PRSice

About the tool

  • Polygenic risk score (PRS) software for calculating, applying, evaluating, and plotting the results of PRS analyses

  • All approaches to PRS calculation involve parameter optimization and are therefore overfitted

  • The scores are normalized

Calculation of PRS

Assuming S is the summary statistic for the effective allele and G is the number of the effective alleles observed, then the main difference between the models is how the genotypes are coded,

For additive model (add)

G=GG =G

For dominant model (with respect to the effective allele of the base file)

G={0if G=01OtherwiseG=\begin{cases} \text{0} & \text{if $G=0$}\\ \text{1} & \text{Otherwise} \end{cases}

For recessive model (with respect to the effective allele of the base file)

G={1if G=20OtherwiseG=\begin{cases} \text{1} & \text{if $G=2$}\\ \text{0} & \text{Otherwise} \end{cases}

For heterozygous model

G={1if G=10OtherwiseG=\begin{cases} \text{1} & \text{if $G=1$}\\ \text{0} & \text{Otherwise} \end{cases}

The average score (--score avg)is calculated as

PRSj=∑iSi−GijMijPRS_j = \sum_i{\frac{S_i - G_{ij}}{M_{ij}}}

To account for overfitting that occurs during parameter optimization, empirical P-value is calculated as

Empirical−P=∑n=1NI(Pnull−P0)+1N+1Empirical-P = \frac{\sum_{n=1}^\N I(P_{null}-P_0)+1}{N+1}

Here

  • I() = Indicator function

  • P0 = P-value of association of best P-value threshold

  • Pnull = P-value of association of the best P-value threshold under the null

  • N = 10000

  • Mj = The number of alleles included in the PRS of the j-th individual

Evaluation metrics

  • R2 - Observed phenotypic variance; remains unadjusted

    • Nagelkerke's R2 - Pseudo-R2 statistic for logistic regression; automatically calculated by PRSice

    • Cox and Snell R2 - Used for a quantitative trait

  • AUC - A measure of how well the genomic profile predicts a binary phenotype

    • Independent of the proportion of cases and controls in the sample cohort

    • Ranges from 0.5 to 1

  • Odds ratio - It shows the odds of the occurrence of a case in each group

    • Distribution is usually cut into deciles (unless otherwise defined) where each decile includes both cases and controls

    • The odds ratio for each decile is compared to a reference decile (PRSice selects the middle one)

Input

  • Base dataset

  • Target dataset

  • Target dataset type

  • Phenotype file

  • Covariates file (Including age and sex as covariates)

  • Filters (if any)

Flags that can be used to toggle with the output

  • To filter SNPs based on base maximum allele frequency: --base-info <Info Name>:<Info Threshold> and --base-maf <MAF Name>:<MAF Threshold>

  • To filter SNPs based on founder samples (target dataset) maximum allele frequency: --maf

  • To use a BGEN type target dataset: --type bgen

    • In this case, the input target dataset is given by --target <bgen prefix>,<sample file>

  • A covariates file can be added using --cov

    • Non-numerical columns can be specified using --cov-factor

  • A phenotype file containing 0 or 1 for all individuals in the cohort has to be provided using --pheno

  • FID can be ignored using --ignore-fid

  • Clumping can be disabled using --no-clump

Output

The tool generates multiple output files including:

  • [Name].summary - Contains the following fields:

    1. Phenotype - Name of phenotype

    2. Set - Name of gene set

    3. Threshold - Best P-value threshold

    4. PRS.R2 - Variance explained by the PRS. If prevalence is provided, this will be adjusted for ascertainment

    5. Full.R2 - Variance explained by the full model (including the covariates). If prevalence is provided, this will be adjusted for ascertainment

    6. Null.R2 - Variance explained by the covariates. If prevalence is provided, this will be adjusted for ascertainment

    7. Prevalence - Population prevalence as indicated by the user. "-" if not provided

    8. Coefficient - Regression coefficient of the model. Can provide insight into the direction of the effect.

    9. P - P value of the model fit

    10. Num_SNP - Number of SNPs included in the model

    11. Empirical-P - Only provided if a permutation is performed. This is the empirical p-value and should account for multiple testing and over-fitting

  • [Name].best - Contains the PRS for each individual at the best-fit PRS. It looks as follows:

    1. FID

    2. IID

    3. In_Regression

    4. PRS at best threshold of first set

    5. PRS at best threshold of second set, ...

  • [Name].prsice - Contains the PRS model fit across thresholds

  • [Name].log - Contains all the commands used for the analysis and information regarding filtering, field selected, etc.

  • [Name].all.score if --all-score is specified - Contains the PRS for each individual at all thresholds and all sets. It looks as follows:

    1. FID

    2. IID

    3. PRS for first set at first threshold

    4. PRS for first set at second threshold, ...

  • [Name]_BARPLOT_[date].png if --bar-levels is specified

  • [Name]_HIGHRES_PLOT_[date].png if --fastscore is not specified

  • [Name]_STRATA_PLOT_[date].png if --quantile [number of quantile] is specified

    • Usually, --quantile 100 is specified with --quant-break

  • [Name]_STRATA_[date].txt- Provides data used for plotting the above plot

Source

https://choishingwan.github.io/PRSice/

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