Current best practices in single‐cell RNA‐seq analysis: a tutorial | Molecular Systems Biology
Please check your email for instructions on resetting your password. If you do not receive an email within 10 minutes, your email address may not be registered, and you may need to create a new Wiley Online Library account. If the address matches an existing account you will receive an email with instructions to retrieve your username Malte D Luecken Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany Search for more papers by this author Corresponding Author Fabian J Theis Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany Department of Mathematics, Technische Universität München, Garching bei München, Germany Search for more papers by this author Malte D Luecken Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Ge
Current best practices in single‐cell RNA‐seq analysis: a tutorial Review Open access Published: 19 June 2019 Volume 15 , article number MSB188746 ( 2019 ) Cite this article You have full access to this open access article Download PDF Save article View saved research Molecular Systems Biology Aims and scope Submit manuscript Current best practices in single‐cell RNA‐seq analysis: a tutorial Download PDF Abstract Single‐cell RNA‐seq has enabled gene expression to be studied at an unprecedented resolution. The promise of this technology is attracting a growing user base for single‐cell analysis
related reading
- Quantifying the effect of experimental perturbations at single-cell resolutionnature.com
- A survey of best practices for RNA-seq data analysisgenomebiology.biomedcentral.com
- Signature-scoring methods developed for bulk samples are not adequate for cancer single-cell RNA sequencing data | eLifeelifesciences.org
- 10. Feature selection — Single-cell best practicessc-best-practices.org
- scGen predicts single-cell perturbation responsesnature.com
- Evaluating the role of pretraining dataset size and diversity on single-cell foundation model performancenature.com
- Strategies for cellular decision‐making | Molecular Systems Biology | Springer Nature Linkembopress.org
- The art of using t-SNE for single-cell transcriptomicsnature.com
- Predicting cellular responses to complex perturbations in high‐throughput screens | Molecular Systems Biology | Springer Nature Linkembopress.org
- Somatic mutation landscapes at single-molecule resolutionnature.com
- Chapter 3 Feature selection | Basics of Single-Cell Analysis with Bioconductorbioconductor.org
- Publicationsbintulab.com