Francesco Strino

The QIAGEN CLC Microbial Genomics Module module extends the capabilities of the QIAGEN CLC Genomics Workbench to support the analysis of bacterial, viral, and eukaryotic (fungal) genomes and metagenomes. It offers tools and workflows for a broad range of bioinformatics needs for microbiome analysis, isolate characterization, functional metagenomics, and resistance identification.

I developed tools for performing OTU clustering, including demultiplexing, clustering, statistical analyses (i.e., alpha/beta diversity, PERMANOVA, differential abundance), and visualization. I also developed most of the current pipeline in the Microbial Genomics Module or functional annotation of metagenomic sequences, i.e., a gene finder to annotate nucleotide sequences using a variable-order Markov model and differential functional abundance.

I was the main developer of the CLC shape-based peak caller, a tool used to identify narrow and broad peaks in sequencing data using shape information.

The tool implements all the signal detection steps, quality control, normalization, discovering obvious peaks, learning the peak shape, peak shape score, and peak detection in a single, easy-to-use algorithm. The algorithm delivers a QC report containing metrics about the ChIP-seq experiment's quality, a peak shape score value for every genomic position, and a list of all called peaks.

A performance evaluation showed that the CLC shape-based peak caller ranks well among popular state-of-the-art peak callers while requiring a minimum intervention and parameterization from the user.

I was the principal author of TrAp, a tool designed to infer subclonal tumor composition in human patients from sequencing data using a few biologically motivated constraints.

More information is available in the paper at doi.org/10.1093/nar/gkt641.