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    DCEG fellowships and training in cancer epidemiology and genetics includes robust professional development, mentoring, and competitive stipends

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    • Make your career a priority this #NewYear! Find a fellowship in #CancerResearch #epidemiology #genetics #biostatistics: https://t.co/pdf88huTuG #EpiTwitter @UNCpublichealth @umichsph @YaleSPH @uabSOPH @UCLAFSPH @uscphs @PittPubHealth @TAMU_SPH @UMDPublicHealth @TulaneSPHTM

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    Statistics in Oncology - 2 year(s) ago

    © 2022 by American Society of Clinical OncologyConception and design: All authorsCollection and assembly of data: All authorsData analysis and interpretation: All authorsManuscript writing: All authorsFinal approval of manuscript: All authorsAccountable for all aspects of the work: All authorsAUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTERESTStatistics in OncologyThe following represents…

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    • 🗒️ #JCO #Review: Statistics in Oncology https://t.co/dfYRtOXq0T @AlexiaIasonos #biostatistics

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    Author summary In recent years, there is an increased interest of estimating heritability from genome-wide SNP data in large scale cohort studies. Here, we propose the PredLMM, a computationally rapid and memory-efficient linear mixed model for heritability estimation. The proposed approach can estimate SNP heritability on Biobank-scale datasets in a fraction of time compared to the existing…

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    • Seal et al present PredLMM: a computationally rapid and memory-efficient linear mixed model for #heritability estimation They demonstrate the method by estimating heritability for quantitative traits using #UKBioBank data #Biostatistics #Genetics https://t.co/BJ3UnRznEb

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    Author summary It is well known that nonrandom selection in one-sample Mendelian Randomization (MR) can result in biased estimates and inflated type I error rates. Actually, two-sample MR analyses are more prone to be affected by nonrandom selection than one-sample MR analyses, because two samples for genome-wide association studies (GWAS) may be selected each under different mechanisms from the…

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    • New research on #MendelianRandomization: Yu et al use simulations to reveal how nonrandom selection in MR analyses can cause bias and type I error They compare how nonrandom selection affects 8 different MR methods #genetics #biostatistics https://t.co/7Hhl8oYlbJ

  • Mashup Score: 1

    NCI’s Division of Cancer Epidemiology and Genetics offers one of the largest training programs in cancer epidemiology. As a fellow, you’ll work with cancer e…

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    • Happening NOW 3pm-4:30: Come visit DCEG's booth with @DianeWigfield to learn more about #postdoc #fellowships in #epidemiology #biostatistics #genetics and more at the @NIH Graduate and Professional School Fair #GPfair22 Learn about fellowships in DCEG: https://t.co/pJzAEKuUaO

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    Author summary Hi-C data is used to understand how chromosomes are ordered in a cell. Often, this data is made up of different kinds of cells. Usually, we do not know the number of each kind of cell in the data. When we study Hi-C data, we must learn which part of the data comes from each kind of cell. If not, what we learn in our study might be wrong. As of now, there is no such approach that…

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    • Rowland et al present THUNDER: an unsupervised deconvolution method for inferring cell type composition from bulk Hi-C data THUNDER can aide the study of cell-type-specificity of the #chromatin interactome #Genomics #biostatistics #Genetics https://t.co/fXsfooZ3JG

  • Mashup Score: 1

    Author summary It is well known that nonrandom selection in one-sample Mendelian Randomization (MR) can result in biased estimates and inflated type I error rates. Actually, two-sample MR analyses are more prone to be affected by nonrandom selection than one-sample MR analyses, because two samples for genome-wide association studies (GWAS) may be selected each under different mechanisms from the…

    Tweet Tweets with this article
    • New research on #MendelianRandomization: Yu et al use simulations to reveal how nonrandom selection in MR analyses can cause bias and type I error They compare how nonrandom selection affects 8 different MR methods #genetics #biostatistics https://t.co/7Hhl8oGKkb

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    Apply for Fellowships - 2 year(s) ago

    Postdoctoral, predoctoral and postbaccalaureate applications are accepted from prospective trainees on a rolling basis. Additionally, some investigators post ‘job ads’ for specific training opportunities. Learn more about eligibility requirements and instructions on how to apply.

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    • Looking for a #postdoc fellowship in #cancer #epi, #biostatistics, or #genetics? See a list of some of the current openings at DCEG: https://t.co/V2LpOoT62r #NCRM22