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Statistics in Biosciences

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https://www.readbyqxmd.com/read/30220933/valuing-sets-of-potential-transplants-in-a-kidney-paired-donation-network
#1
Mathieu Bray, Wen Wang, Peter X-K Song, John D Kalbfleisch
In kidney paired donation (KPD), incompatible donor-candidate pairs and non-directed (also known as altruistic) donors are pooled together with the aim of maximizing the total utility of transplants realized via donor exchanges. We consider a setting in which disjoint sets of potential transplants are selected at regular intervals, with fallback options available within each proposed set in the case of individual donor, candidate or match failure. We develop methods for calculating the expected utility for such sets under a realistic probability model for the KPD...
April 2018: Statistics in Biosciences
https://www.readbyqxmd.com/read/30174757/a-two-stage-hidden-markov-model-design-for-biomarker-detection-with-application-to-microbiome-research
#2
Yi-Hui Zhou, Paul Brooks, Xiaoshan Wang
It has been recognized that for appropriately ordered data, hidden Markov models (HMM) with local false discovery rate (FDR) control can increase the power to detect significant associations. For many high-throughput technologies, the cost still limits their application. Two-stage designs are attractive, in which a set of interesting features or biomarkers is identified in a first stage, and then followed up in a second stage. However, to our knowledge no two-stage FDR control with HMMs has been developed. In this paper, we study an efficient HMM-FDR based two-stage design, using a simple integrated analysis procedure across the stages...
April 2018: Statistics in Biosciences
https://www.readbyqxmd.com/read/30147803/second-order-estimating-equations-for-clustered-current-status-data-from-family-studies-using-response-dependent-sampling
#3
Yujie Zhong, Richard J Cook
Studies about the genetic basis for disease are routinely conducted through family studies under response-dependent sampling in which affected individuals called probands are sampled from a disease registry, and their respective family members (non-probands) are recruited for study. The extent to which the dependence in some feature of the disease process (e.g., presence, age of onset, severity) varies according to the kinship of individuals reflects the evidence of a genetic cause for disease. When the probands are selected from a disease registry, it is common for them to provide quite detailed information regarding their disease history, but non-probands often simply provide their disease status at the time of contact...
2018: Statistics in Biosciences
https://www.readbyqxmd.com/read/29520313/statistical-methods-in-organ-failure-and-transplantation
#4
Douglas E Schaubel
No abstract text is available yet for this article.
December 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/29484032/matching-and-imputation-methods-for-risk-adjustment-in-the-health-insurance-marketplaces
#5
Sherri Rose, Julie Shi, Thomas G McGuire, Sharon-Lise T Normand
New state-level health insurance markets, denoted Marketplaces , created under the Affordable Care Act, use risk-adjusted plan payment formulas derived from a population ineligible to participate in the Marketplaces. We develop methodology to derive a sample from the target population and to assemble information to generate improved risk-adjusted payment formulas using data from the Medical Expenditure Panel Survey and Truven MarketScan databases. Our approach requires multi-stage data selection and imputation procedures because both data sources have systemic missing data on crucial variables and arise from different populations...
December 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/29399206/joint-modeling-of-repeated-measures-and-competing-failure-events-in-a-study-of-chronic-kidney-disease
#6
Wei Yang, Dawei Xie, Qiang Pan, Harold I Feldman, Wensheng Guo
We are motivated by the Chronic Renal Insufficiency Cohort (CRIC) study to identify risk factors for renal progression in patients with chronic kidney diseases. The CRIC study collects two types of renal outcomes: glomerular filtration rate (GFR) estimated annually and end stage renal disease (ESRD). A related outcome of interest is death which is a competing event for ESRD. A joint modeling approach is proposed to model a longitudinal outcome and two competing survival outcomes. We assume multivariate normality on the joint distribution of the longitudinal and survival outcomes...
December 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/29399205/a-lasso-method-to-identify-protein-signature-predicting-post-transplant-renal-graft-survival
#7
Ling Zhou, Lu Tang, Angela T Song, Diane M Cibrik, Peter X-K Song
Identifying novel biomarkers to predict renal graft survival is important in post-transplant clinical practice. Serum creatinine, currently the most popular surrogate biomarker, offers limited information of the underlying allograft profiles. It is known to perform unsatisfactorily to predict renal function. In this paper, we apply a LASSO machine-learning algorithm in the Cox proportional hazards model to identify promising proteins that are associated with the hazard of allograft loss after renal transplantation, motivated by a clinical pilot study that collected 47 patients receiving renal transplants at the University of Michigan Hospital...
