Nature

Alva Rani James, PhD
Bioinformatican

Experienced Bioinformatician Specializing in Bioinformatics Pipeline Development and Multiomics Next-Generation Sequencing Analysis for Disease Research. Proficient in Python, R, SQL, Machine Learning, and Deep Learning Techniques.

Senior Bioinformatics scientist

Over the past eight years, I had the opportunity to work closely with prestigious institutions across Europe, including the Karolinska Institute in Sweden, Charité Medical University in Berlin, Germany, ETH Zurich in Switzerland, University Hospital Zurich, and the Hasso Plattner Institute in Germany. In addition to these academic engagements, I also interned with leading pharmaceutical company AstraZeneca. Currently, I am engaged in a diagnostic biotech company, where I serve as a bioinformatics data scientist operating within the pharmaceutical domain.

Decoding Genetic Variants: Advancing Variant Classification with Nextflow Pipeline for the UK Biobank Exon-seq Dataset

The classification of UK Biobank Exon-seq variants is achieved through the utilization of Ensemble Variant Effect Predictor (VEP). This robust pipeline is implemented in a scalable and reproducible Nextflow workflow, ensuring both reliability and efficiency. Furthermore, the use of a Docker container guarantees the reproducibility and consistency of results.

Unveiling Insights: Exploring RNA-seq and Single-cell Sequencing Datasets from Skin Cancer Patients

The tumor profiler project, which was carried out at ETH Zurich and generously funded by Roche. As part of the team, I actively contributed to the development of the pipeline specifically designed for RNA-seq and single-cell data analysis, encompassing the entire workflow from processing raw fastq files to calculating hypoxia scores. This involved implementing robust methodologies and incorporating cutting-edge techniques to ensure accurate and comprehensive results.

Other projects

The other projects, I have actively contributed, RIP-seq data analysis on breast cancer, DNA-seq, RNA-seq, and proteomics data analysis on leukemia patients.