Single-cell RNA-Seq Gaining Steam

rna-seq The unique genetic makeup of myeloma tumor cells revealed by single cell RNA-Seq (12/7/2018) - Cancer arises when cells lose control. Deciphering the "blueprint" of cancer cells - outlining how cancer cells hijack specific pathways for uncontrolled proliferation - will lead to more efficient ways to fight it. Joint effort of scientists from the Weizmann Institute of Science and clinicians from major hemato-oncology departments in Israel succeeded...
rna-seq Advantages of single-nucleus over single-cell RNA sequencing of adult kidney (12/6/2018) - A challenge for single-cell genomic studies in kidney and other solid tissues is generating a high-quality single-cell suspension that contains rare or difficult-to-dissociate cell types and is free of both RNA degradation and artifactual transcriptional stress...
RNA Sequencing gives new insights into formation of neurons in mammalian adult brain (12/6/2018) - A team of researchers at Baylor College of Medicine, the Texas Heart Institute and Texas Children’s Hospital has developed a powerful new approach to understand the formation of new neurons in the mammalian adult brain. Published in the journal...
rna-seq Analyzing single-cell landscapes (12/4/2018) - Single-cell RNA sequencing is a powerful tool for studying cellular diversity, for example in cancer where varied tumor cell types determine diagnosis, prognosis and response to therapy. Single-cell technologies generate hundreds to thousands...
FiRE (Finder of Rare Entities) – A fast and efficient method to find rare cell types in scRNA-seq expression profiles (11/30/2018) - The advent of single-cell transcriptomics has made rare cell discovery a mainstream component in the downstream analysis pipeline. When the number of profiled cells are in the hundreds, even an outlier cell (singleton) deserves attention. But, the focus shifts to the discovery of minor cell types rather than mere singletons when profiled cells are in ...
rna-seq GERAS – machine learning based classification of cells into chronological stages using single-cell transcriptomics (11/29/2018) - Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular age are limited, as they rely on a limited set of histological markers and lack predictive power. Here, a team led by researchers at ...
Bioinformatics Improves Retrieval of Single Cell RNA Sequencing Data (11/26/2018) - In the era of personalized medicine, scientists are using new genetic and genomic insights to help them determine the best treatment for a given patient. In the case of cancer, the first step toward these treatments is an investigation into how tumor cells behave...
BioLegend partners on TotalSeqTM antibodies to boost single cell surface protein profiling within VIB (11/15/2018) - BioLegend partners on TotalSeqTM antibodies to boost single cell surface protein profiling within VIB BioLegend, a world-class antibody provider, announced today a new partnership with VIB, a leading life science research institute in Flanders (Belgium), to evaluate and implement the TotalSeqTM antibodies for next-generation multi-omics by the combining single cell transcriptomics with single cell proteomics ...
rna-seq Upcoming Workshop – Analysis of single cell RNA-seq data (11/1/2018) - 25 February-1 March 2019 In recent years single-cell RNA-seq (scRNA-seq) has become widely used for transcriptome analysis in many areas of biology. In contrast to bulk RNA-seq, scRNA-seq provides ...
rna-seq Single cell RNA-seq data clustering using TF-IDF based methods (10/30/2018) - Single cell transcriptomics is critical for understanding cellular heterogeneity and identification of novel cell types. Leveraging the recent advances in single cell RNA sequencing (scRNA-Seq) technology requires novel unsupervised...

A slew of recent high profile papers and upcoming conferences highlight the growing interest in single-cell transcriptomics.