Tag: RNA-Seq


[PMID: 28778180] [Genome Biology]

SuperTranscripts: a data driven reference for analysis and visualisation of transcriptomes

“Numerous methods have been developed to analyse RNA sequencing (RNA-seq) data, but most rely on the availability of a reference genome, making them unsuitable for non-model organisms. Here we present superTranscripts, a substitute for a reference genome, where each gene with multiple transcripts is represented by a single sequence. The Lace software is provided to construct superTranscripts from any set of transcripts, including de novo assemblies. “

Genomes of Metastatic Cancer

[PMID: 28783718] [Nature]

Integrative clinical genomics of metastatic cancer

“whole-exome and -transcriptome sequencing of 500 adult patients with metastatic solid tumours of diverse lineage and biopsy site. The most prevalent genes somatically altered in metastatic cancer included TP53CDKN2APTENPIK3CA, and RB1. Putative pathogenic germline variants were present in 12.2% of cases of which 75% were related to defects in DNA repair.”


[PMID:28472340] [Nucleic Acids Research]

MiSTIC, an integrated platform for the analysis of heterogeneity in large tumour transcriptome datasets

“We describe herein an interactive platform, Minimum Spanning Trees Inferred Clustering (MiSTIC), that integrates the direct visualization and comparison of the gene correlation structure between datasets, the analysis of the molecular causes underlying co-variations in gene expression in cancer samples, and the clinical annotation of tumour sets defined by the combined expression of selected biomarkers.”


[PMID:28288103] [Nature Biotechnology]

Reproducible RNA-seq analysis using recount2

“The recount2 resource summarizes expression data for genes, exons, exon–exon splice junctions and base-level coverage.” “The recount2 pipeline can be used for querying, downloading and analyzing large-scale human RNA-seq datasets across more than 70,000 samples, including all of GTEx, TCGA and the SRA. ” Work from Ben Langmead.

Census & Monocle2

[PMID:28114287] [Nature Methods]

Single-cell mRNA quantification and differential analysis with Census

“We introduce the Census algorithm to convert relative RNA-seq expression levels into relative transcript counts without the need for experimental spike-in controls… Census counts can be analyzed with widely used regression techniques to reveal changes in cell-fate-dependent gene expression, splicing patterns and allelic imbalances… Census enabled robust analysis at multiple layers of gene regulation. Census is freely available through our updated single-cell analysis toolkit, Monocle 2.”