5 Works

A semi-parametric Bayesian approach for detection of gene expression heterosis with RNA-seq data

Ran Bi & Peng Liu
Heterosis refers to the superior performance of a hybrid offspring over its two inbred parents. Although heterosis has been widely observed in agriculture, its molecular mechanism is not well studied. Recent advances in high-throughput genomic technologies such as RNA sequencing (RNA-seq) facilitate the investigation of heterosis at the gene expression level. However, it is challenging to identify genes exhibiting heterosis using RNA-seq data because high-dimension of hypotheses tests are conducted with limited sample size. Furthermore,...

A semi-parametric Bayesian approach for detection of gene expression heterosis with RNA-seq data

Ran Bi & Peng Liu
Heterosis refers to the superior performance of a hybrid offspring over its two inbred parents. Although heterosis has been widely observed in agriculture, its molecular mechanism is not well studied. Recent advances in high-throughput genomic technologies such as RNA sequencing (RNA-seq) facilitate the investigation of heterosis at the gene expression level. However, it is challenging to identify genes exhibiting heterosis using RNA-seq data because high-dimension of hypotheses tests are conducted with limited sample size. Furthermore,...

Phylogeny of the supertribe Nebriitae (Coleoptera: Carabidae) based on analyses of DNA sequence data

David H. Kavanaugh, David Maddison, W. Brian Simison, Sean D. Schoville, Joachim Schmidt, Arnaud Faille, Wendy Moore, James M. Pflug, Sophie L. Archambeault, Tinya Hoang & Jei-Ying Chen
The phylogeny of the carabid beetle supertribe Nebriitae is inferred from analyses of DNA sequence data from eight gene fragments including one nuclear ribosomal gene (28S), four nuclear-protein coding genes (CAD, topoisomerase 1, PEPCK and wingless) and three mitochondrial gene fragments (16S + tRNA-Leu + ND1, COI (“barcode” region) and COI (“Pat/Jer” region)). Our taxon sample included 264 exemplars representing 241 species and subspecies (25% of the known nebriite fauna), 39 of 41 currently accepted...

Value Function Guided Subgroup Identification via Gradient Tree Boosting: A Framework to Handle Multiple Outcomes for Optimal Treatment Recommendation

Pingye Zhang, Peng Liu, Junshui Ma & Yue Shentu
In randomized clinical trials, there has been an increasing interest in identifying subgroups with heterogeneous responses to study treatment based on baseline patient characteristics. Even though the benefit risk assessment of any patient population or subgroups is almost always a multi-facet consideration, the statistical literature of subgroup identification has largely been limited to a single clinical outcome. In the article, we propose a nonparametric method that searches for subgroup membership scores by maximizing a value...

Value Function Guided Subgroup Identification via Gradient Tree Boosting: a Framework to Handle Multiple Outcomes for Optimal Treatment Recommendation

Pingye Zhang, Peng Liu, Junshui Ma & Yue Shentu
In randomized clinical trials, there has been an increasing interest in identifying subgroups with heterogeneous responses to study treatment based on baseline patient characteristics. Even though the benefit risk assessment of any patient population or subgroups is almost always a multi-facet consideration, the statistical literature of subgroup identification has largely been limited to a single clinical outcome. In the paper, we propose a nonparametric method that searches for subgroup membership scores by maximizing a value...

Registration Year

  • 2021
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Resource Types

  • Text
    4
  • Dataset
    1

Affiliations

  • University of Wisconsin System
    5
  • Donald Danforth Plant Science Center
    4
  • Central South University
    4
  • Jiangsu University of Science and Technology
    4
  • Southern Medical University
    4
  • Shenzhen University
    4
  • University of Wisconsin–Madison
    4
  • Sheng Jing Hospital
    4
  • Chinese Academy of Medical Sciences & Peking Union Medical College
    4
  • Kyoto University
    4