Tag Archives: Clustering

There exist numerous programs and packages that perform validation for a given clustering solution; however, clustering algorithms fare differently as judged by different validation measures. If more than one performance measure is used to evaluate multiple clustering partitions, an optimal ...

Over-representation analysis (ORA) detects enrichment of genes within biological categories. Gene Ontology (GO) domains are commonly used for gene/gene-product annotation. When ORA is employed, often times there are hundreds of statistically significant GO terms per gene set. Comparing enriched categories ...

Wellcome Trust Sanger Institute scientists and their collaborators have developed a new analysis tool that was able to show, for the first time, which genes were expressed by individual cells in different genetic versions of a benign blood cancer. Single ...

Combining single-cell genomics and computational techniques, a research team including Paul Robson, Ph.D., director of single-cell biology at The Jackson Laboratory (JAX), has defined cell-type composition of cancerous cells from 11 colorectal tumors, as well as adjacent noncancerous cells, a ...

Single-cell RNA-Sequencing (scRNA-Seq) is a fast-evolving technology that enables the understanding of biological processes at an unprecedentedly high resolution. However, well-suited bioinformatics tools to analyze the data generated from this new technology are still lacking. Here researchers from the University ...

Using single-cell RNA-seq (scRNA-seq), the full transcriptome of individual cells can be acquired, enabling a quantitative cell-type characterisation based on expression profiles. However, due to the large variability in gene expression, identifying cell types based on the transcriptome remains challenging. ...

Most existing dimensionality reduction and clustering packages for single cell RNA-Seq (scRNASeq) data deal with dropouts by heavy modelling and computational machinery. Here researchers from the Victor Chang Cardiac Research Institute introduce CIDR (Clustering through Imputation and Dimensionality Reduction), an ...

A comparison of transcriptional profiles derived from different tissues in a given species or among different species assumes that commonalities reflect evolutionarily conserved programs and that differences reflect species or tissue responses to environmental conditions or developmental program staging. Apparently ...

Analysis of the composition of heterogeneous tissue has been greatly enabled by recent developments in single-cell transcriptomics. Researchers from UCSF have developed SCell, an integrated software tool for quality filtering, normalization, feature selection, iterative dimensionality reduction, clustering and the estimation ...

Grade of membership models, also known as “admixture models”, “topic models” or “Latent Dirichlet Allocation”, are a generalization of cluster models that allow each sample to have membership in multiple clusters. These models are widely used in population genetics to ...