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Screening-Assisted Dynamic Multiple Testing with false discovery rate Control

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Journal of Systems Science & Complexity 2023年第2期36卷 716-754页

作者： MUSHTAQ Iram ZHOU Qin ZI Xuemin School of Statistics and Data Science LPMC and KLMDASRNankai UniversityTianjin 300071China School of Mathematics and Statistics Jiangsu Normal UniversityXuzhou 221116China School of Science Tianjin University of Technology and EducationTianjin 300350China

In the era of big data,high-dimensional data always arrive in streams,making timely and accurate decision necessary.It has become particularly important to rapidly and sequentially identify individuals whose behavior deviates from the norm.Aiming at identifying as many irregular behavioral patterns as possible,the authors develop a large-scale dynamic testing system in the framework of false discovery rate(FDR)control.By fully exploiting the sequential feature of datastreams,the authors propose a screening-assisted procedure that filters streams and then only tests streams that pass the filter at each time point.A data-driven optimal screening threshold is derived,giving the new method an edge over existing methods.Under some mild conditions on the dependence structure of datastreams,the FDR is shown to be strongly controlled and the suggested approach for determining screening thresholds is asymptotically optimal.Simulation studies show that the proposed method is both accurate and powerful,and a real-data example is used for illustrative purpose.

关键词： Change-point false discovery rate high-dimensional datastreams large-scale inference sequential analysis weak dependence structure

Support Recovery of Gaussian Graphical Model with false discovery rate Control

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Journal of Systems Science & Complexity 2023年第6期36卷 2605-2623页

作者： ZHANG Yuhao LIU Yanhong WANG Zhaojun School of Mathematics and Statistics Jiangsu Normal UniversityXuzhou221116China School of Statistics and Data Science Nankai UniversityTianjin300071China

This paper focuses on the support recovery of the Gaussian graphical model(GGM)with false discovery rate(FDR)control.The graceful symmetrized data aggregation(SDA)technique which involves sample splitting,data screening and information pooling is exploited via a node-based way.A matrix of test statistics with symmetry property is constructed and a data-driven threshold is chosen to control the FDR for the support recovery of GGM.The proposed method is shown to control the FDR asymptotically under some mild conditions.Extensive simulation studies and a real-data example demonstrate that it yields a better FDR control while offering reasonable power in most cases.

关键词： false discovery rate Gaussian graphical model support recovery symmetrized data aggregation

A protocol of using PTMiner for quality control and localization of protein modifications identified by open or closed search of tandem mass spectra

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Biophysics Reports 2022年第Z1期8卷 269-281页

作者： Zhiyuan Cheng Ge Song Yan Fu Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences Graduate School of Peking Union Medical College National Institute of Biological Sciences

In recent years, an open search of tandem mass spectra has greatly promoted the detection of posttranslational modifications(PTMs) in shotgun proteomics. However, post-processing of the results from open searches remains an unsatisfactorily resolved problem, which hinders the open search mode from wide practical use. PTMiner is a software tool based on dedicated statistical algorithms for reliable filtering, localization and annotation of the modifications(mass shifts) detected by open search.Furthermore, PTMiner also supports quality control and re-localization of modifications identified by the traditional closed search. In this protocol, we describe how to use PTMiner for the two search modes. Currently, the search engines supported by PTMiner include pFind, MSFragger, MaxQuant,Comet, MS-GF + and SEQUEST.

