RNA-seq (scRNA-seq) data from human and mouse tumors, which enables comprehensive characterization gene expression in the tumor microenvironment (TME) across multiple cancer types. As an increasing number datasets are generated public domain, this update, TISCH2 has included 190 scRNA-seq covering 6 million cells 50 types, with 110 newly collected almost tripling compared previous release. Furthermore, includes several new functions that allow users to better utilize large-scale datasets. First, Dataset module, provides cell–cell communication results each dataset, facilitating analyses interacted cell types discovery significant ligand–receptor pairs between also transcription factor for dataset visualization top enriched factors type. Second, Gene adds identifying correlated genes providing survival information input genes. In summary, user-friendly, up-to-date well-maintained TME. freely available at http://tisch.comp-genomics.org/.
Language: Английский
Citations
295Genome biology, Journal Year: 2020, Volume and Issue: 21(1)
Published: Feb. 7, 2020
Abstract We developed Lisa ( http://lisa.cistrome.org/ ) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on input sets, first uses histone mark ChIP-seq and chromatin accessibility profiles construct a model related regulation these genes. Using TR peaks imputed binding sites, probes models using in silico deletion find most relevant TRs. Applied sets derived from targeted TF perturbation experiments, boosted performance cistromes outperformed alternative methods identifying perturbed
Language: Английский
Citations
242Nature Reviews Genetics, Journal Year: 2023, Volume and Issue: 24(11), P. 739 - 754
Published: June 26, 2023
Language: Английский
Citations
201Genome biology, Journal Year: 2020, Volume and Issue: 21(1)
Published: Aug. 7, 2020
Abstract We present Model-based AnalysEs of Transcriptome and RegulOme (MAESTRO), a comprehensive open-source computational workflow ( http://github.com/liulab-dfci/MAESTRO ) for the integrative analyses single-cell RNA-seq (scRNA-seq) ATAC-seq (scATAC-seq) data from multiple platforms. MAESTRO provides functions pre-processing, alignment, quality control, expression chromatin accessibility quantification, clustering, differential analysis, annotation. By modeling gene regulatory potential accessibilities at level, outperforms existing methods integrating cell clusters between scRNA-seq scATAC-seq. Furthermore, supports automatic cell-type annotation using predefined type marker genes identifies driver regulators scATAC-seq peaks.
Language: Английский
Citations
163Cell, Journal Year: 2021, Volume and Issue: 184(21), P. 5357 - 5374.e22
Published: Sept. 27, 2021
Language: Английский
Citations
140Soil Biology and Biochemistry, Journal Year: 2021, Volume and Issue: 164, P. 108472 - 108472
Published: Oct. 29, 2021
Language: Английский
Citations
114Cell Metabolism, Journal Year: 2023, Volume and Issue: 35(9), P. 1580 - 1596.e9
Published: July 27, 2023
Language: Английский
Citations
112Nature, Journal Year: 2023, Volume and Issue: 617(7962), P. 818 - 826
Published: May 17, 2023
Language: Английский
Citations
100PLoS Computational Biology, Journal Year: 2022, Volume and Issue: 18(8), P. e1010378 - e1010378
Published: Aug. 30, 2022
We present WhichTF, a computational method to identify functionally important transcription factors (TFs) from chromatin accessibility measurements. To rank TFs, WhichTF applies an ontology-guided functional approach compute novel enrichment by integrating measurements, high-confidence pre-computed conservation-aware TF binding sites, and putative gene-regulatory models. Comparison with prior sheer abundance-based methods reveals the unique ability of context-specific TFs relevance, including NF-κB family members in lymphocytes GATA cardiac cells. distinguish transcriptional regulatory landscape closely related samples, we apply differential analysis demonstrate its utility lymphocyte, mesoderm developmental, disease find suggestive, under-characterized such as RUNX3 development GLI1 systemic lupus erythematosus. also known for stress response, suggesting routine experimental caveats that warrant careful consideration. yields biological insight into molecular mechanisms TF-mediated regulation diverse contexts, human mouse cell types, fate trajectories, disease-associated
Language: Английский
Citations
96