ArticleNature communications2022
Zero-preserving imputation of single-cell RNA-seq data.
Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 190 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
190 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.Briefings in bioinformatics · 2025Pooled it
- Pooled it
- An imputation method for single-cell RNA sequencing data based on a parallel gated recurrent unit neural network.Quantitative biology (Beijing, China) · 2026Article
- CD200Nature communications · 2026Article
- scCADI: Cell-Aware Diffusion Model for Single-Cell RNA-seq Imputation.Interdisciplinary sciences, computational life sciences · 2026Article
- Reconstructing signaling histories of single cells via perturbation screens and transfer learning.Nature methods · 2026Article
- CAR design equips diverse immune cells with unique antigen-specific activation identities.Molecular therapy. Oncology · 2026Article
- OscillomeR infers ultradian oscillations and targets of the Hes family.Patterns (New York, N.Y.) · 2026Article
- Codon-optimizedMolecular therapy. Nucleic acids · 2026Article
- Generation of effector CD4Stem cell reports · 2026Article
- Single-cell profiling identifies obesity-disrupted brain glucose sensing.Nature communications · 2026Article
- Single-cell transcriptomics and functional analyses identified SPIN.DOC as a regulator for Wnt signaling and cancer stemness in colorectal cancer.Human cell · 2026Article
- Single cell transcriptomic analysis by deep learning identifies novel microglial transcription regulations in Alzheimer's Disease.AI in neuroscience · 2026Article
- Article
- Endothelial cannabinoid CB1 receptor deficiency reduces shear stress-induced arterial inflammation and lipid uptake.Nature communications · 2026Article
- Data-intensive immune network modelling for One Health.Briefings in bioinformatics · 2026Review
- Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer.Molecular oncology · 2026Article
- Neuronal microexons modulate arousal via the cAMP-PKA-CREB pathway in zebrafish.Science advances · 2026Article
- Article
- FAM135B suppresses glioblastoma angiogenesis via stabilizing the IKK complex and inactivating the NF-κB/IL-6 signaling pathway.Journal of translational medicine · 2026Article
130 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
A key challenge in analyzing single cell RNA-sequencing data is the large number of false zeros, where genes actually expressed in a given cell are incorrectly measured as unexpressed. We present a method based on low-rank matrix approximation which imputes these values while preserving biologically non-expressed genes (true biological zeros) at zero expression levels. We provide theoretical justification for this denoising approach and demonstrate its advantages relative to other methods on simulated and biological datasets.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.