December 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/29335670/big-data-and-neuroimaging
#8
Yenny Webb-Vargas, Shaojie Chen, Aaron Fisher, Amanda Mejia, Yuting Xu, Ciprian Crainiceanu, Brian Caffo, Martin A Lindquist
Big Data are of increasing importance in a variety of areas, especially in the biosciences. There is an emerging critical need for Big Data tools and methods, because of the potential impact of advancements in these areas. Importantly, statisticians and statistical thinking have a major role to play in creating meaningful progress in this arena. We would like to emphasize this point in this special issue, as it highlights both the dramatic need for statistical input for Big Data analysis and for a greater number of statisticians working on Big Data problems...
December 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/29308097/methods-for-contrasting-gap-time-hazard-functions-application-to-repeat-liver-transplantation
#9
Xu Shu, Douglas E Schaubel
In studies featuring a sequence of ordered events, gap times between successive events are often of interest. Despite the rich literature in this area, very few methods for comparing gap times have been developed. We propose methods for estimating a hazard ratio connecting the first and second gap times. Specifically, a two-stage procedure is developed based on estimating equations. At the first stage, a proportional hazards model is fitted for the first gap time. Weighted estimating equations are then solved at the second stage to estimate the hazard ratio between the first and second gap times...
December 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/29292402/structured-detection-of-interactions-with-the-directed-lasso
#10
Hristina Pashova, Michael LeBlanc, Charles Kooperberg
When considering low-dimensional gene-treatment or gene-environment interactions we might suspect groups of genes to interact with treatment or environment in a similar way. For example, genes associated with related biological processes might interact with an environmental factor or a clinical treatment in its effect on a phenotype correspondingly. We use the idea of a structured interaction model together with penalized regression to limit the model complexity in a model in which we believe the interactions might behave in a similar way...
December 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/29250207/dynamic-prediction-of-renal-failure-using-longitudinal-biomarkers-in-a-cohort-study-of-chronic-kidney-disease
#11
Liang Li, Sheng Luo, Bo Hu, Tom Greene
In longitudinal studies, prognostic biomarkers are often measured longitudinally. It is of both scientific and clinical interest to predict the risk of clinical events, such as disease progression or death, using these longitudinal biomarkers as well as other time-dependent and time-independent information about the patient. The prediction is dynamic in the sense that it can be made at any time during the follow-up, adapting to the changing at-risk population and incorporating the most recent longitudinal data...
December 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/29225712/a-look-ahead-strategy-for-non-directed-donors-in-kidney-paired-donation
#12
Wen Wang, Mathieu Bray, Peter X-K Song, John D Kalbfleisch
While there is a growing need for kidney transplants to treat end stage kidney disease, the supply of transplantable kidneys is in serious shortage. Kidney paired donation (KPD) programs serve as platforms for candidates with willing but incompatible donors to assess the possibility of exchanging donors, thus opening up new transplant opportunities for these candidates. In recent years, non-directed (or altruistic) donors (NDDs) have been incorporated into KPD programs beginning chains of transplants that benefit many candidates...
December 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/28966695/ipi59-an-actionable-biomarker-to-improve-treatment-response-in-serous-ovarian-carcinoma-patients
#13
J Choi, S Ye, K H Eng, K Korthauer, W H Bradley, J S Rader, C Kendziorski
Despite improvements in operative management and therapies, overall survival rates in advanced ovarian cancer have remained largely unchanged over the past three decades. Although it is possible to identify high-risk patients following surgery, the knowledge does not provide information about the genomic aberrations conferring risk, or the implications for treatment. To address these challenges, we developed an integrative pathway-index model and applied it to messenger RNA expression from 458 patients with serous ovarian carcinoma from the Cancer Genome Atlas project...
June 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/28959368/a-model-based-approach-for-species-abundance-quantification-based-on-shotgun-metagenomic-data
#14
Eric Z Chen, Frederic D Bushman, Hongzhe Li
The human microbiome, which includes the collective microbes residing in or on the human body, has a profound influence on the human health. DNA sequencing technology has made the large-scale human microbiome studies possible by using shotgun metagenomic sequencing. One important aspect of data analysis of such metagenomic data is to quantify the bacterial abundances based on the metagenomic sequencing data. Existing methods almost always quantify such abundances one sample at a time, which ignore certain systematic differences in read coverage along the genomes due to GC contents, copy number variation and the bacterial origin of replication...
