Biology subjects

DuVal, A.

Publications and source records attributed to DuVal, A..

3 recordsLinked to original sources

bioRxiv2023

Deconfounded Dimension Reduction via Partial Embeddings

Dimension reduction tools preserving similarity and graph structure such as t-SNE and UMAP can capture complex biological patterns in high-dimensional data. However, these tools typically are not designed to separate effects of interest from unwanted effects due to confounders. We introduce the partial embedding (PARE) framework, which enables removal of confounders from any distance-based dimension reduction method. We then develop partial t-SNE and partial UMAP and apply these methods to genomic and neuroimaging data. Our results show that the PARE framework can remove batch effects in single-cell sequencing data as well as separate clinical and technical variability in neuroimaging measures. We demonstrate that the PARE framework extends dimension reduction methods to highlight biological patterns of interest while effectively removing confounding effects.

neuroscience↗

bioRxiv2022

Inter-scanner brain MRI volumetric biases persist even in a harmonized multi-subject study of multiple sclerosis

Background/PurposeMulticenter study designs involving a variety of MRI scanners have become increasingly common. However, these present the issue of biases in image-based measures due to scanner or site differences. To assess these biases, we imaged 11 volunteers with multiple sclerosis (MS) with scan and rescan data at 4 sites. Materials and MethodsImages were acquired on Siemens or Philips scanners at 3-tesla. Automated white matter lesion detection and whole brain, gray and white matter, and thalamic volumetry were performed, as well as expert manual delineations of T1 and T2 (FLAIR) lesions. Random effect and permutation-based nonparametric modeling was performed to assess differences in estimated volumes within and across sites. ResultsRandom effect modeling demonstrated model assumption violations for most comparisons of interest. Non-parametric modeling indicated that site explained > 50% of the variation for most estimated volumes. This expanded to > 75% when data from both Siemens and Philips scanners were included. Permutation tests revealed significant differences between average inter- and intra-scanner differences in most estimated brain volumes (P < .05). The automatic activation of spine coil elements during some acquisitions resulted in a shading artifact in these images. Permutation tests revealed significant differences between thalamic volume measurements from acquisitions with and without this artifact. ConclusionDifferences in brain volumetry persisted across MR scanners despite protocol harmonization. These differences were not well explained by variance component modeling; however, statistical innovations for mitigating inter-scanner differences show promise in reducing biases in multi-center studies of MS.

neuroscience↗

bioRxiv2020

Identification of H3N2 NA and PB1-F2 genetic variants and their association with disease symptoms in the 2014-15 influenza season

The 2014-15 influenza season saw the emergence of an H3N2 antigenic drift variant that formed the 3C.2a HA clade. Whole viral genomes were sequenced from nasopharyngeal swabs of 94 patients with confirmed influenza A virus infection and primary human nasal epithelial cell cultures used to efficiently isolate H3N2 viruses. The isolates were classified by HA clade and the presence of a new set of co-selected mutations in NA (a glycosylation site, NAg+) and PB1-F2 (H75P). The NA and PB1-F2 mutations were present in a subset of clade 3C.2a viruses (NAg+F2P) which dominated during the subsequent influenza seasons. In human nasal epithelial cell cultures, a virus with the novel NAg+F2P genotype replicated less well compared to a virus with the parental genotype. Retrospective analyses of clinical data showed that NAg+F2P genotype viruses were associated with increased cough and shortness of breath in infected patients.

microbiology↗