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arXiv 2020年

作者： Landa, Boris Qu, Rihao Chang, Joseph Kluger, Yuval Program in Applied Mathematics Yale University Department of Pathology Yale University School of Medicine Department of Statistics and Data Science Yale University Interdepartmental Program in Computational Biology and Bioinformatics Yale University Department of Immunology Yale School of Medicine

Rejecting the null hypothesis in two-sample testing is a fundamental tool for scientific discovery. Yet, aside from concluding that two samples do not come from the same probability distribution, it is often of interest to characterize how the two distributions differ. Given samples from two densities f1and f0, we consider the task of localizing occurrences of the inequality f1> f0. To avoid the challenges associated with high-dimensional space, we propose a general hypothesis testing framework where hypotheses are formulated adaptively to the data by conditioning on the combined sample from the two densities. We then investigate a special case of this framework where the notion of locality is captured by a random walk on a weighted graph constructed over this combined sample. We derive a tractable testing procedure for this case employing a type of scan statistic, and provide non-asymptotic lower bounds on the power and accuracy of our test to detect whether f1> f0in a local sense. Furthermore, we characterize the test's consistency according to a certain problem-hardness parameter, and show that our test achieves the minimax detection rate for this parameter. We conduct numerical experiments to validate our method, and demonstrate our approach on two real-world applications: detecting and localizing arsenic well contamination across the United States, and analyzing two-sample single-cell RNA sequencing data from melanoma *** Codes 62G10 Copyright © 2020, The Authors. All rights reserved.

关键词： Random processes

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Unexpected failure rates for modular assembly of engineered zinc fingers (vol 5, pg 374, 2008)

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NATURE METHODS 2008年第6期5卷 575-575页

作者： Ramirez, Cherie L. Foley, Jonathan E. Wright, David A. Mueller-Lerch, Felix Rahman, Shamim H. Cornu, Tatjana I. Winfrey, Ronnie J. Sander, Jeffry D. Fu, Fengli Townsend, Jeffrey A. Cathomen, Toni Voytas, Daniel F. Joung, J. Keith These authors contributed equally to this work. These authors contributed equally to this work. Department of Genetics Development and Cell Biology Iowa State University 1035A Roy J. Carver Co-Lab Ames Iowa 50011 USA. Charité Medical School Institute of Virology Hindenburgdamm 27 D-12203 Berlin Germany. Charité Medical School Institute of Virology Hindenburgdamm 27 D-12203 Berlin Germany. Charité Medical School Institute of Virology Hindenburgdamm 27 D-12203 Berlin Germany. Department of Genetics Development and Cell Biology Iowa State University 1035A Roy J. Carver Co-Lab Ames Iowa 50011 USA. Interdepartmental Graduate Program in Bioinformatics and Computational Biology 2114 Molecular Biology Building Iowa State University Ames Iowa 50011 USA. Interdepartmental Graduate Program in Bioinformatics and Computational Biology 2114 Molecular Biology Building Iowa State University Ames Iowa 50011 USA. Department of Genetics Development and Cell Biology Iowa State University 1035A Roy J. Carver Co-Lab Ames Iowa 50011 USA. Charité Medical School Institute of Virology Hindenburgdamm 27 D-12203 Berlin Germany. Department of Genetics Development and Cell Biology Iowa State University 1035A Roy J. Carver Co-Lab Ames Iowa 50011 USA. Department of Pathology Harvard Medical School Boston Massachusetts 02115 USA.

A letter to the editor is presented in response to an article on zinc fingers in a previous issue.

关键词： LETTERS to the editor ZINC

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Identify Non-mutational p53 Functional Deficiency in Human Cancers

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Genomics, Proteomics & bioinformatics 2024年第5期22卷 85-98页

作者： Qianpeng Li Yang Zhang Sicheng Luo Zhang Zhang Ann L.Oberg David E.Kozono Hua Lu Jann N.Sarkaria Lina Ma Liguo Wang National Genomics Data Center China National Center for BioinformationBeijing 100101China Beijing Institute of Genomics Chinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China Division of Computational Biology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Department of Radiation Oncology Dana-Farber Cancer Institute and Brigham and Women's HospitalBostonMA 02215USA Department of Biochemistry&Molecular Biology and Tulane Cancer Center Tulane University School of MedicineNew OrleansLA 70112USA Department of Radiation Oncology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Department of Biochemistry and Molecular Biology Mayo Clinic College of Medicine and ScienceRochesterMN 55905USA Bioinformatics and Computational Biology Graduate Program University of Minnesota RochesterRochesterMN 55904USA

