ArticleBiophysics reports2022
Practical bioinformatics pipelines for single-cell RNA-seq data analysis.
Article in Biophysics reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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
11 citing papers in PubMed.
- CRISPR-Enabled functional genomics in hPSCs-derived neural models for autism spectrum disorder.Metabolic brain disease · 2026Review
- VINE-seq and MultiVINE-seq for single-nucleus and multiome profiling of the brain vasculature.Nature protocols · 2026Review
- Clonal Metamorphosis: Deconstructing MPN Evolution with Single-Cell and Spatial Multi-Omics.Clinical and experimental medicine · 2026Review
- The complement system contributes to the immunosuppressive microenvironment of uveal melanoma.Journal of translational medicine · 2026Article
- Exploring single-cell and multi-omics technologies and their role in unraveling tumor heterogeneity of hepatocellular carcinoma.Journal of liver cancer · 2026Review
- AI-Based Prediction of Gene Expression in Single-Cell and Multiscale Genomics and Transcriptomics.International journal of molecular sciences · 2026Review
- Decoding wound healing: cellular insights and technological advances.npj biomedical innovations · 2026Review
- Integrative Genomic and Functional Approaches Identify FUOM as a Key Driver and Therapeutic Target in Cervical Cancer.Cancer reports (Hoboken, N.J.) · 2025Article
- Galaxy as a gateway to bioinformatics: Multi-Interface Galaxy Hands-on Training Suite (MIGHTS) for scRNA-seq.GigaScience · 2025Article
- HeartMAP: A multi-chamber spatial framework for cardiac cell-cell communication.Computational and structural biotechnology journal · 2025Article
- Data Mining of Microarray Datasets in Translational Neuroscience.Brain sciences · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell RNA sequencing (scRNA-seq) is a revolutionary tool to explore cells. With an increasing number of scRNA-seq data analysis tools that have been developed, it is challenging for users to choose and compare their performance. Here, we present an overview of the workflow for computational analysis of scRNA-seq data. We detail the steps of a typical scRNA-seq analysis, including experimental design, pre-processing and quality control, feature selection, dimensionality reduction, cell clustering and annotation, and downstream analysis including batch correction, trajectory inference and cell-cell communication. We provide guidelines according to our best practice. This review will be helpful for the experimentalists interested in analyzing their data, and will aid the users seeking to update their analysis pipelines.
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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.