Fast, sensitive, and accurate integration of single cell data with Harmony
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Summary
Harmony, for the integration of single-cell transcriptomic data, identifies broad and fine-grained populations, scales to large datasets, and can integrate sequencing- and imaging-based data.
- Type
- article
- Published
- 2019-11-18
- Cited by
- 8,586
- References
- 61
- Access
- Open access
- OpenAlex
- https://openalex.org/W2984472267
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:92407379
Keywords
Data integration, Computer science, Computational biology, Biology, Data mining
References
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- Islet-1 Regulates Arx Transcription during Pancreatic Islet α-Cell Development*
- Insm1 cooperates with Neurod1 and Foxa2 to maintain mature pancreatic β-cell function
- Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool
- Dimensionality Reduction Via Graph Structure Learning
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- Genome-wide atlas of gene expression in the adult mouse brain
- Fast unfolding of communities in large networks
- Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis
- limma powers differential expression analyses for RNA-sequencing and microarray studies
- X-Box Binding Protein 1 Is Essential for Insulin Regulation of Pancreatic α-Cell Function
- Pdx1 (MODY4) regulates pancreatic beta cell susceptibility to ER stress
- Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
- De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data
- Massively parallel digital transcriptional profiling of single cells
- A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor
Cited by
- Single-cell transcriptome sequencing revealed the metabolic changes and microenvironment changes of cardiomyocytes induced by diabetes
- Tumor microenvironment remodeling after neoadjuvant chemoradiotherapy in local advanced rectal cancer revealed by single-cell RNA sequencing
- Probabilistic harmonization and annotation of single‐cell transcriptomics data with deep generative models
- Geometric Sketching Compactly Summarizes the Single-Cell Transcriptomic Landscape
- A novel algorithm for the collective integration of single cell RNA-seq during embryogenesis
- Pancreas patch-seq links physiologic dysfunction in diabetes to single-cell transcriptomic phenotypes
- Systematic comparative analysis of single cell RNA-sequencing methods
- Benchmarking single-cell RNA-sequencing protocols for cell atlas projects
- Current best practices in single‐cell RNA‐seq analysis: a tutorial
- Single-cell transcriptomic analysis of mIHC images via antigen mapping
- LAmbDA: label ambiguous domain adaptation dataset integration reduces batch effects and improves subtype detection
- Embedding to reference t-SNE space addresses batch effects in single-cell classification
- Single cell chromatin accessibility reveals pancreatic islet cell type- and state-specific regulatory programs of diabetes risk
- scAEspy: a unifying tool based on autoencoders for the analysis of single-cell RNA sequencing data
- Systems-level analysis of monocyte responses in inflammatory bowel disease identifies IL-10 and IL-1 cytokine networks that regulate IL-23
- BBKNN: fast batch alignment of single cell transcriptomes
- Cross-Species Analysis of Single-Cell Transcriptomic Data
- Multimodal single-cell approaches shed light on T cell heterogeneity
- The Accelerating Medicines Partnership – Organizational Structure and Preliminary Data from the Phase 1 Studies of Lupus Nephritis
- cellHarmony: cell-level matching and holistic comparison of single-cell transcriptomes
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