An accurate assessment of p53's functional statuses is critical for cancer genomic ***,there is a significant challenge in identifying tumors with non-mutational p53 inactivation which is not detectable through DNA *** undetected cases are often misclassified as p53-normal,leading to inaccurate prognosis and downstream association *** address this issue,we built the support vector machine(SVM)models to systematically reassess p53's functional statuses in TP53 wild-type(TP53^(WT))tumors from multiple The Cancer Genome Atlas(TCGA)***-validation demonstrated the good performance of the SVM models with a mean area under the receiver operating characteristic curve(AUROC)of 0.9822,precision of 0.9747,and recall of *** study revealed that a significant proportion(87%-99%)of TP53^(WT) tumors actually had compromised p53 *** analyses uncovered that these genetically intact but functionally impaired(termed as predictively reduced function of p53 or TP53^(WT)-pRF)tumors exhibited genomic and pathophysiologic features akin to TP53-mutant tumors:heightened genomic instability and elevated levels of ***,patients with TP53^(WT)-pRF tumors experienced significantly shortened overall survival or progression-free survival compared to those with predictively normal function of p53(TP53^(WT)-pN)tumors,and these patients also displayed increased sensitivity to platinum-based chemotherapy and radiation therapy.

关键词： Cancer Composite expression DNA mutation Machine learning p53 deficiency

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Analysis of cancer omics data in a semantic web framework

Analysis of cancer omics data in a semantic web framework

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Workshop on Semantic Web Applications and Tools for Life Sciences 2010, SWAT4LS 2010

作者： Holford, Matthew E. McCusker, James P. Cheung, Kei-Hoi Krauthammer, Michael Interdepartmental Program in Computational Biology and Bioinformatics Yale University New Haven CT United States Department of Pathology Yale University New Haven CT United States Department of Computer Science Yale University New Haven CT United States Center for Medical Informatics Yale University New Haven CT United States Department of Genetics Yale University New Haven CT United States

Our work concerns the elucidation of the cancer (epi)genome, transcriptome and proteome to better understand the complex interplay between a cancer cell's molecular state and its response to anti-cancer therapy. To study the problem, we have previously focused on data warehousing technologies and statistical data integration. In this paper, we present recent work on extending our analytical capabilities using Semantic Web technology. A key new component presented here is a SPARQL endpoint to our existing data warehouse. This endpoint allows the merging of observed quantitative data with existing data from semantic knowledge sources such as Gene Ontology (GO). We show how such variegated quantitative and functional data can be integrated and accessed in a universal manner using Semantic Web tools. We also demonstrate how Description Logic (DL) reasoning can be used to infer previously unstated conclusions from existing knowledge bases. As proof of concept, we illustrate the ability of our setup to answer complex queries on resistance of cancer cells to Decitabine, a demethylating agent.

关键词： Semantic Web

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MetNetAPI: A flexible method to access and manipulate biological network data from MetNet

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BMC Research Notes 2010年第1期3卷 312-312页

作者： Sucaet, Yves Wurtele, Eve Syrkin Department of Genetics Development and Cell Biology Iowa State University Ames IA 50011 United States Interdepartmental Program in Bioinformatics and Computational Biology Iowa State University Ames IA 50011 United States

Background. Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server. Results. MetNetAPI is a versatile Application programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only. Conclusions. An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, *** and R programming environments and offers flexible query and bro

关键词： Application program Interface Molecular Entity Biological Database Command Line Interface Network Object

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Formalizing the representation of immune exposures for human immunology studies 9

Formalizing the representation of immune exposures for human...

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9th International Conference on Biological Ontology, ICBO 2018

作者： Vita, Randi Overton, James A. Cheung, Kei-Hoi Kleinstein, Steven H. Peters, Bjoern Division for Vaccine Discovery San Diego Institute for Allergy and Immunology San DiegoCA United States Department of Emergency Medicine Yale Center for Medical Informatics Yale School of Medicine New HavenCT United States Department of Pathology Yale School of Medicine New HavenCT United States Interdepartmental Program in Computational Biology and Bioinformatics Yale University New HavenCT United States

Human immunology studies typically examine how immune exposures associated with vaccinations, infectious, allergic or autoimmune diseases, or transplantations perturb the immune system with the goal to develop diagnostic tools and therapeutic interventions. While there are established approaches to formally represent the experimental data generated in such studies, which often comprises gene expression data, flow cytometry data, or serology data, the description of the immune exposures themselves is not well standardized. We here present a formal approach to represent immune exposures at a high level of granularity. We capture the exposure process (e.g. 'vaccination' or 'occurrence of allergic disease'), exposure material (e.g. 'Tdap vaccine' or 'House dust mite'), and the associated disease name and stage (e.g. 'allergic rhinitis' and 'chronic'). This representation scheme has been used successfully in the IEDB and an extended version has been adopted by HIPC to capture studies in ImmPort. We are reporting here on this scheme, our ongoing attempts to map the terms used to existing ontologies, and the challenges encountered. © 2018 CEUR-WS.