关键词： Modification identification Open search false discovery rate Modification localization false localization rate

The Statistical Power of Inclusive Composite Interval Mapping in Detecting Digenic Epistasis Showing Common F_2 Segregation Ratios

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Journal of Integrative Plant Biology 2012年第4期54卷 270-279页

作者： Luyan Zhang Huihui Li Jiankang Wang Institute of Crop Sciences The National Key Facility for Crop Gene Resources and Genetic Improvementand CIMMYT ChinaChinese Academy of Agricultural SciencesBeijing 100081China

Epistasis is a commonly observed genetic phenomenon and an important source of variation of complex traits, which could maintain additive variance and therefore assure the long-term genetic gain in breeding. Inclusive composite interval mapping （ICIM） is able to identify epistatic quantitative trait loci （QTLs） no matter whether the two interacting QTLs have any additive effects. In this article, we conducted a simulation study to evaluate detection power and false discovery rate （FDR） of ICIM epistatic mapping, by considering F2 and doubled haploid （DH） populations, different F2 segregation ratios and population sizes. Results indicated that estimations of QTL locations and effects were unbiased, and the detection power of epistatic mapping was largely affected by population size, heritability of epistasis, and the amount and distribution of genetic effects. When the same likelihood of odd （LOD） threshold was used, detection power of QTL was higher in F2 population than power in DH population; meanwhile FDR in F2 was also higher than that in DH. The increase of marker density from 10 cM to 5 cM led to similar detection power but higher FDR. In simulated populations, ICIM achieved better mapping results than multiple interval mapping （MIM） in estimation of QTL positions and effect. At the end, we gave epistatic mapping results of ICIM in one actual population in rice （Oryza sativa L.）.

关键词： Epistasis false discovery rate inclusive composite interval mapping power analysis simulation study.

FDR Control for Pairwise Comparisons of Normal Means Based on Goodness of Fit Test

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Acta Mathematicae Applicatae Sinica 2016年第3期32卷 701-712页

作者： Pei JIN Xing-zhong XU Na LI School of Mathematics and Statistics Beijing Institute of Technology School of Economics and Management University of the Chinese Academy of Sciences

This study is undertaken to apply a bootstrap method of controlling the false discovery rate （FDR） when performing pairwise comparisons of normal means. Due to the dependency of test statistics in pairwise comparisons, many conventional multiple testing procedures can＇t be employed directly. Some modified pro- cedures that control FDR with dependent test statistics are too conservative. In the paper, by bootstrap and goodness-of-fit methods, we produce independent p-values for pairwise comparisons. Based on these indepen- dent p-values, plenty of procedures can be used, and two typical FDR controlling procedures are applied here. An example is provided to illustrate the proposed approach. Extensive simulations show the satisfactory FDR control and power performance of our approach. In addition, the proposed approach can be easily extended to more than two normal, or non-normal, balance or unbalance cases.

关键词： multiple testing false discovery rate goodness-of-fit test pairwise comparisons p-value resampling

A Genome Wide Association Study for Longevity in Cattle

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Open Journal of Genetics 2014年第1期4卷 46-55页

作者： Gabor Meszaros Sophie Eaglen Patrik Waldmann Johann Solkner Division of Livestock Sciences Department of Sustainable Agricultural SystemsUniversity of Natural Resources and Life SciencesViennaAustria Division of Statistics Department of Computer and Information ScienceLinkoping UniversityLinkopingSweden

Longevity is regarded as the most important functional trait in cattle breeding with high economic value yet low heritability. In order to identify genomic regions associated with longevity, a genome wise association study was performed using data from 4887 Fleckvieh bulls and 33,556 SNPs after quality control. Single SNP regression was used for identification of important SNPs including eigenvectors as a means of correction for population structure. SNPs selected with a false discovery rate threshold of 0.05 and with local false discovery rate identified genomic regions associated with longevity which were subsequently cross checked with the National Center for Biotechnology Information (NCBI) database. This, to identify interesting genes in cattle and their homologue forms in other species. The most notable genes were SYT10 located on chromosome 5, ADAMTS3 on chromosome 6, NTRK2 on chromosome 8 and SNTG1 on chromosome 14 of the cattle genome. Several of the genes found have previously been associated with cattle fertility. Poor fertility is an important culling reason and thereby affects longevity in cattle. Several signals were located in regions sparse with described genes, which suggest that there might be several other non-identified genetic pathways for this important trait.

关键词： Genome Wide Association Longevity false discovery rate Population Structure Cattle