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Straightforward clustering of single-cell RNA-Seq data with t-SNE and DBSCAN

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What this work says

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

inferredcites →https://doi.org/10.1007/s10479-011-0841-3openalex-snapshot

Multiobjective evolutionary algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms

inferredcites →https://doi.org/10.1016/j.cpc.2010.04.018openalex-snapshot

NWChem: A comprehensive and scalable open-source solution for large scale molecular simulations

inferredcites →https://doi.org/10.1038/520612aopenalex-snapshot

Statistics: P values are just the tip of the iceberg

inferredcites →https://doi.org/10.1038/nbt.4314openalex-snapshot

Dimensionality reduction for visualizing single-cell data using UMAP

inferredcites →https://doi.org/10.1038/nmeth.2930openalex-snapshot

Validation of noise models for single-cell transcriptomics

inferredcites →https://doi.org/10.1038/nri.2017.76openalex-snapshot

Single-cell RNA sequencing to explore immune cell heterogeneity

inferredcites →https://doi.org/10.1038/s41592-018-0308-4openalex-snapshot

Fast interpolation-based t-SNE for improved visualization of single-cell RNA-seq data

inferredcites →https://doi.org/10.1073/pnas.1721085115openalex-snapshot

Gene expression distribution deconvolution in single-cell RNA sequencing

inferredcites →https://doi.org/10.1093/bib/bby011openalex-snapshot

Evaluation of tools for highly variable gene discovery from single-cell RNA-seq data

inferredcites →https://doi.org/10.1101/217737openalex-snapshot

K-nearest neighbor smoothing for high-throughput single-cell RNA-Seq data

inferredcites →https://doi.org/10.1101/655365openalex-snapshot

Accurate denoising of single-cell RNA-Seq data using unbiased principal component analysis

inferredcites →https://doi.org/10.1137/090771806openalex-snapshot

Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions

inferredcites →https://doi.org/10.1214/aoms/1177729756openalex-snapshot

Transformations Related to the Angular and the Square Root

inferredcites →https://doi.org/10.12688/f1000research.15666.2openalex-snapshot

A systematic performance evaluation of clustering methods for single-cell RNA-seq data

inferredcites →https://doi.org/10.21105/joss.00861openalex-snapshot

UMAP: Uniform Manifold Approximation and Projection

inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot

Scikit-learn: Machine Learning in Python

inferredcites →https://doi.org/10.48550/arxiv.1712.09005openalex-snapshot

Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding

inferredcites →https://doi.org/10.48550/arxiv.1802.03426openalex-snapshot

UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

inferredcites →https://doi.org/10.5555/2627435.2697068openalex-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← citeshttps://doi.org/10.1016/j.biosystemseng.2021.08.033openalex-snapshot

Efficiency of the t-distribution stochastic neighbor embedding technique for detailed visualization and modeling interactions between agricultural soil quality indicators

inferred← citeshttps://doi.org/10.1016/j.compbiomed.2022.106305openalex-snapshot

Dual-Stream Subspace Clustering Network for revealing gene targets in Alzheimer's disease

inferred← citeshttps://doi.org/10.1038/s41467-020-19015-1openalex-snapshot

Benchmarking of cell type deconvolution pipelines for transcriptomics data

inferred← citeshttps://doi.org/10.1101/2020.01.10.897116openalex-snapshot

Comprehensive benchmarking of computational deconvolution of transcriptomics data

inferred← citeshttps://doi.org/10.1101/2020.06.08.140673openalex-snapshot

Monet: An open-source Python package for analyzing and integrating scRNA-Seq data using PCA-based latent spaces

inferred← citeshttps://doi.org/10.1109/tcbb.2023.3242260openalex-snapshot

scENT for Revealing Gene Clusters From Single-Cell RNA-Seq Data

inferred← citeshttps://doi.org/10.1186/s12859-026-06525-wopenalex-snapshot

ScEnsemble: weighted hypergraph ensemble clustering for single-cell RNA sequencing

inferred← citeshttps://doi.org/10.1186/s13059-021-02451-7openalex-snapshot

Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data

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