June 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/28919931/improving-hierarchical-models-using-historical-data-with-applications-in-high-throughput-genomics-data-analysis
#15
Ben Li, Yunxiao Li, Zhaohui S Qin
Modern high-throughput biotechnologies such as microarray and next generation sequencing produce a massive amount of information for each sample assayed. However, in a typical high-throughput experiment, only limited amount of data are observed for each individual feature, thus the classical 'large p , small n ' problem. Bayesian hierarchical model, capable of borrowing strength across features within the same dataset, has been recognized as an effective tool in analyzing such data. However, the shrinkage effect, the most prominent feature of hierarchical features, can lead to undesirable over-correction for some features...
June 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/28785367/prediction-oriented-marker-selection-promise-with-application-to-high-dimensional-regression
#16
Soyeon Kim, Veerabhadran Baladandayuthapani, J Jack Lee
In personalized medicine, biomarkers are used to select therapies with the highest likelihood of success based on an individual patient's biomarker/genomic profile. Two goals are to choose important biomarkers that accurately predict treatment outcomes and to cull unimportant biomarkers to reduce the cost of biological and clinical verifications. These goals are challenging due to the high dimensionality of genomic data. Variable selection methods based on penalized regression (e.g., the lasso and elastic net) have yielded promising results...
June 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/28781713/estimation-of-stratified-mark-specific-proportional-hazards-models-under-two-phase-sampling-with-application-to-hiv-vaccine-efficacy-trials
#17
Guangren Yang, Yanqing Sun, Li Qi, Peter B Gilbert
An objective of preventive HIV vaccine efficacy trials is to understand how vaccine-induced immune responses to specific protein sequences of HIV-1 associate with subsequent infection with specific sequences of HIV, where the immune response biomarkers are measured in vaccine recipients via a two-phase sampling design. Motivated by this objective, we investigate the stratified mark-specific proportional hazards model under two-phase biomarker sampling, where the mark is the genetic distance of an infecting HIV-1 sequence to an HIV-1 sequence represented inside the vaccine...
June 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/28781712/trom-a-testing-based-method-for-finding-transcriptomic-similarity-of-biological-samples
#18
Wei Vivian Li, Yiling Chen, Jingyi Jessica Li
Comparative transcriptomics has gained increasing popularity in genomic research thanks to the development of high-throughput technologies including microarray and next-generation RNA sequencing that have generated numerous transcriptomic data. An important question is to understand the conservation and divergence of biological processes in different species. We propose a testing-based method TROM (Transcriptome Overlap Measure) for comparing transcriptomes within or between different species, and provide a different perspective, in contrast to traditional correlation analyses, about capturing transcriptomic similarity...
June 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/28781711/annotation-regression-for-genome-wide-association-studies-with-an-application-to-psychiatric-genomic-consortium-data
#19
Sunyoung Shin, Sündüz Keleş
Although genome-wide association studies (GWAS) have been successful at finding thousands of disease-associated genetic variants (GVs), identifying causal variants and elucidating the mechanisms by which genotypes influence phenotypes are critical open questions. A key challenge is that a large percentage of disease-associated GVs are potential regulatory variants located in noncoding regions, making them difficult to interpret. Recent research efforts focus on going beyond annotating GVs by integrating functional annotation data with GWAS to prioritize GVs...
June 2017: Statistics in Biosciences
https://www.readbyqxmd.com/read/28694879/estimating-a-treatment-effect-in-residual-time-quantiles-under-the-additive-hazards-model
#20
Luis Alexander Crouch, Cheng Zheng, Ying Qing Chen
For randomized clinical trials where the endpoint of interest is a time-to-event subject to censoring, estimating the treatment effect has mostly focused on the hazard ratio from the Cox proportional hazards model. Since the model's proportional hazards assumption is not always satisfied, a useful alternative, the so-called additive hazards model, may instead be used to estimate a treatment effect on the difference of hazard functions. Still, the hazards difference may be difficult to grasp intuitively, particularly in a clinical setting of, e...
June 2017: Statistics in Biosciences
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