Hi there, I'm Kamil 👋

I work as a biomedical researcher at Mass General Brigham, where I focus on statistical analysis for projects that involve millions of cells from hundreds of patient samples.

My research experience is in the fields of human genetics, functional genomics, and immunology. I specialize in the analysis of single-cell transcriptomics data (scRNA-seq).

In other words, I study data that tells us what cells are doing at the molecular level, and I compare the cells from different people to find out what might be happening in the context of diseases like rheumatoid arthritis, immunotherapy-related colitis, and COVID-19.

I also have research experience in human genetics, with a focus on immunology and the human leukocyte antigen (HLA) genes.

• Check out my latest single-cell data browser: Cell Guide

• Browse datasets from recent publications: Immunogenomics.io

Single cell RNA-seq data 170k cells from 350 patients. Each point represents a cell. Color represents a cell's assignment to a cluster of cells, based on its similarity to other cells. Each cell is embedded in 3 dimensions based on its gene expression profile. (Make your own animation in R.) Harmony can help to integrate many batches of high-dimensional data (R package or Python package).

A human HLA-TCR complex (6py2) Two human proteins. The HLA protein (pink and purple subunits) is at the bottom and it is presenting a peptide (green) to the TCR protein (orange and yellow subunits) on top. The peptide is a fragment of the glutenin protein from wheat flour. This presentation mechanism is the basis for our adaptive immunity that protects us from pathogens and cancers, but it can also make us susceptible to autoimmune diseases. Find tools and databases for analyzing HLA and VDJ genes at slowkow/awesome-vdj.