Experiments

Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).

• OTMODE: an optimal transport theory-based framework for identifying differential features in single-cell multi-omics data.

  PMID 41335419 · PMC12766913 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups

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  OTMODE, using an unbalanced Sinkhorn algorithm and Wald test, improves differential feature identification in single-cell multi-omics data

  simulated classical degs naive simulated bulk real

• Evaluating imputation methods for accurate estimation of cell population fractions in single-cell RNA sequencing.

  PMID 41503159 · PMC12770975 · NAR genomics and bioinformatics · 2026 · 8 claims · 6 setups

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  Eight prominent imputation methods (MAGIC, SAVER, scVI, DCA, scBiG, kNN-smoothing, scImpute, ALRA) were systematically evaluated for their ability to recover the true non-zero expression fraction using simulated and real-world scRNA-seq data

  basal tracheal airway k562 simulated scrna-seq imputation

• FLASH-MM: fast and scalable single-cell differential expression analysis using linear mixed-effects models.

  PMID 41644528 · PMC12982622 · Nature communications · 2026 · 8 claims · 6 setups

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  FLASH-MM produces LMM parameter estimates identical to lmer (lme4) up to the sixth decimal place while being 50- to 140-fold faster as sample size increases from 20,000 to 120,000 cells

  simulated same healthy female-biased simulated comparative single-cell

• PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns.

  PMID 41673899 · PMC12998178 · Genome biology · 2026 · 7 claims · 8 setups

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  PreTSA dramatically reduces computational time and memory versus GAM (Monocle, TSCAN) and PseudotimeDE for identifying temporally variable genes (TVGs) while producing highly similar results

  simulated null pbmc pancreas pseudotime tvg false-positive

• scTWAS: a powerful statistical framework for single-cell transcriptome-wide association studies.

  PMID 41820391 · PMC13121454 · Nature communications · 2026 · 8 claims · 5 setups

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  scTWAS uses a latent-variable expression-measurement model combined with a moment-based regression to more accurately estimate genetic regulation of gene expression from single-cell data, improving GReX prediction across cell types and datasets

  onek1k-derived onek1k-based immune brain simulated two-sample stage

• scComm: a contrastive learning framework for deciphering cell-cell communications at single-cell resolution.

  PMID 41877186 · PMC13134144 · Genome biology · 2026 · 8 claims · 7 setups

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  scComm infers cell-cell communications at single-cell resolution using a data-adaptive L-R weighting module and supervised contrastive learning (SupCon loss) to distinguish significant CCC events from background noise

  simulated spatial liver single-cell simulated spatial scrna-seq

• Integrative Learning of Disentangled Representations from Single-Cell RNA-Sequencing Datasets.

  PMID 41971949 · PMC13068006 · Computational and structural biotechnology journal · 2026 · 8 claims · 6 setups

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  spVIPES decomposes unpaired scRNA-seq datasets with nonmatching features into shared and private latent representations using a Product of Experts framework

  simulated zebrafish kidney peripheral simulated cross-species scrna-seq

• scGACL: a generative adversarial network with multi-scale contrastive learning for accurate single-cell RNA sequencing imputation.

  PMID 41632596 · PMC12866930 · Briefings in bioinformatics · 2026 · 8 claims · 6 setups

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  scGACL, a GAN integrated with multi-scale contrastive learning, is proposed to overcome the over-smoothing problem in scRNA-seq imputation

  simulated real-world scrna-seq scrna-seq clustering gene

• ScLRTC: imputation for single-cell RNA-seq data via low-rank tensor completion.

  PMID 34844559 · PMC8628418 · BMC genomics · 2021 · 8 claims · 8 setups

  Has reproduction · 85

  scLRTC imputes dropout entries closest to the original expression values on simulated datasets, outperforming other state-of-the-art methods by SSE and PCC.

  usoskin pollen zeisel yan scrna-seq umap masking

• Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data.

