Diego M. Coelho

Founder

Fast and Integraded Genomics Association•  December 2021 - Present

Development of bioinformatics pipelines using workflow languages (WDL and Nextflow), Docker and cloud computing (AWS and GCP). Focus on: * RNAseq / scRNAseq; * WES, WGS, Array; * System Biology; * Experimental design, data visualization;

Software Engineer

EMBL•  January 2022 - April 2023

• As a member of Variation team, we develop new tools to VEP (variant effect predictor) while refactor and adjust old functionalities. Also, as part of our team tasks, we update our databases analysis every trimester release. • Integrated new databases to our main tool, making users avoid get terabytes of information to have key information about populational data. • Refactored part of our main pipelines which facilitates our trimester releases bottlenecks saving up to 90% of the pipeline time. • Daily programming in perl, SQL, python, shell.

Bioinformatics Analyst

Mendelics•  February 2020 - December 2021

• One of the responsible to maintain our GCP environment running to analyze our patients data. Our workflow process more than 1500 exomes per month. • Created a statistical metric to avoid usage of low-coverage samples. This KPI accelerated sample results in failing cases and avoided unnecessary processing of patient data. • As part of R&D team, I was principal responsible to developed a new private python tool to classify haplotypes in pharmacogenetics genes using whole- exome sequencing data. Fully dockerized and had an easy CLI to use. This generated a new demand in our company with international pharmaceuticals companies. • My daily demand programming in R, python, SQL, shell.

Universidade Federal do Rio Grande do Norte

Bioinformatics, PhD•  May 2016 - May 2021

• In my PhD work, I reprocessed three large different datasets for Alzheimer’s disease. Our work resulted in a publication (Marques-Coelho et al, 2021). • In our research team, assisted in several publications, mining and analyzing already published data (Github: Guimarães et al, 2018 e Alves et al, 2018). Also have several publications with our lab colleagues (Kilinc et al, 2020). • All analysis were performed in R and Python.

Johns Hopkins University

Neuroscience, PhD•  June 2017 - August 2018

• Managed bioinformatics data of three distinct projects about neurodevelopment. Further, built a platform in RShiny to facilitate access to analyzed data. Also created several Jupyter and RMarkdown reports. • Our efforts resulted in a few publications (Fabra-besser et al, 2021; Accepted: Alves et al, 2021). • My daily programming work were in R and shell; sometimes in python.