关键词： Ontology

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Biwhitening reveals the rank of a count matrix

arXiv

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arXiv 2021年

作者： Landa, Boris Zhang, Thomas T.C.K. Kluger, Yuval Program in Applied Mathematics Yale University United States Department of Electrical and Systems Engineering University of Pennsylvania United States Interdepartmental Program in Computational Biology and Bioinformatics Yale University United States Department of Pathology Yale University School of Medicine United States

Estimating the rank of a corrupted data matrix is an important task in data analysis, most notably for choosing the number of components in PCA. Significant progress on this task was achieved using random matrix theory by characterizing the spectral properties of large noise matrices. However, utilizing such tools is not straightforward when the data matrix consists of count random variables, e.g., Poisson, in which case the noise can be heteroskedastic with an unknown variance in each entry. In this work, we consider a Poisson random matrix with independent entries, and propose a simple procedure termed biwhitening for estimating the rank of the underlying signal matrix (i.e., the Poisson parameter matrix) without any prior knowledge. Our approach is based on the key observation that one can scale the rows and columns of the data matrix simultaneously so that the spectrum of the corresponding noise agrees with the standard Marchenko-Pastur (MP) law, justifying the use of the MP upper edge as a threshold for rank selection. Importantly, the required scaling factors can be estimated directly from the observations by solving a matrix scaling problem via the Sinkhorn-Knopp algorithm. Aside from the Poisson, our approach is extended to families of distributions that satisfy a quadratic relation between the mean and the variance, such as the generalized Poisson, binomial, negative binomial, gamma, and many others. This quadratic relation can also account for missing entries in the data. We conduct numerical experiments that corroborate our theoretical findings, and showcase the advantage of our approach for rank estimation in challenging regimes. Furthermore, we demonstrate the favorable performance of our approach on several real datasets of single-cell RNA sequencing (scRNA-seq), High-Throughput Chromosome Conformation Capture (Hi-C), and document topic *** Codes 62H12, 62H25. Copyright © 2021, The Authors. All rights reserved.

关键词： Random variables

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Distinct adipose progenitor cells emerging with age drive active adipogenesis

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Science (New York, N.Y.) 2025年第6745期388卷 eadj0430页

作者： Wang, Guan Li, Gaoyan Song, Anying Zhao, Yutian Yu, Jiayu Wang, Yifan Dai, Wenting Salas, Martha Qin, Hanjun Medrano, Leonard Dow, Joan Li, Aimin Armstrong, Brian Fueger, Patrick T. Yu, Hua Zhu, Yi Shao, Mengle Wu, Xiwei Jiang, Lei Campisi, Judith Yang, Xia Wang, Qiong A. Department of Molecular and Cellular Endocrinology Arthur Riggs Diabetes and Metabolism Research Institute City of Hope Medical Center Duarte CA USA Department of Integrative Biology and Physiology University of California Los Angeles CA United States Light Microscopy Core City of Hope Medical Center Duarte CA USA The Integrative Genomics Core City of Hope Medical Center Duarte CA USA Division of Developmental and Translational Diabetes and Endocrinology Research City of Hope Medical Center Duarte CA USA Comprehensive Metabolic Phenotyping Core City of Hope Medical Center Duarte CA USA Pathology Core of Shared Resources City of Hope Medical Center Duarte CA USA Comprehensive Cancer Center Beckman Research Institute City of Hope Medical Center Duarte CA USA Children's Nutrition Research Center Department of Pediatrics Baylor College of Medicine Houston TX United States Key Laboratory of Immune Response and Immunotherapy Shanghai Institute of Immunity and Infection Chinese Academy of Sciences Shanghai China Buck Institute for Research on Aging Novato CA United States Bioinformatics Interdepartmental Program University of California Los Angeles CA United States Institute for Quantitative and Computational Biosciences University of California Los Angeles CA United States Molecular and Medical Pharmacology University of California Los Angeles CA United States

Starting at middle age, adults often suffer from visceral adiposity and associated adverse metabolic disorders. Lineage tracing in mice revealed that adipose progenitor cells (APCs) in visceral fat undergo extensive adipogenesis during middle age. Thus, despite the low turnover rate of adipocytes in young adults, adipogenesis is unlocked during middle age. Transplantations quantitatively showed that APCs in middle-aged mice exhibited high adipogenic capacity cell-autonomously. Single-cell RNA sequencing identified a distinct APC population, the committed preadipocyte, age-enriched (CP-A), emerging at this age. CP-As demonstrated elevated proliferation and adipogenesis activity. Pharmacological and genetic manipulations indicated that leukemia inhibitory factor receptor signaling was indispensable for CP-A adipogenesis and visceral fat expansion. These findings uncover a fundamental mechanism of age-dependent adipose remodeling, offering critical insights into age-related metabolic diseases.

