HCA Data Explorer

Benchmarking Single-Cell RNA Sequencing Protocols for Cell Atlas Projects

Updated April 5, 2023

Single-cell RNA sequencing (scRNA-seq) is the leading technique for charting the molecular properties of individual cells. The latest methods are scalable to thousands of cells, enabling in- depth characterization of sample composition without prior knowledge. However, there are important differences between scRNA-seq techniques, and it remains unclear which are the most suitable protocols for drawing cell atlases of tissues, organs and organisms. We have generated benchmark datasets to systematically evaluate techniques in terms of their power to comprehensively describe cell types and states. We performed a multi-center study comparing 13 commonly used single-cell and single-nucleus RNA-seq protocols using a highly heterogeneous reference sample resource. Comparative and integrative analysis at cell type and state level revealed marked differences in protocol performance, highlighting a series of key features for cell atlas projects. These should be considered when defining guidelines and standards for international consortia, such as the Human Cell Atlas project. Overall design: The samples consists of two complex tissues (human PBMC and mouse colon) and three cell lines (HEK293-RFP, NIH3T3-GFP, MDCK-Turbo650). The primary PBMC and the colon sample constitute 90% and the cell lines 10%. The sample preparation aims to be standardized for all methods to allow a comparison of library preparation performance (6% HEK293T-RFP, 3% NIH3T3-GFP, 1% MDCK-Turbo650) of the sample content.

Holger HeynCNAG-CRG, Centre for Genomic Regulation (CRG)holger.heyn@cnag.crg.eu
Elisabetta Mereu1
Atefeh Lafzi1
Catia Moutinho1
Christoph Ziegenhain2
Davis J McCarthy3
Adrián Álvarez-Varela4
Eduard Batlle4
Sagar 5
Dominic Grün5
Julia K Lau6
Stéphane C Boutet6
Chad Sanada7
Aik Ooi7
Robert C Jones8
Kelly Kaihara9
Chris Brampton9
Yasha Talaga9
Yohei Sasagawa10
Kaori Tanaka10
Tetsutaro Hayashi10
Caroline Braeuning11
Cornelius Fischer11
Sascha Sauer11
Timo Trefzer12
Christian Conrad12
Xian Adiconis13
Lan T Nguyen13
Aviv Regev13
Joshua Z Levin13
Swati Parekh14
Aleksandar Janjic15
Lucas E Wange15
Johannes W Bagnoli15
Wolfgang Enard15
Marta Gut1
Rickard Sandberg2
Itoshi Nikaido10
Ivo Gut1
Oliver Stegle3
Holger Heyn1
1CNAG-CRG, Centre for Genomic Regulation (CRG)
2Karolinska Institutet
3EMBL-EBI
4Institute for Research in Biomedicine, Barcelona Institute of Science and Technology
5Max-Planck-Institute of Immunobiology and Epigenetics
610x Genomics
7Fluidigm Corporation
8Stanford University
9Bio-Rad
10RIKEN Center for Biosystems, Dynamics Research
11Max Delbrück Center for Molecular Medicine/Berlin Institute of Health
12Berlin Institute of Health, Charité-Universitätsmedizin Berlin
13Klarman Cell Observatory, Broad Institute of MIT and Harvard
14Max-Planck-Institute for Biology of Ageing
15Ludwig-Maximilians-University
Ami Day
Ida Zucchi

To reference this project, please use the following link:

https://explore.data.humancellatlas.dev.clevercanary.com/projects/6e177195-0ac0-468b-99a2-87de96dc9db4
None
INSDC Project Accessions:
SRP212637, SRP212638, SRP212639, SRP212640, SRP212641, SRP212642, SRP212643, SRP212644, SRP212645, SRP212646, SRP212647, SRP212648, SRP212649, SRP212651, SRP234722
GEO Series Accessions:INSDC Study Accessions:

Atlas

None

Analysis Portals

None

Project Label

BenchmarkingSingleCellProtocols

Species

3 species

Sample Type

2 sample types

Anatomical Entity

4 anatomical entities

Organ Part

Unspecified

Selected Cell Types

Unspecified

Model Organ

2 model organs

Disease Status (Specimen)

normal

Disease Status (Donor)

normal

Development Stage

2 development stages

Library Construction Method

12 library construction methods

Nucleic Acid Source

2 nucleic acid sources

Paired End

false, true

Analysis Protocol

analysis_protocol_raw

File Format

3 file formats

Cell Count Estimate

50.6k

Donor Count

18
fastq.gz764 file(s)tsv.gz60 file(s)xlsx2 file(s)