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Open AccessJournal ArticleDOI

CEL-Seq: Single-Cell RNA-Seq by Multiplexed Linear Amplification

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TLDR
It is shown that CEL-Seq gives more reproducible, linear, and sensitive results than a PCR-based amplification method, and will be useful for transcriptomic analyses of complex tissues containing populations of diverse cell types.
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This article is published in Cell Reports.The article was published on 2012-09-27 and is currently open access. It has received 1166 citations till now. The article focuses on the topics: RNA-Seq & Gene expression.

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Citations
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The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells

TL;DR: Monocle is described, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points that revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation.
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Spatial reconstruction of single-cell gene expression data

TL;DR: Seurat is a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns, and correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups.
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Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells

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.
References
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Journal ArticleDOI

The Sequence Alignment/Map format and SAMtools

TL;DR: SAMtools as discussed by the authors implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.
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Matplotlib: A 2D Graphics Environment

TL;DR: Matplotlib is a 2D graphics package used for Python for application development, interactive scripting, and publication-quality image generation across user interfaces and operating systems.
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BEDTools: a flexible suite of utilities for comparing genomic features

TL;DR: A new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format, which allows the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks.
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Embryonic Stem Cell Lines Derived from Human Blastocysts

TL;DR: Human blastocyst-derived, pluripotent cell lines are described that have normal karyotypes, express high levels of telomerase activity, and express cell surface markers that characterize primate embryonic stem cells but do not characterize other early lineages.
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RNA-Seq: a revolutionary tool for transcriptomics

TL;DR: The RNA-Seq approach to transcriptome profiling that uses deep-sequencing technologies provides a far more precise measurement of levels of transcripts and their isoforms than other methods.
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