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Exploring transposable element-based markers to identify allelic variations underlying agronomic traits in rice

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Plant Communications 2022年第3期3卷 59-71页

作者： Haidong Yan David C.Haak Song Li Linkai Huang Aureliano Bombarely School of Plant and Environmental Sciences Virginia TechBlacksburgVA 24061USA Graduate Program in Genetics Bioinformatics and Computational Biology(GBCB)Virginia TechBlacksburgVA 24061USA Department of Grassland Science Animal Science and Technology CollegeSichuan Agricultural UniversityChengdu 611130China Department of Bioscience Universita degli Studi di Milano(UNIMI)20133 MilanoItaly Instituto de Biologıa Molecular y Celular de Plantas(IBMCP) UPV-CSIC46022 ValenciaSpain

Transposable elements(TEs)are a major force in the production of new alleles during domestication;nevertheless,their use in association studies has been limited because of their *** have developed a TE genotyping pipeline(TEmarker)and applied it to whole-genome genome-wide association study(GWAS)data from 176 Oryza sativa *** accessions to identify genetic elements associated with specific agronomic *** markers recovered a large proportion(69%)of single-nucleotide polymorphism(SNP)-based GWAS peaks,and these TE peaks retained ca.25%of the *** use of TEs in GWASs may reduce false positives associated with linkage disequilibrium(LD)among SNP markers.A genome scan revealed positive selection on TEs associated with agronomic *** found several cases of insertion and deletion variants that potentially resulted from the direct action of TEs,including an allele of LOC_Os11g08410 associated with plant height and panicle length ***,these findings reveal the utility of TE markers for connecting genotype to phenotype and suggest a potential role for TEs in influencing phenotypic variations in rice that impact agronomic traits.

关键词： transposable element marker agronomic trait rice GWAS

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APIR:Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control

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Genomics, Proteomics & bioinformatics 2024年第2期22卷 171-187页

作者： Yiling Elaine Chen Xinzhou Ge Kyla Woyshner MeiLu McDermott Antigoni Manousopoulou Scott B.Ficarro Jarrod A.Marto Kexin Li Leo David Wang Jingyi Jessica Li Department of Statistics and Data Science University of CaliforniaLos AngelesCA 90095USA Department of Immuno-Oncology Beckman Research InstituteCity of Hope National Medical CenterDuarteCA 91010USA Department of Quantitative and Computational Biology University of Southern CaliforniaLos AngelesCA 90089USA Department of Cancer Biology and Blais Proteomics Center Dana-Farber Cancer InstituteDepartment of PathologyBrigham and Women’s Hospital and Harvard Medical SchoolBostonMA 02215USA Department of Pediatrics City of Hope National Medical CenterDuarteCA 91010USA Bioinformatics Interdepartmental Program University of CaliforniaLos AngelesCA 90095USA Department of Human Genetics University of CaliforniaLos AngelesCA 90095USA Department of Computational Medicine University of CaliforniaLos AngelesCA 90095USA Department of Biostatistics University of CaliforniaLos AngelesCA 90095USA

Advances in mass spectrometry(MS)have enabled high-throughput analysis of proteomes in biological *** state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide–spectrum matches(PSMs),which convert mass spectra to peptide *** database search algorithms use distinct search strategies and thus may identify unique ***,no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and a control on the false discovery rate(FDR).To fill in this gap,we proposed a statistical framework,Aggregation of Peptide Identification Results(APIR),that is universally compatible with all database search ***,under an FDR threshold,APIR is guaranteed to identify at least as many,if not more,peptides as individual database search algorithms *** of APIR on a complex proteomics standard dataset showed that APIR outpowers individual database search algorithms and empirically controls the *** data studies showed that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search *** APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis,e.g.,differential gene expression analysis on RNA sequencing *** APIR R package is available at https://***/yiling0210/APIR.

关键词： Shotgun proteomics Peptide–spectrum match Peptide identification Aggregation of lists FDR control

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