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Metric learning enables synthesis of heterogeneous single-cell modalities

https://doi.org/10.1101/834549
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing
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A Single-Cell Transcriptome Atlas of the Aging Drosophila Brain
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Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain
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Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity
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Comprehensive Integration of Single-Cell Data
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Entropy-Scaling Search of Massive Biological Data
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Geometric Sketching Compactly Summarizes the Single-Cell Transcriptomic Landscape
inferredcites →https://doi.org/10.1016/j.cels.2021.04.005openalex-snapshot
Hotspot identifies informative gene modules across modalities of single-cell genomics
inferredcites →https://doi.org/10.1016/j.tibtech.2018.04.002openalex-snapshot
Single-Cell DNA Methylation Profiling: Technologies and Biological Applications
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The Hitchhiker’s guide to Hi-C analysis: Practical guidelines
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Quantifiable predictive features define epitope-specific T cell receptor repertoires
inferredcites →https://doi.org/10.1038/nbt.3383openalex-snapshot
Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state
inferredcites →https://doi.org/10.1038/nbt.4091openalex-snapshot
Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors
inferredcites →https://doi.org/10.1038/nmeth.3971openalex-snapshot
Diffusion pseudotime robustly reconstructs lineage branching
inferredcites →https://doi.org/10.1038/nmeth.4227openalex-snapshot
Accurate identification of single-nucleotide variants in whole-genome-amplified single cells
inferredcites →https://doi.org/10.1038/nmeth.4380openalex-snapshot
Simultaneous epitope and transcriptome measurement in single cells
inferredcites →https://doi.org/10.1038/nmeth.4634openalex-snapshot
Identification of spatial expression trends in single-cell gene expression data
inferredcites →https://doi.org/10.1038/nmeth.4636openalex-snapshot
SpatialDE: identification of spatially variable genes
inferredcites →https://doi.org/10.1038/nmeth.4644openalex-snapshot
scmap: projection of single-cell RNA-seq data across data sets
inferredcites →https://doi.org/10.1038/nrg3833openalex-snapshot
Computational and analytical challenges in single-cell transcriptomics
inferredcites →https://doi.org/10.1038/s41467-018-06365-0openalex-snapshot
NEDDylation promotes nuclear protein aggregation and protects the Ubiquitin Proteasome System upon proteotoxic stress
inferredcites →https://doi.org/10.1038/s41467-019-13056-xopenalex-snapshot
The art of using t-SNE for single-cell transcriptomics
inferredcites →https://doi.org/10.1038/s41586-018-0654-5openalex-snapshot
Shared and distinct transcriptomic cell types across neocortical areas
inferredcites →https://doi.org/10.1038/s41586-019-0933-9openalex-snapshot
A single-cell molecular map of mouse gastrulation and early organogenesis
inferredcites →https://doi.org/10.1038/s41586-019-1825-8openalex-snapshot
Multi-omics profiling of mouse gastrulation at single-cell resolution
inferredcites →https://doi.org/10.1038/s41587-019-0113-3openalex-snapshot
Efficient integration of heterogeneous single-cell transcriptomes using Scanorama
inferredcites →https://doi.org/10.1038/s41587-020-0591-3openalex-snapshot
Generalizing RNA velocity to transient cell states through dynamical modeling
inferredcites →https://doi.org/10.1038/s41592-019-0466-zopenalex-snapshot
Joint analysis of heterogeneous single-cell RNA-seq dataset collections
inferredcites →https://doi.org/10.1038/s41592-019-0619-0openalex-snapshot
Fast, sensitive and accurate integration of single-cell data with Harmony
inferredcites →https://doi.org/10.1038/s41592-019-0701-7openalex-snapshot
Statistical analysis of spatial expression patterns for spatially resolved transcriptomic studies
inferredcites →https://doi.org/10.1038/s41593-017-0056-2openalex-snapshot
Conserved properties of dentate gyrus neurogenesis across postnatal development revealed by single-cell RNA sequencing
inferredcites →https://doi.org/10.1038/s41598-019-41695-zopenalex-snapshot
From Louvain to Leiden: guaranteeing well-connected communities
inferredcites →https://doi.org/10.1038/s41598-020-60845-2openalex-snapshot
