Publications by authors named "Yukai Xiao"

Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS.

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Article Synopsis
  • Genome-wide polygenic risk scores (GW-PRS) were analyzed for their predictive ability regarding prostate cancer risk, compared to an established multi-ancestry polygenic risk score (PRS).
  • The GW-PRS models utilized data from a large and diverse group of nearly 235,000 participants, including individuals from both African and European ancestries.
  • Results showed that while GW-PRS had varying predictive abilities, the multi-ancestry PRS performed equally well or better in predicting prostate cancer risk for both ancestry groups, indicating GW-PRS may not offer significant improvements in risk prediction.
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Characterizing the tissue-specific binding sites of transcription factors (TFs) is essential to reconstruct gene regulatory networks and predict functions for non-coding genetic variation. DNase-seq footprinting enables the prediction of genome-wide binding sites for hundreds of TFs simultaneously. Despite the public availability of high-quality DNase-seq data from hundreds of samples, a comprehensive, up-to-date resource for the locations of genomic footprints is lacking.

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