Quantifying Health Outcome Disparity in Invasive Methicillin-Resistant Staphylococcus aureus Infection using Fairness Algorithms on Real-World Data
In conclusion, this work demonstrates a practical utility of fairness AI methods in public health settings.PMID:38160296 (Source: Pacific Symposium on Biocomputing)
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Inyoung Jun Sarah E Ser Scott A Cohen Jie Xu Robert J Lucero Jiang Bian Mattia Prosperi Source Type: research
Imputation of race and ethnicity categories using genetic ancestry from real-world genomic testing data
This study introduces two methods-one heuristic and the other machine learning-based-to impute race and ethnicity from genetic ancestry using tumor profiling data. Analyzing de-identified data from over 100,000 cancer patients sequenced with the Tempus xT panel, we demonstrate that both methods outperform existing geolocation and surname-based methods, with the machine learning approach achieving high recall (range: 0.859-0.993) and precision (range: 0.932-0.981) across four mutually exclusive race and ethnicity categories. This work presents a novel pathway to enhance RWD utility in studying racial disparities in healthca...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Brooke Rhead Paige E Haffener Yannick Pouliot Francisco M De La Vega Source Type: research
Session Introduction: Precision Medicine: Innovative methods for advanced understanding of molecular underpinnings of disease
Pac Symp Biocomput. 2024;29:446-449.ABSTRACTPrecision medicine, also often referred to as personalized medicine, targets the development of treatments and preventative measures specific to the individual's genomic signatures, lifestyle, and environmental conditions. The series of Precision Medicine sessions in PSB has continuously highlighted the advances in this field. Our 2024 collection of manuscripts showcases algorithmic advances that integrate data from distinct modalities and introduce innovative approaches to extract new, medically relevant information from existing data. These evolving technology and analytical me...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Yana Bromberg Hannah Carter Steven E Brenner Source Type: research
Enhancing Spatial Transcriptomics Analysis by Integrating Image-Aware Deep Learning Methods
We present a novel method integrating spatial transcriptomics and histopathological image data to better capture biologically meaningful patterns in patient data, focusing on aggressive cancer types such as glioblastoma and triple-negative breast cancer. We used a ResNet-based deep learning model to extract key morphological features from high-resolution whole-slide histology images. Spot-level PCA-reduced vectors of both the ResNet-50 analysis of the histological image and the spatial gene expression data were used in Louvain clustering to enable image-aware feature discovery. Assessment of features from image-aware clust...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Jiarong Song Josh Lamstein Vivek Gopal Ramaswamy Michelle Webb Gabriel Zada Steven Finkbeiner David W Craig Source Type: research
Spatial Omics Driven Crossmodal Pretraining Applied to Graph-based Deep Learning for Cancer Pathology Analysis
Pac Symp Biocomput. 2024;29:464-476.ABSTRACTGraph-based deep learning has shown great promise in cancer histopathology image analysis by contextualizing complex morphology and structure across whole slide images to make high quality downstream outcome predictions (ex: prognostication). These methods rely on informative representations (i.e., embeddings) of image patches comprising larger slides, which are used as node attributes in slide graphs. Spatial omics data, including spatial transcriptomics, is a novel paradigm offering a wealth of detailed information. Pairing this data with corresponding histological imaging loca...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Zarif L Azher Michael Fatemi Yunrui Lu Gokul Srinivasan Alos B Diallo Brock C Christensen Lucas A Salas Fred W Kolling Laurent Perreard Scott M Palisoul Louis J Vaickus Joshua J Levy Source Type: research
Potential to Enhance Large Scale Molecular Assessments of Skin Photoaging through Virtual Inference of Spatial Transcriptomics from Routine Staining
Pac Symp Biocomput. 2024;29:477-491.ABSTRACTThe advent of spatial transcriptomics technologies has heralded a renaissance in research to advance our understanding of the spatial cellular and transcriptional heterogeneity within tissues. Spatial transcriptomics allows investigation of the interplay between cells, molecular pathways, and the surrounding tissue architecture and can help elucidate developmental trajectories, disease pathogenesis, and various niches in the tumor microenvironment. Photoaging is the histological and molecular skin damage resulting from chronic/acute sun exposure and is a major risk factor for ski...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Gokul Srinivasan Matthew J Davis Matthew R LeBoeuf Michael Fatemi Zarif L Azher Yunrui Lu Alos B Diallo Marietta K Saldias Montivero Fred W Kolling Laurent Perrard Lucas A Salas Brock C Christensen Thomas J Palys Margaret R Karagas Scott M Palisoul Gregor Source Type: research
PEPSI: Polarity measurements from spatial proteomics imaging suggest immune cell engagement
Pac Symp Biocomput. 2024;29:492-505.ABSTRACTSubcellular protein localization is important for understanding functional states of cells, but measuring and quantifying this information can be difficult and typically requires high-resolution microscopy. In this work, we develop a metric to define surface protein polarity from immunofluorescence (IF) imaging data and use it to identify distinct immune cell states within tumor microenvironments. We apply this metric to characterize over two million cells across 600 patient samples and find that cells identified as having polar expression exhibit characteristics relating to tumo...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Eric Wu Zhenqin Wu Aaron T Mayer Alexandro E Trevino James Zou Source Type: research
KombOver: Efficient k-core and K-truss based characterization of perturbations within the human gut microbiome
Pac Symp Biocomput. 2024;29:506-520.ABSTRACTThe microbes present in the human gastrointestinal tract are regularly linked to human health and disease outcomes. Thanks to technological and methodological advances in recent years, metagenomic sequencing data, and computational methods designed to analyze metagenomic data, have contributed to improved understanding of the link between the human gut microbiome and disease. However, while numerous methods have been recently developed to extract quantitative and qualitative results from host-associated microbiome data, improved computational tools are still needed to track micro...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Nicolae Sapoval Marko Tanevski Todd J Treangen Source Type: research
