存在潜在模型偏误时小域估计的不确定性评价:一带一路法

当可能存在模型偏误时,现有结果表明小域估计中观测最佳预测比传统的经验最佳线性无偏预测的预测精度更高,表现更加稳健.然而,出于稳健性考虑,实际所用的假设模型无法直接用于推导观测最佳预测相关的均方预测误差的估计,从而导致其不确定性评价变得困难重重.有鉴于此,本文着重考虑观测最佳预测有关均方预测误差的估计问题,提出一类具有解析形式的针对无条件均方预测误差的估计,并在一定条件下推导出相关估计的二阶无偏性.模拟和实际数据例子均表明本文提出的新估计无论在理论方面还是在有限样本性质方面都有着比现有估计更好的表现.

Phased,chromosome-scale genome assemblies of tetraploid potato reveal a complex genome,transcriptome,and predicted proteome landscape underpinning genetic diversity

Cultivated potato is a clonally propagated autotetraploid species with a highly heterogeneous genome.Phased assemblies of six cultivars including two chromosome-scale phased genome assemblies revealed extensive allelic diversity,including altered coding and transcript sequences,preferential allele expression,and structural variation that collectively result in a highly complex transcriptome and predicted proteome,which are distributed across the homologous chromosomes.Wild species contribute to the extensive allelic diversity in tetraploid cultivars,demonstrating ancestral introgressions predating modern breeding efforts.As a clonally propagated autotetraploid that undergoes limited meiosis,dysfunctional and deleterious alleles are not purged in tetraploid potato.Nearly a quarter of the loci bore mutations are predicted to have a high negative impact on protein function,complicating breeder’s efforts to reduce genetic load.The StCDF1 locus controls maturity,and analysis of six tetraploid genomes revealed that 12 allelic variants of StCDF1 are correlated with maturity in a dosage-dependent manner.Knowledge of the complexity of the tetraploid potato genome with its rampant structural variation and embedded deleterious and dysfunctional alleles will be key not only to implementing precision breeding of tetraploid cultivars but also to the construction of homozygous,diploid potato germplasm containing favorable alleles to capitalize on heterosis in F1 hybrids.

Local Changes in Chromatin Accessibility and Transcriptional Networks Underlying the Nitrate Response in Arabidopsis Roots

Transcriptional regulation,determined by the chromatin structure and regulatory elements interacting at pro-moter regions,is a key step in plant responses to environmental cues.Nitrate(NO3-)is a nutrient signal that regulates the expression of hundreds of genes in Arabidopsis thaliana.Here,we integrate mRNA sequencing,genome-wide RNA polymeraseⅡ(RNPⅡ),chromatin immunoprecipitation sequencing,and DNase Sequencing datasets to establish the relationship between RNPⅡoccupancy and chromatin accessibility in response to NO3-treatments in Arabidopsis roots.Genomic footprinting allowed us to identify in vivo regula-tory elements controlling gene expression in response to NO3-treatments.NO3--modulated transcription factor(TF)footprints are important for a rapid increase in RNPⅡoccupancy and transcript accumulation over time.We mapped key TF regulatory interactions and functionally validated the role of NAP,an NAC-domain containing TF,as a new regulatory factor in NO3-transport.Taken together,our study provides a comprehensive view of transcriptional networks in response to a nutrient signal in Arabidopsis roots.

Power analysis,sample size calculation for testing the largest binomial probability

A procedure is developed for power analysis and sample size calculation for a class of complex testing problems regarding the largest binomial probability under a combination of treatments.It is shown that the asymptotic null distribution of the likelihood-ratio statistic is not parameterfree,but χ_(1)^(2) is a conservative asymptotic null distribution.A nonlinear Gauss-Seidel algorithm is proposed to uniquely determine the alternative for the power and sample size calculation given the baseline binomial probability.An example from an animal clinical trial is discussed.

A discussion of prior-based Bayesian information criterion (PBIC)

Professor Bayarri and coauthors’ paper (hereafter,PBIC) offers a stimulating and welcomed addition tothe already extensive and yet still rapid expanding literature on model selection and related topics. In a 2013review on model selection in linear mixed models byMüller, Scealy, and Welsh (2013), the authors classified main approaches in mixed model selection intothree categories, the information criteria, the shrinkagemethods and the fence methods. The current paper isnot specifically regarding mixed model selection problems;however, as one shall see, there is a connection invarious ways.