You need a
bioinformatician.
Sequencing is the easy part. Turning WGS and WES output into an answer clinicians can act on takes reproducible, documented pipelines, built to be re-run.
I'm a bioinformatician at IRCCS Istituto Ortopedico Rizzoli and a PhD candidate in Data Science and Computation at the University of Bologna.
The gap between data
and discovery.
I'm a bioinformatician at IRCCS Istituto Ortopedico Rizzoli (IOR) in Bologna, Italy, and a PhD candidate in Data Science and Computation at the Alma Mater Studiorum — Università di Bologna (UNIBO).
My focus is rare disease genomics: end-to-end pipelines for WGS and WES variant calling, annotation, and clinical prioritisation, with machine learning for VUS reclassification. That work produced MuSA, a Nextflow pipeline for deep variant annotation, published in BMC Bioinformatics in 2026.
Around that core I take on what the clinical environment generates: genotype-phenotype studies, patient registry cohorts, and inertial sensor analysis for gait and motion biomarkers in orthopaedic and rehabilitation work.
I treat computational infrastructure as a scientific contribution in its own right: reproducible, version-controlled, containerised, and documented.
What I work on.
Genomics
Rare Disease Genomics
End-to-end variant annotation and clinical prioritisation for Mendelian disorders. Core output: MuSA, an nf-core–compliant Nextflow pipeline integrating VEP (22 plugins), ANNOVAR, dbNSFP, RENOVO, and automated ACMG/AMP classification. Produces 920-column MAF files and interactive HTML reports for clinical review.
Collateral
Inertial Sensor Analysis
Signal processing and statistical modelling of IMU data from wearable sensors in orthopaedic and rehabilitation settings. Extracting objective gait and motion biomarkers that translate raw accelerometer and gyroscope streams into clinically actionable outcome measures.
Collateral
Clinical Data Analysis
Genotype-phenotype correlations, patient registry cohort studies, and cross-disciplinary data analyses. Whatever dataset the clinical environment generates, the approach is the same: reproducible, version-controlled, documented.
Pipelines & open-source tools.
MuSA
Multi-Source variant Annotation
nf-core–compliant Nextflow pipeline for deep variant annotation and clinical ranking. Integrates VEP (22 plugins), ANNOVAR, native dbNSFP, RENOVO scoring, and automated ACMG/AMP classification via GeneBe. Produces up to 920-column MAF files and interactive HTML reports with HPO-matched gene panel filtering. Published in BMC Bioinformatics 2026.
Career.
Reach out.
If you're working with genomics, or you have a dataset that needs a hand, reach out.
davide.scognamiglio@ior.it