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When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
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A z score (or standardized value) is measured in units of the standard deviation. It tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
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A z score (or standardized value) is measured in units of the standard deviation. It indicates how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
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z Scores and Area Under the Curve01:17

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z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of...
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The z score is one of the three measures of relative standing. It describes the location of a value in a dataset relative to the mean. z scores are obtained after the standardization of the values in a dataset. The z score for the mean is 0.
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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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Comprehensive benchmarking single and multi ancestry polygenic score methods with the PGS-hub platform.

Xingyu Chen1,2,3,4,5, Fei Wang6,7, Hongqiang Zhao1,2

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Summary
This summary is machine-generated.

This study benchmarks 13 polygenic score (PGS) methods for complex traits. LDpred2 excels in single-ancestry prediction, while LDpred2-multi leads multi-ancestry performance, with a new platform, PGS-hub, simplifying PGS computation.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Polygenic scores (PGS) are crucial for assessing genetic contributions to complex traits.
  • Existing PGS methods lack comprehensive, unified multi-dimensional evaluation.
  • Benchmarking is needed to compare performance, efficiency, and variant impact.

Purpose of the Study:

  • To comprehensively benchmark 13 state-of-the-art polygenic score methods.
  • To evaluate prediction performance, computational efficiency, variant count, and LD reference size impact.
  • To develop an accessible platform for harmonized PGS computation.

Main Methods:

  • Benchmarked 13 PGS methods across 36 traits in UK Biobank (European and African samples).
  • Assessed prediction accuracy, computational speed, variant numbers, and linkage disequilibrium (LD) reference panel sizes.
  • Developed and integrated methods into the user-friendly online platform, PGS-hub.

Main Results:

  • LDpred2 demonstrated superior accuracy and efficiency for single-ancestry PGS.
  • LDpred2-multi outperformed PRS-CSx and X-Wing in multi-ancestry PGS.
  • Increasing LD reference panel size improved PGS performance up to 5,000 samples.

Conclusions:

  • LDpred2 and LDpred2-multi are top-performing methods for single- and multi-ancestry PGS, respectively.
  • PGS-hub provides a scalable, harmonized platform for accessible PGS computation.
  • Methodological choices significantly impact PGS accuracy and efficiency across diverse traits.