Collective effects of long-range DNA methylations predict gene expressions and estimate phenotypes in cancer
inferredcites →https://doi.org/10.1073/pnas.1212755109openalex-snapshot
Statistical inference of the generation probability of T-cell receptors from sequence repertoires
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Fast unfolding of communities in large networks
inferredcites →https://doi.org/10.1093/nar/gkv1351openalex-snapshot
The Reactome pathway Knowledgebase
inferredcites →https://doi.org/10.1093/nar/gkx1081openalex-snapshot
The Encyclopedia of DNA elements (ENCODE): data portal update
inferredcites →https://doi.org/10.1093/nar/gkx1132openalex-snapshot
The Reactome Pathway Knowledgebase
inferredcites →https://doi.org/10.1093/nar/gkx760openalex-snapshot
VDJdb: a curated database of T-cell receptor sequences with known antigen specificity
inferredcites →https://doi.org/10.1093/nar/gky007openalex-snapshot
dropClust: efficient clustering of ultra-large scRNA-seq data
inferredcites →https://doi.org/10.1101/834549openalex-snapshot
Metric learning enables synthesis of heterogeneous single-cell modalities
inferredcites →https://doi.org/10.1109/78.258082openalex-snapshot
Matching pursuits with time-frequency dictionaries
inferredcites →https://doi.org/10.1111/j.1582-4934.2012.01604.xopenalex-snapshot
Neddylation dysfunction in Alzheimer's disease
inferredcites →https://doi.org/10.1111/j.2517-6161.1951.tb00095.xopenalex-snapshot
Inversions and Rank Correlation Coefficients
inferredcites →https://doi.org/10.1126/sciadv.aaw1668openalex-snapshot
Principles of genome folding into topologically associating domains
inferredcites →https://doi.org/10.1126/science.aau0730openalex-snapshot
Joint profiling of chromatin accessibility and gene expression in thousands of single cells
inferredcites →https://doi.org/10.1126/science.aaw1219openalex-snapshot
Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution
inferredcites →https://doi.org/10.1145/1143844.1143958openalex-snapshot
Local Fisher discriminant analysis for supervised dimensionality reduction
inferredcites →https://doi.org/10.1145/1273496.1273523openalex-snapshot
Information-theoretic metric learning
inferredcites →https://doi.org/10.1186/1471-2105-10-48openalex-snapshot
GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists
inferredcites →https://doi.org/10.1186/s12859-019-2864-8openalex-snapshot
Balancing sensitivity and specificity in distinguishing TCR groups by CDR sequence similarity
inferredcites →https://doi.org/10.1186/s13059-017-1382-0openalex-snapshot
SCANPY: large-scale single-cell gene expression data analysis
inferredcites →https://doi.org/10.1186/s13059-018-1416-2openalex-snapshot
Single-cell RNA-seq analysis unveils a prevalent epithelial/mesenchymal hybrid state during mouse organogenesis
inferredcites →https://doi.org/10.1186/s13059-020-02015-1openalex-snapshot
MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data
inferredcites →https://doi.org/10.1371/journal.pone.0021800openalex-snapshot
REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms
inferredcites →https://doi.org/10.21105/joss.00861openalex-snapshot
UMAP: Uniform Manifold Approximation and Projection
inferredcites →https://doi.org/10.4049/jimmunol.1700744openalex-snapshot
Emerging Concepts in TCR Specificity: Rationalizing and (Maybe) Predicting Outcomes
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.48550/arxiv.1802.03426openalex-snapshot
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
inferredcites →https://doi.org/10.5555/1577069.1577078openalex-snapshot
Distance Metric Learning for Large Margin Nearest Neighbor Classification
inferredcites →https://doi.org/10.5555/2627435.2697068openalex-snapshot
Accelerating t-SNE using tree-based algorithms

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← backgroundhttps://doi.org/10.5281/zenodo.4521803zenodo-depositor-declared
inferred← citeshttps://doi.org/10.1016/j.csbj.2021.04.060openalex-snapshot
Computational strategies for single-cell multi-omics integration
inferred← citeshttps://doi.org/10.1093/bib/bbaa042openalex-snapshot
Computational methods for the integrative analysis of single-cell data
inferred← citeshttps://doi.org/10.1101/719088openalex-snapshot
Coexpression enables multi-study cellular trajectories of development and disease
inferred← citeshttps://doi.org/10.1186/s13059-021-02313-2openalex-snapshot
Schema: metric learning enables interpretable synthesis of heterogeneous single-cell modalities
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