Simulating paired and longitudinal single-cell RNA sequencing data with rescueSim.

Motivation: As single-cell RNA-sequencing (scRNA-seq) becomes more widely used in transcriptomic research, complex experimental designs, such as paired or longitudinal studies, become increasingly feasible. Paired/longitudinal scRNA-seq enables the study of transcriptomic changes over time within specific cell types, yet guidance on analytical approaches and resources for study planning, such as power analysis, remains limited. Data simulation is a valuable tool for evaluating analysis method performance and informing study design decisions, including sample size selection.

Systems serology in cystic fibrosis: Anti-Pseudomonas IgG1 responses and reduced lung function.

Nearly one-half of patients with cystic fibrosis (CF) carry the homozygous F508del mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene but exhibit variable lung function phenotypes. How adaptive immunity influences their lung function remains unclear, particularly the serological antibody responses to antigens from mucoid Pseudomonas in sera from patients with CF with varying lung function. Sera from patients with CF with reduced lung function show higher anti-outer membrane protein I (OprI) immunoglobulin G1 (IgG1) titers and greater antibody-mediated complement deposition.

Quantifying the spatial clustering characteristics of radiographic emphysema explains variability in pulmonary function.

Quantitative assessment of emphysema in CT scans has mostly focused on calculating the percentage of lung tissue that is deemed abnormal based on a density thresholding strategy. However, this overall measure of disease burden discards virtually all the spatial information encoded in the scan that is implicitly utilized in a visual assessment. This simplification is likely grouping heterogenous disease patterns and is potentially obscuring clinical phenotypes and variable disease outcomes.

lmerSeq: an R package for analyzing transformed RNA-Seq data with linear mixed effects models.

Background: Studies that utilize RNA Sequencing (RNA-Seq) in conjunction with designs that introduce dependence between observations (e.g. longitudinal sampling) require specialized analysis tools to accommodate this additional complexity.

A comparison of methods for multiple degree of freedom testing in repeated measures RNA-sequencing experiments.

Background: As the cost of RNA-sequencing decreases, complex study designs, including paired, longitudinal, and other correlated designs, become increasingly feasible. These studies often include multiple hypotheses and thus multiple degree of freedom tests, or tests that evaluate multiple hypotheses jointly, are often useful for filtering the gene list to a set of interesting features for further exploration while controlling the false discovery rate. Though there are several methods which have been proposed for analyzing correlated RNA-sequencing data, there has been little research evaluating and comparing the performance of multiple degree of freedom tests across methods.

Filtering Spatial Point Patterns Using Kernel Densities.

Understanding spatial inhomogeneity and clustering in point patterns arises in many contexts, ranging from disease outbreak monitoring to analyzing radiologically-based emphysema in biomedical images. This can often involve classifying individual points as being part of a feature/cluster or as being part of a background noise process. Existing methods for this task can struggle when there are differences in the size and/or density of individual clusters.

MCMSeq: Bayesian hierarchical modeling of clustered and repeated measures RNA sequencing experiments.

Background: As the barriers to incorporating RNA sequencing (RNA-Seq) into biomedical studies continue to decrease, the complexity and size of RNA-Seq experiments are rapidly growing. Paired, longitudinal, and other correlated designs are becoming commonplace, and these studies offer immense potential for understanding how transcriptional changes within an individual over time differ depending on treatment or environmental conditions. While several methods have been proposed for dealing with repeated measures within RNA-Seq analyses, they are either restricted to handling only paired measurements, can only test for differences between two groups, and/or have issues with maintaining nominal false positive and false discovery rates.

Using a spatial point process framework to characterize lung computed tomography scans.

Pulmonary emphysema is a destructive disease of the lungs that is currently diagnosed via visual assessment of lung Computed Tomography (CT) scans by a radiologist. Visual assessment can have poor inter-rater reliability, is time consuming, and requires access to trained assessors. Quantitative methods that reliably summarize the biologically relevant characteristics of an image are needed to improve the way lung diseases are characterized.

Eating-related behaviors and appetite during energy imbalance in obese-prone and obese-resistant individuals.

While the majority of Americans are now overweight, some individuals maintain their weight with minimal effort. This study investigated behavioral differences between 58 individuals recruited as either obese-resistant (OR) or obese-prone (OP) based on self-identification, BMI, and personal/family weight history. Subjects were studied during Eucaloric (EU), Overfed (OF), and Underfed (UF) phases which included a run-in diet, 1 day intervention diet, and a study day.