Biology subjects

Walton, N. A.

Publications and source records attributed to Walton, N. A..

4 recordsLinked to original sources

bioRxiv2025

Robust Consensus Nuclear and Cell Segmentation

Cell segmentation is a crucial step in numerous biomedical imaging endeavors; so much so that the community is flooded with publicly available, state-of-the-art segmentation techniques ready for out of the box use. Assessing the virtues and limitations of each method on a tissue sample set and then selecting the optimum method for each research objective and input image is a time consuming and exacting task that often monopolizes the resources of biologists, biochemists, immunologists and pathologists; despite not being their project primary research goal. In this work, we present a segmentation software wrapper, coined CellSampler, which runs a selection of established segmentation methods and then combines their individual segmentation masks into a single optimized mask. This, so called uber mask, selects the best of the established masks across local neighborhoods within the image, where the neighborhood size and the statistical measure which determines the qualitative term best are both chosen by the user.

bioinformatics↗

bioRxiv2021

The Imaging and Molecular Annotation of Xenografts and Tumours (IMAXT) High Throughput Data and Analysis Infrastructure

With the aim of producing a 3D representation of tumours, IMAXT uses a large variety of modalities in order to acquire tumour samples and produce a map of every cell in the tumour and its host environment. With the large volume and variety of data produced in the project we develop automatic data workflows and analysis pipelines and introduce a research methodology where scientists connect to a cloud environment to perform analysis close to where data are located instead of bringing data to their local computers. Here we present the data and analysis infrastructure, discuss the unique computational challenges and describe the analysis chains developed and deployed to generate molecularly annotated tumour models. Registration is achieved by use of a novel technique involving spherical fiducial marks that are visible in all imaging modalities used within IMAXT.

cancer biology↗

bioRxiv2019

Semantic Integration of Clinical Laboratory Tests from Electronic Health Records for Deep Phenotyping and Biomarker Discovery

Electronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to the Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2421 commonly used laboratory tests with HPO terms. Using these annotations, a software assesses laboratory test results and converts each into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows reusing readily available laboratory tests in EHR for deep phenotyping and using the hierarchical structure of HPO for association studies with medical outcomes and genomics.\n\nOne Sentence SummaryWe present an approach to semantically integrating LOINC-encoded laboratory data with the Human Phenotype Ontology and show that the integrated LOINC data can be used to identify biomarkers for asthma from electronic health record data.

bioinformatics↗

bioRxiv2017

A new sequencing-based women’s health assay combining self-sampling, HPV detection and genotyping, STI detection, and vaginal microbiome analysis

The composition of the vaginal microbiome, including both the presence of pathogens involved in sexually transmitted infections (STI) as well as commensal microbiota, has been shown to have important associations for a womans reproductive and general health. Currently, healthcare providers cannot offer comprehensive vaginal microbiome screening, but are limited to the detection of individual pathogens, such as high-risk human papillomavirus (hrHPV), the predominant cause of cervical cancer. There is no single test on the market that combines HPV, STI, and microbiome screening. Here, we describe a novel inclusive womens health assay that combines self-sampling with sequencing-based HPV detection and genotyping, vaginal microbiome analysis, and STI-associated pathogen detection. The assay includes genotyping and detection of 14 hrHPV types, 5 low-risk HPV types (lrHPV), as well as the relative abundance of 32 bacterial taxa of clinical importance, including Lactobacillus, Sneathia, Gardnerella, and 4 pathogens involved in STI, with high sensitivity, specificity, and reproducibility. For each of these taxa, healthy ranges were determined in a group of 50 self-reported healthy women. The hrHPV portion of the test was evaluated against the Digene High-Risk HPV HC2 DNA test with vaginal samples obtained from 185 women. Results were concordant for 181/185 of the samples (overall agreement of 97.83%, Cohens kappa = 0.93), with sensitivity and specificity values of 94.74% and 98.64%, respectively. Two discrepancies were caused by the Digene assays known cross-reactivity with low-risk HPV types, while two additional samples were found to contain hrHPV not detected by Digene. This novel assay could be used to complement conventional cervical cancer screening, because its self-sampling format can expand access among women who would otherwise not participate, and because of its additional information about the composition of the vaginal microbiome and the presence of pathogens.

microbiology↗