scAmpi-A versatile pipeline for single-cell RNA-seq analysis from basics to clinics.

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful technique to decipher tissue composition at the single-cell level and to inform on disease mechanisms, tumor heterogeneity, and the state of the immune microenvironment. Although multiple methods for the computational analysis of scRNA-seq data exist, their application in a clinical setting demands standardized and reproducible workflows, targeted to extract, condense, and display the clinically relevant information. To this end, we designed scAmpi (Single Cell Analysis mRNA pipeline), a workflow that facilitates scRNA-seq analysis from raw read processing to informing on sample composition, clinically relevant gene and pathway alterations, and in silico identification of personalized candidate drug treatments.

A showcase study on personalized in silico drug response prediction based on the genetic landscape of muscle invasive bladder cancer.

Improved and cheaper molecular diagnostics allow the shift from "one size fits all" therapies to personalised treatments targeting the individual tumor. However, the wealth of potential targets based on comprehensive sequencing remains a yet unsolved challenge that prevents its routine use in clinical practice. Thus, we designed a workflow that selects the most promising treatment targets based on multi-omics sequencing and in silico drug prediction.

Genome-wide polyadenylation site mapping datasets in the rice blast fungus Magnaporthe oryzae.

Polyadenylation plays an important role in gene regulation, thus affecting a wide variety of biological processes. In the rice blast fungus Magnaporthe oryzae the cleavage factor I protein Rpb35 is required for pre-mRNA polyadenylation and fungal virulence. Here we present the bioinformatic approach and output data related to a global survey of polyadenylation site usage in M.