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Statistical Applications in Genetics and Molecular Biology

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https://read.qxmd.com/read/30772870/discrete-wavelet-packet-transform-based-discriminant-analysis-for-whole-genome-sequences
#1
Hsin-Hsiung Huang, Senthil Balaji Girimurugan
In recent years, alignment-free methods have been widely applied in comparing genome sequences, as these methods compute efficiently and provide desirable phylogenetic analysis results. These methods have been successfully combined with hierarchical clustering methods for finding phylogenetic trees. However, it may not be suitable to apply these alignment-free methods directly to existing statistical classification methods, because an appropriate statistical classification theory for integrating with the alignment-free representation methods is still lacking...
February 18, 2019: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30759070/lcox-a-tool-for-selecting-genes-related-to-survival-outcomes-using-longitudinal-gene-expression-data
#2
Jiehuan Sun, Jose D Herazo-Maya, Jane-Ling Wang, Naftali Kaminski, Hongyu Zhao
Longitudinal genomics data and survival outcome are common in biomedical studies, where the genomics data are often of high dimension. It is of great interest to select informative longitudinal biomarkers (e.g. genes) related to the survival outcome. In this paper, we develop a computationally efficient tool, LCox, for selecting informative biomarkers related to the survival outcome using the longitudinal genomics data. LCox is powerful to detect different forms of dependence between the longitudinal biomarkers and the survival outcome...
February 13, 2019: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30735484/meta-analytic-framework-for-modeling-genetic-coexpression-dynamics
#3
Tyler G Kinzy, Timothy K Starr, George C Tseng, Yen-Yi Ho
Methods for exploring genetic interactions have been developed in an attempt to move beyond single gene analyses. Because biological molecules frequently participate in different processes under various cellular conditions, investigating the changes in gene coexpression patterns under various biological conditions could reveal important regulatory mechanisms. One of the methods for capturing gene coexpression dynamics, named liquid association (LA), quantifies the relationship where the coexpression between two genes is modulated by a third "coordinator" gene...
February 9, 2019: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30685747/sliced-inverse-regression-for-integrative-multi-omics-data-analysis
#4
Yashita Jain, Shanshan Ding, Jing Qiu
Advancement in next-generation sequencing, transcriptomics, proteomics and other high-throughput technologies has enabled simultaneous measurement of multiple types of genomic data for cancer samples. These data together may reveal new biological insights as compared to analyzing one single genome type data. This study proposes a novel use of supervised dimension reduction method, called sliced inverse regression, to multi-omics data analysis to improve prediction over a single data type analysis. The study further proposes an integrative sliced inverse regression method (integrative SIR) for simultaneous analysis of multiple omics data types of cancer samples, including MiRNA, MRNA and proteomics, to achieve integrative dimension reduction and to further improve prediction performance...
January 26, 2019: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30685746/a-powerful-test-for-ordinal-trait-genetic-association-analysis
#5
Yuan Xue, Jinjuan Wang, Juan Ding, Sanguo Zhang, Qizhai Li
Response selective sampling design is commonly adopted in genetic epidemiologic study because it can substantially reduce time cost and increase power of identifying deleterious genetic variants predispose to human complex disease comparing with prospective design. The proportional odds model (POM) can be used to fit data obtained by this design. Unlike the logistic regression model, the estimated genetic effect based on POM by taking data as being enrolled prospectively is inconsistent. So the power of resulted Wald test is not satisfactory...
January 26, 2019: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30667368/sample-size-calculations-for-the-differential-expression-analysis-of-rna-seq-data-using-a-negative-binomial-regression-model
#6
Xiaohong Li, Dongfeng Wu, Nigel G F Cooper, Shesh N Rai
High throughput RNA sequencing (RNA-seq) technology is increasingly used in disease-related biomarker studies. A negative binomial distribution has become the popular choice for modeling read counts of genes in RNA-seq data due to over-dispersed read counts. In this study, we propose two explicit sample size calculation methods for RNA-seq data using a negative binomial regression model. To derive these new sample size formulas, the common dispersion parameter and the size factor as an offset via a natural logarithm link function are incorporated...
January 22, 2019: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30653470/mlml2r-an-r-package-for-maximum-likelihood-estimation-of-dna-methylation-and-hydroxymethylation-proportions
#7
Samara F Kiihl, Maria Jose Martinez-Garrido, Arce Domingo-Relloso, Jose Bermudez, Maria Tellez-Plaza
Accurately measuring epigenetic marks such as 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC) at the single-nucleotide level, requires combining data from DNA processing methods including traditional (BS), oxidative (oxBS) or Tet-Assisted (TAB) bisulfite conversion. We introduce the R package MLML2R, which provides maximum likelihood estimates (MLE) of 5-mC and 5-hmC proportions. While all other available R packages provide 5-mC and 5-hmC MLEs only for the oxBS+BS combination, MLML2R also provides MLE for TAB combinations...
January 17, 2019: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30507552/a-practical-approach-to-adjusting-for-population-stratification-in-genome-wide-association-studies-principal-components-and-propensity-scores-pcaps
#8
Huaqing Zhao, Nandita Mitra, Peter A Kanetsky, Katherine L Nathanson, Timothy R Rebbeck
Genome-wide association studies (GWAS) are susceptible to bias due to population stratification (PS). The most widely used method to correct bias due to PS is principal components (PCs) analysis (PCA), but there is no objective method to guide which PCs to include as covariates. Often, the ten PCs with the highest eigenvalues are included to adjust for PS. This selection is arbitrary, and patterns of local linkage disequilibrium may affect PCA corrections. To address these limitations, we estimate genomic propensity scores based on all statistically significant PCs selected by the Tracy-Widom (TW) statistic...
