ArticleBMC genomics2016
Assessing characteristics of RNA amplification methods for single cell RNA sequencing.
Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- A practical guide to targeted single-cell RNA sequencing technologies.Communications biology · 2026Review
- Performance comparison of high throughput single-cell RNA-Seq platforms in complex tissues.Heliyon · 2024Article
- Gene expression in the primate orbitofrontal cortex related to anxious temperament.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Gene length is a pivotal feature to explain disparities in transcript capture between single transcriptome techniques.Frontiers in bioinformatics · 2023Article
- Enhancing biological signals and detection rates in single-cell RNA-seq experiments with cDNA library equalization.Nucleic acids research · 2022Article
- Statistics or biology: the zero-inflation controversy about scRNA-seq data.Genome biology · 2022Review
- Multi-omics integration in the age of million single-cell data.Nature reviews. Nephrology · 2021Review
- Systematic comparison of single-cell and single-nucleus RNA-sequencing methods.Nature biotechnology · 2020Article
- Scedar: A scalable Python package for single-cell RNA-seq exploratory data analysis.PLoS computational biology · 2020Article
- Robust RNA-Seq of aRNA-amplified single cell material collected by patch clamp.Scientific reports · 2020Article
- scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data.Genome biology · 2019Article
- Allele-specific RNA imaging shows that allelic imbalances can arise in tissues through transcriptional bursting.PLoS genetics · 2019Article
- The successes and future prospects of the linear antisense RNA amplification methodology.Nature protocols · 2018Article
- Rare Cell Detection by Single-Cell RNA Sequencing as Guided by Single-Molecule RNA FISH.Cell systems · 2018Article
- Article
- Multimodal profiling of single-cell morphology, electrophysiology, and gene expression using Patch-seq.Nature protocols · 2017Article
- Single cell transcriptomics of noncoding RNAs and their cell-specificity.Wiley interdisciplinary reviews. RNA · 2017Review
- Unravelling biology and shifting paradigms in cancer with single-cell sequencing.Nature reviews. Cancer · 2017Review
- Nanopore long-read RNAseq reveals widespread transcriptional variation among the surface receptors of individual B cells.Nature communications · 2017Article
- Assessment of Single Cell RNA-Seq Normalization Methods.G3 (Bethesda, Md.) · 2017Article
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Authors and funding
31 authors.
Funding
Abstract
backgroundRecently, measurement of RNA at single cell resolution has yielded surprising insights. Methods for single-cell RNA sequencing (scRNA-seq) have received considerable attention, but the broad reliability of single cell methods and the factors governing their performance are still poorly known.
resultsHere, we conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. All three methods detected greater than 70% of the expected number of genes and had a 50% probability of detecting genes with abundance greater than 2 to 4 molecules. Despite the small number of molecules, sequencing depth significantly affected gene detection. While biases in detection and quantification were qualitatively similar across methods, the degree of bias differed, consistent with differences in molecular protocol. Measurement reliability increased with expression level for all methods and we conservatively estimate measurements to be quantitative at an expression level greater than ~5-10 molecules.
conclusionsBased on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information.
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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.