Arthur Boffelli Castro
Bioinformatician & PhD Student
Functional Breast Cancer Genomics, Lund University
Investigating the functional impact of splicing factors in breast cancer using genomic and computational approaches.
Let's Connect
Bioinformatician & PhD Student
Functional Breast Cancer Genomics, Lund University
Investigating the functional impact of splicing factors in breast cancer using genomic and computational approaches.
Let's Connect
I am a PhD student in the Functional Breast Cancer Genomics group at Lund University, where I study how splicing factors influence breast cancer biology. My research uses genomic data analysis to uncover new insights into gene regulation and cancer mechanisms.
Alongside my research, I work as a systems administrator for the Bioinformatics Masters Programme at Lund University, maintaining the computational infrastructure used for teaching. I enjoy coding and building tools, whether it's exploring biological data, creating workflows, or helping students get the most out of our teaching infrastructure.
Outside of work, I enjoy playing tennis, practicing guitar, and drawing.
Genomics, Transcriptomics, Variant Analysis, Functional Annotation, Image Analysis
R, Python
tidyverse, Pandas, Data Visualization
Snakemake, Conda
Git, GitHub
Linux, Ansible, Server Management
Bash scripting, AWK, SLURM
HTML, CSS, Shiny
Developed a pipeline for detecting enlarged cancer cell nuclei in breast cancer tissue microarray (TMA) images. The workflow combines QuPath and Stardist for nuclear detection and feature extraction, with a Snakemake-based automation pipeline to streamline analysis.
The project is ongoing and the pipeline will continue to be developed by other team members. The code is publicly available on GitHub.
Source CodeA Shiny-based web application for metagenomic data exploration and visualization. Built in R using phyloseq, metacoder, and plotly, Interomics enables users to generate interactive diversity, abundance, and taxonomic tree plots directly from their data tables.
Live App Source codeDesigned and developed the official website for the Runemark Lab from scratch using HTML, CSS, and JavaScript. I handled the design, setup, and deployment, creating a fully functional and publicly accessible site for the lab.
Visit SitePerformed single-cell whole-genome sequencing (scWGS) analysis to investigate genomic instability in drug-resilient breast cancer cells. This project contributed to the publication "Drug-resilient Cancer Cell Phenotype Is Acquired via Polyploidization Associated with Early Stress Response Coupled to HIF2α Transcriptional Regulation".
The analysis pipeline was developed in Bash using established bioinformatics tools for alignment and copy number inference.
Publication Source CodeInitially developed during my Master's thesis and now extended in my PhD, this computational pipeline identifies potentially functional synonymous variants across breast cancer cohorts. The workflow integrates variant calling, annotation, and predictive modeling using GATK, VCFtools, VEP, MMSplice, and custom Python and R scripts. The pipeline pinpointed candidate variants for experimental validation and forms the foundation for ongoing functional studies.
Source CodeThis ongoing project investigates the expression and function of splicing factors across breast cancer subtypes using SCAN-B RNA-seq data. The analysis integrates gene expression, alternative isoform usage, and somatic variant data to identify regulatory changes in splicing factors and their potential impact on target gene networks.
Available upon request