nSEA: n-Node Subnetwork Enumeration Algorithm Identifies Lower Grade Glioma Subtypes with Altered Subnetworks and Distinct Prognostics
This study offers a comprehensive molecular classification of LGG, providing insights beyond traditional genetic markers. By integrating network analysis with patient clustering, we unveil a previously overlooked patient subgroup with potential implications for prognosis and treatment strategies. Our approach sheds light on the synergistic nature of driver genes and highlights the biological relevance of the identified subnetworks. With broad implications for glioma research, our findings pave the way for further investigations into the mechanistic underpinnings of LGG subtypes and their clinical relevance.Availability: So...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Zhihan Zhang Christiana Wang Ziyin Zhao Ziyue Yi Arda Durmaz Jennifer S Yu Gurkan Bebek Source Type: research
Application of quantile discretization and bayesian network analysis to publicly available cystic fibrosis data sets
Pac Symp Biocomput. 2024;29:534-548.ABSTRACTThe availability of multiple publicly-available datasets studying the same phenomenon has the promise of accelerating scientific discovery. Meta-analysis can address issues of reproducibility and often increase power. The promise of meta-analysis is especially germane to rarer diseases like cystic fibrosis (CF), which affects roughly 100,000 people worldwide. A recent search of the National Institute of Health's Gene Expression Omnibus revealed 1.3 million data sets related to cancer compared to about 2,000 related to CF. These studies are highly diverse, involving different tiss...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Kiyoshi Ferreira Fukutani Thomas H Hampton Carly A Bobak Todd A MacKenzie Bruce A Stanton Source Type: research
Low- and high-level information analyses of transcriptome connecting endometrial-decidua-placental origin of preeclampsia subtypes: A preliminary study
CONCLUSIONS: We identified the transcriptome of endometrial maturation in placental dysfunction that distinguished early- and late-onset PE, and indicated chorioamnionitis as a PE competing risk. This study implied a feasibility to develop and validate the pathogenesis models that include pre-pregnancy and competing risks to decide if it is needed to collect prospective data for PE starting from pre-pregnancy including chorioamnionitis information.PMID:38160306 (Source: Pacific Symposium on Biocomputing)
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Herdiantri Sufriyana Yu-Wei Wu Emily Chia-Yu Su Source Type: research
Deconvolution of Nascent Sequencing Data Using Transcriptional Regulatory Elements
We present here the first attempt at solving the supervised deconvolution problem for run-on nascent sequencing data (GRO-seq and PRO-seq), a readout of active transcription. Then, we develop a novel filtering method suited to the mixed set of promoter and enhancer regions provided by nascent sequencing, and apply best-practice standards from the RNA-seq literature, using in-silico mixtures of cells. Using these methods, we find that enhancer RNAs are highly informative features for supervised deconvolution. In most cases, simple deconvolution methods perform better than more complex ones for solving the nascent deconvolut...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Zachary Maas Rutendo Sigauke Robin Dowell Source Type: research
Splitpea: quantifying protein interaction network rewiring changes due to alternative splicing in cancer
Pac Symp Biocomput. 2024;29:579-593.ABSTRACTProtein-protein interactions play an essential role in nearly all biological processes, and it has become increasingly clear that in order to better understand the fundamental processes that underlie disease, we must develop a strong understanding of both their context specificity (e.g., tissue-specificity) as well as their dynamic nature (e.g., how they respond to environmental changes). While network-based approaches have found much initial success in the application of protein-protein interactions (PPIs) towards systems-level explorations of biology, they often overlook the fa...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Ruth Dannenfelser Vicky Yao Source Type: research
Lymphocyte Count Derived Polygenic Score and Interindividual Variability in CD4 T-cell Recovery in Response to Antiretroviral Therapy
Pac Symp Biocomput. 2024;29:594-610.ABSTRACTAccess to safe and effective antiretroviral therapy (ART) is a cornerstone in the global response to the HIV pandemic. Among people living with HIV, there is considerable interindividual variability in absolute CD4 T-cell recovery following initiation of virally suppressive ART. The contribution of host genetics to this variability is not well understood. We explored the contribution of a polygenic score which was derived from large, publicly available summary statistics for absolute lymphocyte count from individuals in the general population (PGSlymph) due to a lack of publicly ...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Kathleen M Cardone Scott Dudek Karl Keat Yuki Bradford Zinhle Cindi Eric S Daar Roy Gulick Sharon A Riddler Jeffrey L Lennox Phumla Sinxadi David W Haas Marylyn D Ritchie Source Type: research
Polygenic risk scores for cardiometabolic traits demonstrate importance of ancestry for predictive precision medicine
In this study, we present an in-depth evaluation of PRS based on multi-ancestry GWAS for five cardiometabolic phenotypes in the Penn Medicine BioBank (PMBB) followed by a phenome-wide association study (PheWAS). We examine the PRS performance across all individuals and separately in African ancestry (AFR) and EUR ancestry groups. For AFR individuals, PRS derived using the multi-ancestry LD panel showed a higher effect size for four out of five PRSs (DBP, SBP, T2D, and BMI) than those derived from the AFR LD panel. In contrast, for EUR individuals, the multi-ancestry LD panel PRS demonstrated a higher effect size for two ou...
Source: Pacific Symposium on Biocomputing - December 31, 2023 Category: Bioinformatics Authors: Rachel L Kember Shefali S Verma Anurag Verma Brenda Xiao Anastasia Lucas Colleen M Kripke Renae Judy Jinbo Chen Scott M Damrauer Daniel J Rader Marylyn D Ritchie Source Type: research