December 4, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30447151/a-novel-method-to-accurately-calculate-statistical-significance-of-local-similarity-analysis-for-high-throughput-time-series
#9
Fang Zhang, Ang Shan, Yihui Luan
In recent years, a large number of time series microbial community data has been produced in molecular biological studies, especially in metagenomics. Among the statistical methods for time series, local similarity analysis is used in a wide range of environments to capture potential local and time-shifted associations that cannot be distinguished by traditional correlation analysis. Initially, the permutation test is popularly applied to obtain the statistical significance of local similarity analysis. More recently, a theoretical method has also been developed to achieve this aim...
November 17, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30231014/assessing-genome-wide-significance-for-the-detection-of-differentially-methylated-regions
#10
Christian M Page, Linda Vos, Trine B Rounge, Hanne F Harbo, Bettina K Andreassen
DNA methylation plays an important role in human health and disease, and methods for the identification of differently methylated regions are of increasing interest. There is currently a lack of statistical methods which properly address multiple testing, i.e. control genome-wide significance for differentially methylated regions. We introduce a scan statistic (DMRScan), which overcomes these limitations. We benchmark DMRScan against two well established methods (bumphunter, DMRcate), using a simulation study based on real methylation data...
September 19, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30205662/a-variable-selection-approach-in-the-multivariate-linear-model-an-application-to-lc-ms-metabolomics-data
#11
Marie Perrot-Dockès, Céline Lévy-Leduc, Julien Chiquet, Laure Sansonnet, Margaux Brégère, Marie-Pierre Étienne, Stéphane Robin, Grégory Genta-Jouve
Omic data are characterized by the presence of strong dependence structures that result either from data acquisition or from some underlying biological processes. Applying statistical procedures that do not adjust the variable selection step to the dependence pattern may result in a loss of power and the selection of spurious variables. The goal of this paper is to propose a variable selection procedure within the multivariate linear model framework that accounts for the dependence between the multiple responses...
September 8, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30169328/biology-challenging-statistics
#12
EDITORIAL
Michael P H Stumpf
No abstract text is available yet for this article.
August 30, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30142087/editorial-change-at-statistical-applications-in-genetics-and-molecular-biology
#13
Torsten Krüger
No abstract text is available yet for this article.
August 24, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30059350/a-test-for-detecting-differential-indirect-trans-effects-between-two-groups-of-samples
#14
Nimisha Chaturvedi, Renée X de Menezes, Jelle J Goeman, Wessel van Wieringen
Integrative analysis of copy number and gene expression data can help in understanding the cis and trans effect of copy number aberrations on transcription levels of genes involved in a pathway. To analyse how these copy number mediated gene-gene interactions differ between groups of samples we propose a new method, named dNET. Our method uses ridge regression to model the network topology involving one gene's expression level, its gene dosage and the expression levels of other genes in the network. The interaction parameters are estimated by fitting the model per gene for all samples together...
July 31, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/30007059/on-the-relation-between-the-true-and-sample-correlations-under-bayesian-modelling-of-gene-expression-datasets
#15
Royi Jacobovic
No abstract text is available yet for this article.
July 14, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/29975669/empirical-bayesian-approach-to-testing-multiple-hypotheses-with-separate-priors-for-left-and-right-alternatives
#16
Naveen K Bansal, Mehdi Maadooliat, Steven J Schrodi
No abstract text is available yet for this article.
July 5, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/29959888/comparisons-of-classification-methods-for-viral-genomes-and-protein-families-using-alignment-free-vectorization
#17
COMPARATIVE STUDY
Hsin-Hsiung Huang, Shuai Hao, Saul Alarcon, Jie Yang
No abstract text is available yet for this article.
June 30, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/29897889/a-statistical-method-for-measuring-activation-of-gene-regulatory-networks
#18
Gustavo H Esteves, Luiz F L Reis
MOTIVATION: Gene expression data analysis is of great importance for modern molecular biology, given our ability to measure the expression profiles of thousands of genes and enabling studies rooted in systems biology. In this work, we propose a simple statistical model for the activation measuring of gene regulatory networks, instead of the traditional gene co-expression networks. RESULTS: We present the mathematical construction of a statistical procedure for testing hypothesis regarding gene regulatory network activation...
June 13, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/29897888/multi-locus-data-distinguishes-between-population-growth-and-multiple-merger-coalescents
#19
Jere Koskela
We introduce a low dimensional function of the site frequency spectrum that is tailor-made for distinguishing coalescent models with multiple mergers from Kingman coalescent models with population growth, and use this function to construct a hypothesis test between these model classes. The null and alternative sampling distributions of the statistic are intractable, but its low dimensionality renders them amenable to Monte Carlo estimation. We construct kernel density estimates of the sampling distributions based on simulated data, and show that the resulting hypothesis test dramatically improves on the statistical power of a current state-of-the-art method...
June 13, 2018: Statistical Applications in Genetics and Molecular Biology
https://read.qxmd.com/read/29886455/non-parametric-estimation-of-population-size-changes-from-the-site-frequency-spectrum
#20
Berit Lindum Waltoft, Asger Hobolth
Changes in population size is a useful quantity for understanding the evolutionary history of a species. Genetic variation within a species can be summarized by the site frequency spectrum (SFS). For a sample of size n, the SFS is a vector of length n - 1 where entry i is the number of sites where the mutant base appears i times and the ancestral base appears n - i times. We present a new method, CubSFS, for estimating the changes in population size of a panmictic population from an observed SFS. First, we provide a straightforward proof for the expression of the expected site frequency spectrum depending only on the population size...
June 11, 2018: Statistical Applications in Genetics and Molecular Biology
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