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Comparative Analysis of Commercial Single-Cell RNA Sequencing Technologies

https://doi.org/10.1101/2024.06.18.599579

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Mass cytometry panel optimization through the designed distribution of signal interference

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A Curve for all reasons

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Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells

inferredcites →https://doi.org/10.1016/j.cell.2015.05.002openalex-snapshot

Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets

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Comprehensive Integration of Single-Cell Data

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Scrublet: Computational Identification of Cell Doublets in Single-Cell Transcriptomic Data

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Performance comparison of high throughput single-cell RNA-Seq platforms in complex tissues

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Multiplexed droplet single-cell RNA-sequencing using natural genetic variation

inferredcites →https://doi.org/10.1038/nprot.2017.149openalex-snapshot

Exponential scaling of single-cell RNA-seq in the past decade

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High-throughput RNA sequencing of paraformaldehyde-fixed single cells

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Best practices for single-cell analysis across modalities

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Systematic comparison of single-cell and single-nucleus RNA-sequencing methods

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Benchmarking single-cell RNA-sequencing protocols for cell atlas projects

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Systematic benchmarking of single-cell ATAC-sequencing protocols

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Characterizing the impacts of dataset imbalance on single-cell data integration

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Fast, sensitive and accurate integration of single-cell data with Harmony

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Optimized single-nucleus transcriptional profiling by combinatorial indexing

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Mitochondrial gene expression in single cells shape pancreatic beta cells' sub-populations and explain variation in insulin pathway

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Defining diversity, specialization, and gene specificity in transcriptomes through information theory

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Regulation of the cell cycle via mitochondrial gene expression and energy metabolism in HeLa cells

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Systematic determination of the mitochondrial proportion in human and mice tissues for single-cell RNA-sequencing data quality control

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A curated database reveals trends in single-cell transcriptomics

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A mitochondrial specific stress response in mammalian cells

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Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain

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Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding

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Cross-tissue immune cell analysis reveals tissue-specific features in humans

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Detect tissue heterogeneity in gene expression data with BioQC

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Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

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PBMC fixation and processing for Chromium single-cell RNA sequencing

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Scalable microfluidics for single-cell RNA printing and sequencing

inferredcites →https://doi.org/10.1186/s13059-016-0888-1openalex-snapshot

Classification of low quality cells from single-cell RNA-seq data

inferredcites →https://doi.org/10.1186/s13059-016-0947-7openalex-snapshot

Pooling across cells to normalize single-cell RNA sequencing data with many zero counts

inferredcites →https://doi.org/10.1186/s13059-016-1104-zopenalex-snapshot

Patterns of ribosomal protein expression specify normal and malignant human cells

inferredcites →https://doi.org/10.1186/s13059-018-1603-1openalex-snapshot

Cell Hashing with barcoded antibodies enables multiplexing and doublet detection for single cell genomics

inferredcites →https://doi.org/10.1186/s13059-019-1865-2openalex-snapshot

Vireo: Bayesian demultiplexing of pooled single-cell RNA-seq data without genotype reference

inferredcites →https://doi.org/10.12688/f1000research.15809.1openalex-snapshot

Comparison of clustering tools in R for medium-sized 10x Genomics single-cell RNA-sequencing data

inferredcites →https://doi.org/10.1371/journal.pone.0209648openalex-snapshot

Single-nucleus and single-cell transcriptomes compared in matched cortical cell types

inferredcites →https://doi.org/10.3389/fnmol.2023.1223798openalex-snapshot

Effect of methanol fixation on single-cell RNA sequencing of the murine dentate gyrus

inferredcites →https://doi.org/10.3389/fonc.2019.00415openalex-snapshot

Validation of CyTOF Against Flow Cytometry for Immunological Studies and Monitoring of Human Cancer Clinical Trials

inferredcites →https://doi.org/10.3390/genes14122226openalex-snapshot

Comparison of Single Cell Transcriptome Sequencing Methods: Of Mice and Men

inferredcites →https://doi.org/10.3390/ijms25073828openalex-snapshot

Comparative Analysis of Single-Cell RNA Sequencing Methods with and without Sample Multiplexing

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Comparison of single-cell RNA-seq methods to enable transcriptome profiling of neutrophils in clinical samples

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Immune-cell profiling to guide stratification and treatment of patients with rheumatic diseases

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High-throughput gene expression analysis with TempO-LINC sensitively resolves complex brain, lung and kidney heterogeneity at single-cell resolution

inferred← citeshttps://doi.org/10.1038/s41598-026-47700-6openalex-snapshot

Comprehensive guide for optimizing octopus immune cell preparation to enhance single cell RNA sequencing success

inferred← citeshttps://doi.org/10.1093/bib/bbae662openalex-snapshot

scRGCL: a cell type annotation method for single-cell RNA-seq data using residual graph convolutional neural network with contrastive learning

inferred← citeshttps://doi.org/10.1093/nargab/lqaf215openalex-snapshot

Evaluating the practical aspects and performance of commercial single-cell RNA sequencing technologies

inferred← citeshttps://doi.org/10.1093/nargab/lqag079openalex-snapshot

The challenges of single cell transcriptomics on difficult human tissue: the placenta

inferred← citeshttps://doi.org/10.1101/2024.08.13.607508openalex-snapshot

Single-Molecule Barcoding Technology for Single-Cell Genomics

inferred← citeshttps://doi.org/10.1101/2024.10.04.616561openalex-snapshot

Intrinsic molecular identifiers enable robust molecular counting in single-cell sequencing

inferred← citeshttps://doi.org/10.1101/2025.03.06.637075openalex-snapshot

Systematic evaluation of single-cell multimodal data integration for comprehensive human reference atlas

inferred← citeshttps://doi.org/10.1101/2025.10.24.684243openalex-snapshot

REFLEX, a Novel Immune Profiling Assay, Combining TCR Repertoire and Multiome at Massively Scalable Single-cell Resolution to Catapult Exploration of T-cell Derived Immunity

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Initiation of meiosis from human iPSCs under defined conditions through identification of regulatory factors

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Multistep genomics on single cells and live cultures in subnanoliter capsules

inferred← citeshttps://doi.org/10.1136/gutjnl-2024-334165openalex-snapshot

Single-cell omics in inflammatory bowel disease: recent insights and future clinical applications

inferred← citeshttps://doi.org/10.1161/circresaha.125.325795openalex-snapshot

Advancing Cardiovascular Research With Single-Cell and Spatial Transcriptomics

inferred← citeshttps://doi.org/10.1186/s13059-026-04002-4openalex-snapshot

Systematic evaluation of single-cell multimodal data integration enhances cell type resolution and discovery of clinically relevant states in complex tissues

inferred← citeshttps://doi.org/10.1371/journal.pone.0317343openalex-snapshot

Exploring a pico-well based scRNA-seq method (HIVE) for simplified processing of equine bronchoalveolar lavage cells

inferred← citeshttps://doi.org/10.64898/2026.01.27.702057openalex-snapshot

A platform-agnostic evaluation of non-formalin fixed single cell RNA technologies

inferred← citeshttps://doi.org/10.64898/2026.07.29.741357openalex-snapshot

Single-cell transcriptomics reveals a multiphasic Wolbachia host infection trajectory

inferred← citeshttps://doi.org/10.7171/001c.162768openalex-snapshot

Multisite Assessment of Methods for Cell Preservation Upstream of Single-Cell RNA Sequencing

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