ArticleGigaScience2022
Triku: a feature selection method based on nearest neighbors for single-cell data.
Article in GigaScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Optimal gene panel selection for targeted spatial transcriptomics experiments.Nucleic acids research · 2026Article
- Benchmarking LLM-based agents for single-cell omics analysis.Genome biology · 2026Article
- High resolution multi-scale profiling of embryonic germ cell-like cell derivation reveals pluripotent state transitions in humans.Stem cell reports · 2026Article
- Novel Acinar Metaplastic States Uncovered in Exocrine Pancreas Disease.Cellular and molecular gastroenterology and hepatology · 2026Article
- Optimal Gene Panel Selection for Targeted Spatial Transcriptomics Experiments.bioRxiv : the preprint server for biology · 2025Article
- Feature selection methods affect the performance of scRNA-seq data integration and querying.Nature methods · 2025Article
- Probe set selection for targeted spatial transcriptomics.Nature methods · 2024Article
- A polarized FGF8 source specifies frontotemporal signatures in spatially oriented cell populations of cortical assembloids.Nature methods · 2024Article
- Mcadet: A feature selection method for fine-resolution single-cell RNA-seq data based on multiple correspondence analysis and community detection.PLoS computational biology · 2024Article
- Boosting Single-Cell RNA Sequencing Analysis with Simple Neural Attention.bioRxiv : the preprint server for biology · 2023Article
- A cofunctional grouping-based approach for non-redundant feature gene selection in unannotated single-cell RNA-seq analysis.Briefings in bioinformatics · 2023Article
- Computational single cell oncology: state of the art.Frontiers in genetics · 2023Review
- On the use of QDE-SVM for gene feature selection and cell type classification from scRNA-seq data.PloS one · 2023Article
- Triku: a feature selection method based on nearest neighbors for single-cell data.GigaScience · 2022Article
- The need to reassess single-cell RNA sequencing datasets: the importance of biological sample processing.F1000Research · 2021Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundFeature selection is a relevant step in the analysis of single-cell RNA sequencing datasets. Most of the current feature selection methods are based on general univariate descriptors of the data such as the dispersion or the percentage of zeros. Despite the use of correction methods, the generality of these feature selection methods biases the genes selected towards highly expressed genes, instead of the genes defining the cell populations of the dataset.
resultsTriku is a feature selection method that favors genes defining the main cell populations. It does so by selecting genes expressed by groups of cells that are close in the k-nearest neighbor graph. The expression of these genes is higher than the expected expression if the k-cells were chosen at random. Triku efficiently recovers cell populations present in artificial and biological benchmarking datasets, based on adjusted Rand index, normalized mutual information, supervised classification, and silhouette coefficient measurements. Additionally, gene sets selected by triku are more likely to be related to relevant Gene Ontology terms and contain fewer ribosomal and mitochondrial genes.
conclusionTriku is developed in Python 3 and is available at https://github.com/alexmascension/triku.
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