Whole blood gene expression data and matched white blood cell counts generated from human donors diagnosed with a variety of chronic diseases

In this project, RNA sequencing was used in parallel with flow cytometry to generate a dataset containing peripheral blood gene expression profiles and matched circulating leukocyte counts originating from a racially and ethnically diverse cohort of human donors diagnosed with a variety of chronic health conditions. The dataset, which is fully accessible via linked NCBI data repositories, contains genome-wide expression data from venous whole blood samples, matched neutrophil, lymphocyte, monocyte, and eosinophil counts, as well as rich meta-data including donor sex, race, ethnicity, age, and diagnoses for eleven common chronic pathophysiologic states: obesity, hypertension, dyslipidemia, type II diabetes, chronic obstructive pulmonary disease, chronic kidney disease, congestive heart failure, cancer, dementia, hypothyroidism, and asthma. These data could be used to technically evaluate the influence of sample cellular composition on the efficacy of various RNA sequencing data processing and analysis tasks, for benchmarking cellular deconvolution pipelines, or to explore transcriptional alterations to the immune system associated with any of the aforementioned health conditions.