ReviewIET nanobiotechnology2023
scRNA-seq data analysis method to improve analysis performance.
Review in IET nanobiotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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
40 citing papers in PubMed, 49 citations in OpenAlex.
- A graph-attentive GAN for rare-cell-aware single-cell RNA-seq data generation.PLoS computational biology · 2026Article
- Role of IFIT1 and IFIT3 in systemic lupus erythematosus: modeling a diagnosis and exploring immune regulation.Clinical and experimental medicine · 2026Article
- SC-framework: A robust and FAIR semi-interactive environment for single-cell resolution datasets.iScience · 2026Article
- Targeting macrophage-associated core genes for prognostic prediction and therapeutic insights in bladder cancer.Discover oncology · 2026Article
- Single-cell RNA sequencing in ovarian cancer: decoding the tumor microenvironment for personalized therapy.Journal of ovarian research · 2026Review
- SGMHA: semantic graph reconstruction with multi-head attention for gene regulatory network inference.BMC genomics · 2026Article
- Identification of key genes related to macrophages and metabolic reprogramming in myocardial infarct based on single-cell and bulk transcriptomics data and experimental validation.BMC cardiovascular disorders · 2026Article
- Combined single-cell RNA sequencing and mendelian randomization to identify biomarkers associated with circadian rhythm in sarcopenia.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- In Vitro and In Vivo Validation of Endothelium-Derived Potential Therapeutics for Myocardial Ischemia/Reperfusion Injury Identified by an AI-Enhanced Single-Cell and Virtual-Cell Paradigm.International journal of molecular sciences · 2026Article
- Assessment of dispersion metrics for estimating single-cell transcriptional variability.PLoS computational biology · 2026Article
- Ranitidine protects Müller cells against ferroptosis in diabetic retinopathy by regulating the AKT1/GSK3β pathway.Indian journal of ophthalmology · 2026Article
- Integrated multi-omics and machine learning identify an interaction between SLC39A11 and phosphoinositide metabolism in deep vein thrombosis.BMC medical informatics and decision making · 2026Article
- Single-cell-derived ferroptosis signature predicts prognosis and therapy response in esophageal squamous cell carcinoma.Frontiers in oncology · 2026Article
- Advances in single-cell transcriptomic sequencing in hepatic echinococcosis.Frontiers in immunology · 2026Review
- From Single Genes to Systemic Networks: Transcriptomic Insights into Traditional Chinese Medicine for Heart Failure.Drug design, development and therapy · 2026Review
- Integrative multi-omics and machine learning analysis identifies candidate biomarkers associated with mitochondrial quality control in major depressive disorder.Frontiers in psychiatry · 2026Article
- LIMPACAT: Multi-omics attention transformer for immune prediction in liver cancer using whole-slide imaging.PloS one · 2026Article
- From trigeminal ganglion to cortex: ATG7 emerges as a key integrator of migraine pathways via multi-omics profiling.The journal of headache and pain · 2025Article
- Spatial Transcriptomics RevealsbioRxiv : the preprint server for biology · 2025Article
- The molecular complexity of deep vein thrombosis was preliminarily explored based on the ceRNA network, scRNA-seq and AlphaFold 2.BMC medical genomics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
With the development of single-cell RNA sequencing technology (scRNA-seq), we have the ability to study biological questions at the level of the individual cell transcriptome. Nowadays, many analysis tools, specifically suitable for single-cell RNA sequencing data, have been developed. In this review, the currently commonly used scRNA-seq protocols are discussed. The upstream processing flow pipeline of scRNA-seq data, including goals and popular tools for reads mapping and expression quantification, quality control, normalization, imputation, and batch effect removal is also introduced. Finally, methods to evaluate these tools in both cellular and genetic dimensions, clustering and differential expression analysis are presented.
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.