  PMID 41825449 · PMC13030991 · Cell reports methods · 2026 · 7 claims · 3 setups

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  NCLUSION matches the performance of state-of-the-art single-cell clustering techniques with significantly reduced runtime

  brain-large scdesign3-simulated facs-purified scrna-seq simulated

• FUNCellA: A Tool for Single-Sample Enrichment Analysis and Relative Pathway Activity Estimation in Single-Cell RNA Sequencing Data.

  PMID 42021835 · PMC13096679 · Computational and structural biotechnology journal · 2026 · 7 claims · 8 setups

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  FUNCellA integrates 7 single-sample enrichment algorithms with novel relative activation thresholding methods to identify active, inactive, and intermediate cellular states in scRNA-Seq data

  pbmcs bone liver blood scrna-seq simulated microarray

• A copula-infused graph neural network for cell type classification in single-cell RNA sequencing data.

  PMID 41940310 · PMC12914865 · Computational and structural biotechnology journal · 2026 · 8 claims · 5 setups

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  scCopulaGNN combines copula theory with graph neural network representation learning for scRNA-seq cell type classification

  brain pancreas kidney turtle scrna-seq simulated

• Hypergraph representations of single-cell RNA sequencing data for improved cell clustering.

  PMID 41896196 · PMC13070707 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups

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  Unipartite network projections (e.g. cell/gene co-expression networks) of scRNA-seq data lose higher-order information and are an inefficient, inflated representation of sparse transcriptomic data

  pancreas brain lung simulated scrna-seq simulated

• Compact and informative representation learning for scRNA-seq data clustering with masked information bottleneck.

  PMID 41917934 · PMC13162528 · BMC biology · 2026 · 6 claims · 4 setups

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  scMIB achieves state-of-the-art and more stable clustering performance across diverse scRNA-seq datasets compared with ten baseline methods

  real same splatter-simulated scrna-seq clustering denoising

• scZiva: imputation method for single-cell RNA-seq data with zero-inflated variational autoencoder.

  PMID 41857511 · PMC13122936 · BMC bioinformatics · 2026 · 8 claims · 1 setups

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  scZiva is a novel VAE-based imputation method for scRNA-seq data using a Zero-Inflated Negative Binomial (ZINB) likelihood.

  simulated scrna-seq

• Cell neighborhood topology directs rare cell population identification.

  PMID 41912521 · PMC13199379 · Nature communications · 2026 · 8 claims · 8 setups

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  RareQ is a framework that quantifies neighborhood connectivity (Q), a cell-specific measure of kNN-graph cliquishness, to detect rare cell populations from single-cell and spatial omics data

  downsampled pbmc brain simulated scrna-seq cite-seq single-cell

• Trajectory-guided dimensionality reduction for multi-sample single-cell RNA-seq data reveals biologically relevant sample-level heterogeneity.

  PMID 42024616 · PMC13188987 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups

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  MUSTARD is a trajectory-guided dimensionality reduction method for multi-sample, multi-condition scRNA-seq data that simultaneously captures gene expression variation along pseudotime and across samples

  simulated covid-su covid-stephenson tuberculosis data-driven scrna-seq pseudobulk-pca

• scSurvival: Single-Cell Survival Analysis of Clinical Cancer Cohort Data at Cellular Resolution.

  PMID 42013315 · PMC13133615 · Cancer discovery · 2026 · 8 claims · 7 setups

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  scSurvival, an attention-based multiple-instance Cox regression framework, models each tumor sample as an ensemble of cells to predict survival outcomes at both patient and single-cell levels

  simulated melanoma liver higher scrna-seq differential

• Single-cell omics data-driven decoding of tumor clonal evolution through reinforcement learning.

  PMID 41998716 · PMC13224513 · Genome medicine · 2026 · 8 claims · 3 setups

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  scRevol is an RL-based model that infers tumor clonal evolution from scRNA-seq-derived CNV profiles via a label assignment learning strategy.

  simulated lineage ovarian scrna-seq-derived

• scSurv: a deep generative model for single-cell survival analysis.

  PMID 41429574 · PMC12797213 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups

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  scSurv combines a Cox proportional hazards model with a deep generative model (VAE) of single-cell transcriptomes to estimate individual cellular contributions to clinical outcomes

  simulated tcga melanoma renal scrna-seq bulk single-cell