SUMMARY: bollito is an automated, flexible and parallelizable computational pipeline for the comprehensive analysis of single-cell RNA-seq data. Starting from FASTQ files or preprocessed expression matrices, bollito performs both basic and advanced tasks in single-cell analysis integrating >30 state-of-the-art tools. This includes quality control, read alignment, dimensionality reduction, clustering, cell-marker detection, differential expression, functional analysis, trajectory inference and RNA velocity. bollito is built using the Snakemake workflow management system, which easily connects each execution step and facilitates the reproducibility of results. bollito's modular design makes it easy to incorporate other packages into the pipeline enabling its expansion with new functionalities. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://gitlab.com/bu_cnio/bollito under the MIT license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Genetic alterations lead to tumor progression and cell survival but also uncover cancer-specific vulnerabilities on gene dependencies that can be therapeutically exploited. RESULTS: vulcanSpot is a novel computational approach implemented to expand the therapeutic options in cancer beyond known-driver genes unlocking alternative ways to target undruggable genes. The method integrates genome-wide information provided by massive screening experiments to detect genetic vulnerabilities associated to tumors. Then, vulcanSpot prioritizes drugs to target cancer-specific gene dependencies using a weighted scoring system based on well known drug-gene relationships and drug repositioning strategies. AVAILABILITY AND IMPLEMENTATION: http://www.vulcanspot.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.