Kamil Slowikowski

@slowkow.com

646 Followers 2208 Following

Computational biologist 🧬🖥️ at Mass General Brigham and Broad Institute, PhD at Harvard. Bioinformatics, transcriptomics, COVID, genomics, immunology, genetics, statistics, and web development. I made #ggrepel and I blog at https://slowkow.com

Animation of a data visualization that shows the average resting heart rate of people in Germany as a line plot on the left. The right shows a map of Germany with districts, and color is used to represent the average heart rate of people within each district. In the line plot, a vertical line moves from left to right to indicate which time point is currently being displayed on the map. Data from: https://corona-datenspende.github.io/en/vitaldata-tool/

**M.** Volcano plot for convalescent CD4 T cell subset 6 (Treg).
Dots indicate genes, x-axis indicates fold-change, y-axis indicates negative log10 p-value from multivariate linear regression.
Red color indicates FDR < 5%.

**N.** Box plot of *ICOS* gene expression in CD4 T cell subset 6 (Treg) in the convalescent data.
Fold-change and p-value is shown.
Dots represent patients, box plots indicate median and interquartile range, x-axis and hue represent convalescent COVID infection.

**O.** Box plot of *ICOS* gene expression in CD4 T cell subset 13 (Treg) in the acute data.
Dots represent patients, box plots indicate median and interquartile range, x-axis represents time point, and hue represents COVID infection.

**E.** Amino acid position associations with COVID severity for HLA-DQB1.
x-axis indicates position along the gene.
y-axis indicates negative log10 p-value from multivariate linear regression.
Black color indicates FDR < 5%.

**F.** Coefficients from the multivariate linear regression for the effect size of each amino acid position on COVID severity.
Amino acid positions D57 and V57 are highlighted.
Error bars indicate 95% CI.

**G.** Bar plots of the number of patients with each genotype.
Facets indicate genotype (0, 1, 2) for amino acid position D57 (top) and V57 (bottom).
x-axis indicates number of patients.
Hue indicates COVID severity.

**H.** Box plot of abundance of CD8 T cells with TRBV28, x-axis indicates time point and hue indicates genotype of HLA-DQB1 V57 (0, 1, 2).
P-value from multivariate linear regression.

A scatter plot where each point represents a gene. The x-axis represents the fold-change of the gene in acute patients who received tocilizumab treatment, where genes induced after treatment are seen on the right and genes repressed after treatment are seen on the left. The y-axis represents the fold-change of the gene in acute patients, where genes associated with worse severity are seen on the top, and genes associated with lesser severity are seeon on the bottom. Some genes are labeled.

A schematic that shows some factors associated with the severity of COVID-19. Starting with SARS-CoV-2 infection, the adaptive immune response should lead to successful elimination and convalescence. In some patients, various factors such as viral titer, age, autoantibodies, lymphopenia, serum IL-6 levels, TCR and BCR clones, and HLA genotypes can increase risk for severe disease. This leads to a feedback loop wherein lack of viral clearance leads to increased tissue damage. This is associated with myeloid cell dysfunction marked by impaired antigen presentation, which drives a non-productive adaptive immune response, as reflected by reduced expression of B and T cell gene programs involved in antigen recognition, immune synapse formation, and cytotoxicity. The anti-IL-6R antibody, tocilizumab, appears to reverse the mRNA signature of disease severity in myeloid cells.

Overview of a research study about COVID-19. The study includes three cohorts: (1) 351 acute COVID-19 patients across 5 severity levels and 3 time points profiled by multiple modalities, (2) 4 acute COVID-19 patients treated with tocilizumab, (3) 73 patients, 43 of whom were previously infected with SARS-CoV-2 3 months ago. The overview shows the general study design and visualizations of the single-cell RNA sequencing data analyzed in this study.

A screen recording of a web app called Visual Search that allows uers to search Pubmed or Semantic Scholar and view the results on a 2D embedding. Each point represents a paper, and similar papers are near each other. Colors indicate clusters of similar papers.

A graph from a 1993 article published in the New England Journal of Medicine illustrating the relationship between air pollution and mortality rates in six U.S. cities. The x-axis represents the concentration of fine particles (µg/m³), while the y-axis shows the adjusted mortality-rate ratios. Cities such as Steubenville, OH, and Portage, WI, are marked. The adjusted mortality rate for the most polluted of the cities (Steubenville, OH) is 1.26 times higher than the morality rate least polluted city (Portage, WI). Data from Dockery et al., NEJM 1993.

Today, I watch with deep sadness as the United States’ remarkable scientific enterprise, which took generations of hard work and national investment to build, faces a concerted dismantling by the current administration.

American science is the envy of the world, but this global leadership is now threatened by draconian cuts to federal support of biomedical research through the defunding of grants and drastic reductions in funding for essential research costs and infrastructure.

This will have catastrophic consequences for the US biomedical research and medical sector, choking off the next generation of medical advances and undermining our global competitiveness at a time when other countries are working hard to overtake us.

— Ardem Patapoutian, Nobel laureate

Airborne Infection Prevention Using Germicidal UV-C: Training and Certification Program. August 2025 in College Park, Maryland. Designed by Dr. Rolf Bergman, Dr. Paul Jensen, and Dr. David Sliney. In an era of resurgent measles, TB, and emerging pathogens, we offer a first of its kind training program for implementing Germicidal UV-C (GUV) in public settings. You will learn the fundamentals of GUV, how to design an installation, and safely install and maintain UV-C luminaires. Funded by Balvi Philanthropic Fund. Sign up at: https://docs.google.com/forms/d/e/1FAIpQLSeb_ycH_6TNdUe-nIg06R1H1ruA7dCEZMDTmr2A2e48dwJeGQ/viewform

US New Daily COVID-19 Infections and 1-Month Forecast

"As of December 16, 2024: 1.6% of the population (1 in 64 people) is estimated to be actively infectious with Covid, meaning just under 750,000 daily infections. Transmission is higher than during 73% of the pandemic, and lower than during 27% of the pandemic. We are seeing about 5 million infections a week now, likely resulting in over 200,000 eventual Covid-associated conditions or Long Covid."

Source: PMC19.com/data by Michael Hoerger, PhD, MSCR, MBA, @michael_hoerger

A chart showing the COVID positivity rate for samples from 7 international airports from 6 US States. Each line represents data from one year, including 2021, 2022, and 2023. The latest data shows that 23.5% of pools (representing 6,086 total participants) were positive for COVID. The data source is CDC Genomic Surveillance, available at the following URL: https://covid.cdc.gov/covid-data-tracker/#traveler-genomic-surveillance

A screenshot of a website called PubMed Pairs. There are two input text boxes, one for each list of search terms. The app automatically searches for each pair of terms and shows the number of PubMed results for each pair. Titles and abstracts are shown below.