Dataset Information

Efficient Signal Inclusion With Genomic Applications.

ABSTRACT: This paper addresses the challenge of efficiently capturing a high proportion of true signals for subsequent data analyses when sample sizes are relatively limited with respect to data dimension. We propose the signal missing rate as a new measure for false negative control to account for the variability of false negative proportion. Novel data-adaptive procedures are developed to control signal missing rate without incurring many unnecessary false positives under dependence. We justify the efficiency and adaptivity of the proposed methods via theory and simulation. The proposed methods are applied to GWAS on human height to effectively remove irrelevant SNPs while retaining a high proportion of relevant SNPs for subsequent polygenic analysis.

SUBMITTER: Jeng XJ

PROVIDER: S-EPMC6953619 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Efficient Signal Inclusion With Genomic Applications.

Jeng X Jessie XJ Zhang Teng T Tzeng Jung-Ying JY

Journal of the American Statistical Association 20190227 528

This paper addresses the challenge of efficiently capturing a high proportion of true signals for subsequent data analyses when sample sizes are relatively limited with respect to data dimension. We propose the signal missing rate as a new measure for false negative control to account for the variability of false negative proportion. Novel data-adaptive procedures are developed to control signal missing rate without incurring many unnecessary false positives under dependence. We justify the effi ...[more]

PMID: 31929665

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Project description:Implant osteoinduction and subsequent osteogenic activity are critical events that need improvement for regenerative healing of large craniofacial bone defects. Here we describe the augmentation of the mineral content of a class of mineralized collagen scaffolds under development for craniomaxillofacial bone regeneration via the inclusion of zinc ions to promote osteogenesis in vitro. Zinc is an essential trace element in skeletal tissue and bone, with soluble zinc being shown to promote osteogenic differentiation of porcine adipose derived stem cells. We report the development of a new class of zinc functionalized scaffolds fabricated by adding zinc sulfate to a mineralized collagen-glycosaminoglycan precursor suspension that was then freeze dried to form a porous biomaterial. We report analysis of zinc functionalized scaffolds via imaging (scanning electron microscopy), mechanical testing (compression), and compositional (X-ray diffraction, inductively coupled plasma mass spectrometry) analyses. Notably, zinc-functionalized scaffolds display morphological changes to the mineral phase and altered elastic modulus without substantially altering the composition of the brushite phase or removing the micro-scale pore morphology of the scaffold. These scaffolds also display zinc release kinetics on the order of days to weeks and promote successful growth and pro-osteogenic capacity of porcine adipose derived stem cells cultured within these zinc scaffolds. Taken together, we believe that zinc functionalized scaffolds provide a unique platform to explore strategies to improve in vivo osteogenesis in craniomaxillofacial bone injuries models. STATEMENT OF SIGNIFICANCE: Craniomaxillofacial bone defects that arise from traumatic, congenital, and post-oncologic origins cannot heal on their own and often require surgical intervention. We have developed a class of mineralized collagen scaffolds that promotes osteogenesis and bone regeneration. Here we describe the inclusion of zinc sulfate into the mineralized collagen scaffold to improve osteogenesis. Zinc functionalized scaffolds demonstrate altered crystallite microstructure but consistent Brushite chemistry, improved mechanics, and promote zinc transporter expression while supporting stem cell viability, osteogenic differentiation, and mineral biosynthesis.

Dataset Information

Efficient Signal Inclusion With Genomic Applications.

Publications

Efficient Signal Inclusion With Genomic Applications.

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