Assessment of single cell RNA-seq normalization methods
Abstract
We have assessed the performance of seven normalization methods for single cell RNA-seq using data generated from dilution of RNA samples. Our analyses showed that methods considering spike-in ERCC RNA molecules significantly outperformed those not considering ERCCs. This work provides a guidance of selecting normalization methods to remove technical noise in single cell RNA-seq data.
02 /Specification & Classification
Click any tag to browse matching papers- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Assessing The Reliability Of Spike-In Normalization For Analyses Of Single-Cell RNA Sequencing Data
Aaron T. L. Lun, Fernando J. Calero‐Nieto, … John C. Marioni·Genome ResearchPeer-reviewed·Nov 1, 2017
- SCnorm: A quantile-regression based approach for robust normalization of single-cell RNA-seq data
Rhonda L. Bacher, Li‐Fang Chu, … Christina M. Kendziorski·Nature MethodsPeer-reviewed·Apr 17, 2017
- Normalization by distributional resampling of high throughput single-cell RNA-sequencing data
Jared Brown, Zijian Ni, … Christina M. Kendziorski·BioinformaticsPeer-reviewed·Jun 15, 2021
- Normalizing single-cell RNA sequencing data with internal spike-in-like genes
Li Lin, Minfang Song, … Liye Zhang·NAR Genomics and BioinformaticsPeer-reviewed·Aug 18, 2020
- Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-seq
Michael B. Cole, Davide Risso, … Nir Yosef·Cell SystemsPeer-reviewed·Apr 1, 2019
- Evaluation of RNA-seq normalization methods using challenging datasets
Severin Uebbing·bioRxiv·Aug 27, 2018