scispace - formally typeset
Topic

Single cell sequencing

About: Single cell sequencing is a(n) research topic. Over the lifetime, 1064 publication(s) have been published within this topic receiving 82543 citation(s).
Papers
More filters

Journal ArticleDOI
TL;DR: SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies.
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V−SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online (http://bioinf.spbau.ru/spades). It is distributed as open source software.

12,399 citations


01 Jun 2012-
Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

10,124 citations


Journal ArticleDOI
21 May 2015-Cell
TL;DR: Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together.
Abstract: Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution. VIDEO ABSTRACT.

4,167 citations


Journal ArticleDOI
01 Sep 2008-Genome Research
TL;DR: It is found that the Illumina sequencing data are highly replicable, with relatively little technical variation, and thus, for many purposes, it may suffice to sequence each mRNA sample only once (i.e., using one lane).
Abstract: Ultra-high-throughput sequencing is emerging as an attractive alternative to microarrays for genotyping, analysis of methylation patterns, and identification of transcription factor binding sites. Here, we describe an application of the Illumina sequencing (formerly Solexa sequencing) platform to study mRNA expression levels. Our goals were to estimate technical variance associated with Illumina sequencing in this context and to compare its ability to identify differentially expressed genes with existing array technologies. To do so, we estimated gene expression differences between liver and kidney RNA samples using multiple sequencing replicates, and compared the sequencing data to results obtained from Affymetrix arrays using the same RNA samples. We find that the Illumina sequencing data are highly replicable, with relatively little technical variation, and thus, for many purposes, it may suffice to sequence each mRNA sample only once (i.e., using one lane). The information in a single lane of Illumina sequencing data appears comparable to that in a single array in enabling identification of differentially expressed genes, while allowing for additional analyses such as detection of low-expressed genes, alternative splice variants, and novel transcripts. Based on our observations, we propose an empirical protocol and a statistical framework for the analysis of gene expression using ultra-high-throughput sequencing technology.

2,699 citations


Journal ArticleDOI
21 May 2015-Cell
TL;DR: This work has developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing, which shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays.
Abstract: It has long been the dream of biologists to map gene expression at the single-cell level With such data one might track heterogeneous cell sub-populations, and infer regulatory relationships between genes and pathways Recently, RNA sequencing has achieved single-cell resolution What is limiting is an effective way to routinely isolate and process large numbers of individual cells for quantitative in-depth sequencing We have developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing The method shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays We analyzed mouse embryonic stem cells, revealing in detail the population structure and the heterogeneous onset of differentiation after leukemia inhibitory factor (LIF) withdrawal The reproducibility of these high-throughput single-cell data allowed us to deconstruct cell populations and infer gene expression relationships VIDEO ABSTRACT

2,293 citations


Network Information
Related Topics (5)
Epigenetics

38.1K papers, 1.7M citations

87% related
Deep sequencing

3.7K papers, 189.1K citations

87% related
DNA methylation

49.8K papers, 2.5M citations

86% related
Epigenome

4.8K papers, 221.1K citations

86% related
Epigenomics

9K papers, 734.4K citations

86% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20222
2021150
2020124
201974
201886
2017105

Top Attributes

Show by:

Topic's top 5 most impactful authors

Marlon Stoeckius

4 papers, 1.4K citations

Alexander Krasnitz

4 papers, 2.3K citations

Timour Baslan

4 papers, 307 citations

Peter Smibert

4 papers, 1.4K citations

Rahul Satija

4 papers, 1.4K citations