Tag Archives: University of Washington

New technology enables single cell analysis of mouse embryonic development Scientists from Seattle and Berlin have published an atlas on mouse embryonic...

To facilitate scalable profiling of single cells, engineers at the University of Washington have developed split-pool ligation-based transcriptome sequencing (SPLiT-seq), a single-cell RNA-seq (scRNA-seq) method that labels the cellular origin of RNA through combinatorial barcoding. SPLiT-seq is compatible with fixed ...

Bioinformatics publications typically include complex software workflows that are difficult to describe in a manuscript. University of Washington, Tacoma researchers describe and demonstrate the use of interactive software notebooks to document and distribute bioinformatics research. They provide a user-friendly tool, ...

To resolve cellular heterogeneity, researchers from the University of Washington developed a combinatorial indexing strategy to profile the transcriptomes of single cells or nuclei, termed sci-RNA-seq (single-cell combinatorial indexing RNA sequencing). They applied sci-RNA-seq to profile nearly 50,000 cells from ...

Single cell RNA-seq (scRNA-seq) experiments can provide a wealth of information about heterogeneous, multi-cellular systems. However, this information has to be inferred computationally from sequencing reads which constitute a sparse and noisy sub-sampling of the actual cellular transcriptomes. Here, University ...

RNA-Seq has supplanted microarrays as the preferred method of transcriptome-wide identification of differentially expressed genes. However, RNA-Seq analysis is still rapidly evolving, with a large number of tools available for each of the three major processing steps: read alignment, expression ...

Single-cell gene expression studies promise to reveal rare cell types and cryptic states, but the high variability of single-cell RNA-seq measurements frustrates efforts to assay transcriptional differences between cells. University of Washington researchers have developed the Census algorithm to convert ...

RNA-Seq has supplanted microarrays as the preferred method of transcriptome-wide identification of differentially expressed genes. However, RNA-Seq analysis is still rapidly evolving, with a large number of tools available for each of the three major processing steps: read alignment, expression ...

While RNA-Seq has enabled great progress towards the goal of wide-scale isoform-level mRNA quantification, short reads have limitations when resolving complex or similar sets of isoforms. As a result, estimates of isoform abundance carry far more uncertainty than those made ...

Gene expression levels are dynamic molecular phenotypes that respond to biological, environmental, and technical perturbations. Here, University of Washington researchers use a novel replicate classifier approach for discovering transcriptional signatures and apply it to the Genotype-Tissue Expression (GTEx) data set. ...