4.8 Article

Scalable single-cell RNA sequencing from full transcripts with Smart-seq3xpress

Related references

Note: Only part of the references are listed.
Article Biochemical Research Methods

Molecular spikes: a gold standard for single-cell RNA counting

Christoph Ziegenhain et al.

Summary: This study introduces a strategy using molecular spikes with unique molecular identifiers (UMIs) to evaluate the accuracy of RNA counting in single-cell sequencing. The authors uncover and correct impaired counting methods, as well as improve estimates of cellular mRNA amounts. These molecular spikes and the accompanying software will benefit the validation of new methods and enable more accurate characterization of RNA counting in single-cell sequencing.

NATURE METHODS (2022)

Article Biochemical Research Methods

Cellsnp-lite: an efficient tool for genotyping single cells

Xianjie Huang et al.

Summary: Single-cell sequencing is increasingly popular, but current genotyping methods for single-cell data need improvement. Cellsnp-lite, a software based on htslib, shows significant improvements in computational speed and memory efficiency, making genetic analysis easier for expanding single-cell datasets.

BIOINFORMATICS (2021)

Article Biochemical Research Methods

High-throughput full-length single-cell RNA-seq automation

Lira Mamanova et al.

Summary: Existing protocols for full-length single-cell RNA sequencing produce high-complexity libraries with outstanding sensitivity and specificity. These libraries allow probing of transcript isoforms and are informative regarding single-nucleotide polymorphisms. However, scalability and cost have limited their popularity as compared with other approaches.

NATURE PROTOCOLS (2021)

Article Biochemistry & Molecular Biology

Integrated analysis of multimodal single-cell data

Yuhan Hao et al.

Summary: The study introduces a weighted-nearest neighbor analysis framework to learn the relative utility of each data type in each cell, enabling integrative analysis of multiple modalities. Applied to a CITE-seq dataset, the method constructs a multimodal reference atlas of the circulating immune system and successfully identifies and validates previously unreported lymphoid subpopulations.
Article Biotechnology & Applied Microbiology

BRIE2: computational identification of splicing phenotypes from single-cell transcriptomic experiments

Yuanhua Huang et al.

Summary: RNA splicing plays a crucial role in driving heterogeneity in single cells through alternative transcript expression and transcriptional kinetics. BRIE2, a scalable computational method, effectively identifies differential disease-associated alternative splicing events and improves RNA velocity analysis, enabling exploration of the association between splicing phenotypes and biological changes.

GENOME BIOLOGY (2021)

Article Biotechnology & Applied Microbiology

Single-cell RNA counting at allele and isoform resolution using Smart-seq3

Michael Hagemann-Jensen et al.

NATURE BIOTECHNOLOGY (2020)

Article Biotechnology & Applied Microbiology

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

Elisabetta Mereu et al.

NATURE BIOTECHNOLOGY (2020)

Article Biochemical Research Methods

Scirpy: a Scanpy extension for analyzing single-cell T-cell receptor-sequencing data

Gregor Sturm et al.

BIOINFORMATICS (2020)

Article Biochemistry & Molecular Biology

Solo: Doublet Identification in Single-Cell RNA-Seq via Semi-Supervised Deep Learning

Nicholas J. Bernstein et al.

CELL SYSTEMS (2020)

Article Biochemical Research Methods

Miniaturization of Smart-seq2 for Single-Cell and Single- Nucleus RNA Sequencing

Baptiste N. Jaeger et al.

STAR PROTOCOLS (2020)

Article Multidisciplinary Sciences

Miniaturization and optimization of 384-well compatible RNA sequencing library preparation

Madeline Y. Mayday et al.

PLOS ONE (2019)

Article Multidisciplinary Sciences

RNA velocity of single cells

Gioele La Manno et al.

NATURE (2018)

Article Multidisciplinary Sciences

Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris

Nicholas Schaum et al.

NATURE (2018)

Article Biotechnology & Applied Microbiology

SCANPY: large-scale single-cell gene expression data analysis

F. Alexander Wolf et al.

GENOME BIOLOGY (2018)

Article Biochemical Research Methods

T cell fate and clonality inference from single-cell transcriptomes

Michael J. T. Stubbington et al.

NATURE METHODS (2016)

Article Biochemistry & Molecular Biology

Tn5 transposase and tagmentation procedures for massively scaled sequencing projects

Simone Picelli et al.

GENOME RESEARCH (2014)

Article Biochemical Research Methods

Smart-seq2 for sensitive full-length transcriptome profiling in single cells

Simone Picelli et al.

NATURE METHODS (2013)

Article Biochemistry & Molecular Biology

Suppression of artifacts and barcode bias in high-throughput transcriptome analyses utilizing template switching

Dave T. P. Tang et al.

NUCLEIC ACIDS RESEARCH (2013)