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saraalv/README.md

Hi, I'm Sara Álvarez 👋

Bioinformatics & Biostatistics

MSc in Bioinformatics & Biostatistics with an interest in computational biology, statistical modelling and biological data analysis.

I use R and Python to explore, analyse and visualize scientific data, with a particular interest in genomics and reproducible research.

🔬 What I work with

  • 🧬 Gene-expression and genomic data
  • 📊 Statistical modelling and regression
  • 📈 Exploratory data analysis and visualization
  • 🐍 Python for scientific computing
  • 📐 R for statistical analysis
  • 🔬 PCA and batch-effect analysis
  • 📓 Jupyter Notebook & R Markdown

🚀 Featured projects

Project What I did Technologies
🧬 Stemness & Immune Evasion in Breast Cancer Multi-omics analysis & ML · Master's Thesis R · RNA-seq · WGCNA · Random Forest
🧬 Skin Cancer Subtyping RNA-seq classification R · Machine Learning · Random Forest · SVM
📊 DMD Biomarkers Statistical biomarker analysis R · Biostatistics · Regression
🧬 Bioinformatics Sequence Analysis Sequence & phylogenetic analysis Python · Biopython · FASTA
🧪 Bioinformatics Software Testing Scientific software testing Python · Unit Testing · Error Handling

🛠️ Tech stack

Languages

Python R

Data & Statistics

Regression Statistical Modelling Hypothesis Testing EDA Data Visualization

Bioinformatics

Gene Expression Genomics GEO PCA Batch Effects

Scientific Python

NumPy SciPy Matplotlib Jupyter

🎓 Background

My portfolio is built from projects developed during my MSc in Bioinformatics & Biostatistics, reorganized into reproducible, portfolio-oriented analyses.

📫 Let's connect

LinkedIn · Email

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  1. stemness-immune-evasion-breast-cancer stemness-immune-evasion-breast-cancer Public

    Master's Thesis: multi-omics analysis of cancer stemness and immune evasion in breast cancer using gene signatures, WGCNA and machine learning.

    R

  2. SkinSubtyping-RNAseq SkinSubtyping-RNAseq Public

    Machine learning models for classifying skin cancer subtypes from RNA-seq gene expression data, including k-NN, Naive Bayes, neural networks, SVM, decision trees and Random Forest.

    HTML

  3. dmd-biomarkers dmd-biomarkers Public

    Statistical analysis of biomarkers associated with Duchenne muscular dystrophy using R, exploratory data analysis, correlation and regression models.

    HTML

  4. bioinformatics-sequence-analysis bioinformatics-sequence-analysis Public

    Python and Biopython workflows for biological sequence analysis, including FASTA processing, nucleotide composition, motif detection, mutations, phylogenetics and sequence alignment.

    Jupyter Notebook

  5. bioinformatics-software-testing bioinformatics-software-testing Public

    This project demonstrates unit testing and error handling for Python functions working with peptide sequences.

    Python