tidytof: a user-friendly framework for scalable and reproducible high-dimensional cytometry data analysis.

Summary: While many algorithms for analyzing high-dimensional cytometry data have now been developed, the software implementations of these algorithms remain highly customized-this means that exploring a dataset requires users to learn unique, often poorly interoperable package syntaxes for each step of data processing. To solve this problem, we developed {tidytof}, an open-source R package for analyzing high-dimensional cytometry data using the increasingly popular 'tidy data' interface.

Availability And Implementation: {tidytof} is available at https://github.

Single-cell technologies uncover intra-tumor heterogeneity in childhood cancers.

Childhood cancer is the second leading cause of death in children aged 1 to 14. Although survival rates have vastly improved over the past 40 years, cancer resistance and relapse remain a significant challenge. Advances in single-cell technologies enable dissection of tumors to unprecedented resolution.

CytofIn enables integrated analysis of public mass cytometry datasets using generalized anchors.

The increasing use of mass cytometry for analyzing clinical samples offers the possibility to perform comparative analyses across public datasets. However, challenges in batch normalization and data integration limit the comparison of datasets not intended to be analyzed together. Here, we present a data integration strategy, CytofIn, using generalized anchors to integrate mass cytometry datasets from the public domain.

Progressive B Cell Loss in Revertant X-SCID.

We report the case of a patient with X-linked severe combined immunodeficiency (X-SCID) who survived for over 20 years without hematopoietic stem cell transplantation (HSCT) because of a somatic reversion mutation. An important feature of this rare case included the strategy to validate the pathogenicity of a variant of the IL2RG gene when the T and B cell lineages comprised only revertant cells. We studied the X-inactivation of sorted T cells from the mother to show that the pathogenic variant was indeed the cause of his SCID.

A Cancer Biologist's Primer on Machine Learning Applications in High-Dimensional Cytometry.

The application of machine learning and artificial intelligence to high-dimensional cytometry data sets has increasingly become a staple of bioinformatic data analysis over the past decade. This is especially true in the field of cancer biology, where protocols for collecting multiparameter single-cell data in a high-throughput fashion are rapidly developed. As the use of machine learning methodology in cytometry becomes increasingly common, there is a need for cancer biologists to understand the basic theory and applications of a variety of algorithmic tools for analyzing and interpreting cytometry data.

Student Education About Pre-exposure Prophylaxis (PrEP) Varies Between Regions of the United States.

Background: Daily, oral pre-exposure prophylaxis (PrEP) is an effective and safe prevention strategy for people at risk for HIV. However, prescription of PrEP has been limited for patients at the highest risk. Disparities in PrEP prescription are pronounced among racial and gender minority patients.

Structural and functional features of central nervous system lymphatic vessels.

One of the characteristics of the central nervous system is the lack of a classical lymphatic drainage system. Although it is now accepted that the central nervous system undergoes constant immune surveillance that takes place within the meningeal compartment, the mechanisms governing the entrance and exit of immune cells from the central nervous system remain poorly understood. In searching for T-cell gateways into and out of the meninges, we discovered functional lymphatic vessels lining the dural sinuses.