analytic_locFDR_BF_uncor {CPBayes} | R Documentation |

## Analytic calculation of the local FDR & Bayes factor for uncorrelated summary statistics.

### Description

Run the `analytic_locFDR_BF_uncor`

function to analytically compute the local FDR & Bayes factor (BF)
that quantifies the evidence of aggregate-level pleiotropic association for uncorrelated summary statistics.
Here a fixed value of slab variance is considred instead of a range of it in `cpbayes_uncor`

.

### Usage

```
analytic_locFDR_BF_uncor(BetaHat, SE, SpikeVar = 1e-04, SlabVar = 0.8)
```

### Arguments

`BetaHat` |
A numeric vector of length K where K is the number of phenotypes. It contains the beta-hat values across studies/traits. No default. |

`SE` |
A numeric vector with the same dimension as BetaHat providing the standard errors corresponding to BetaHat. Every element of SE must be positive. No default. |

`SpikeVar` |
Variance of spike (normal distribution with small variance) representing the null effect distribution. Default is 10^(-4). |

`SlabVar` |
Variance of slab normal distribution representing the non-null effect distribution. Default is 0.8. |

### Value

The output produced by the function is a list which consists of the local FDR and log10(Bayes factor).

`locFDR` |
It provides the analytically computed local false discovery rate (posterior probability of null association) under CPBayes model (a Bayesian analog of the p-value) which is a measure of the evidence of the aggregate-level pleiotropic association. Bayes factor is adjusted for prior odds, but locFDR is solely a function of the posterior odds. |

`log10_BF` |
It provides the analytically computed log10(Bayes factor) produced by CPBayes that measures the evidence of the overall pleiotropic association. |

### References

Majumdar A, Haldar T, Bhattacharya S, Witte JS (2018) An efficient Bayesian meta analysis approach for studying cross-phenotype genetic associations. PLoS Genet 14(2): e1007139.

### See Also

`cpbayes_uncor`

, `analytic_locFDR_BF_cor`

, `cpbayes_cor`

, `estimate_corln`

, `post_summaries`

, `forest_cpbayes`

### Examples

```
data(ExampleDataUncor)
BetaHat <- ExampleDataUncor$BetaHat
BetaHat
SE <- ExampleDataUncor$SE
SE
result <- analytic_locFDR_BF_uncor(BetaHat, SE)
str(result)
```

*CPBayes*version 1.1.0 Index]