Extract Information for Top Variant from Finemapping Results

This function extracts information about the variant with the highest Posterior Inclusion Probability (PIP) from finemapping results, typically used when no Credible Sets (CS) are identified in the analysis.

Usage

extractTopPipInfo(fmRow, sumstats)

Arguments

fmRow

A fineMappingRow carrying the SuSiE fit and variant ids (e.g. from getFineMappingResult).

sumstats

A list or data frame carrying a z element aligned to the fit's variants (sumstats$z).

Value

A data frame with one row containing the following columns:

cs_name

NA (as no CS is identified)

variants_per_cs

NA (as no CS is identified)

top_variant

ID of the variant with the highest PIP

top_variant_index

Index of the top variant in the original data

top_pip

Highest Posterior Inclusion Probability (PIP)

top_z

Z-score of the top variant

p_value

P-value calculated from the top Z-score

cs_corr_max

NA (no between-CS correlation without a CS)

cs_corr_min

NA (no between-CS correlation without a CS)

Details

This function is designed to be used when no Credible Sets are identified in the finemapping results, but information about the most significant variant is still desired. It identifies the variant with the highest PIP and extracts relevant statistical information.

Note

This function is particularly useful for capturing information about potentially important variants that might be included in Credible Sets under different analysis parameters or lower coverage. It maintains a structure similar to the output of `extract_cs_info()` for consistency in downstream analyses.

See also

extractCsInfo for processing when Credible Sets are present.

Examples

vids <- c("chr1:100:A:G", "chr1:200:C:T", "chr1:300:G:A")
fit <- list(pip = c(0.1, 0.7, 0.2))
tl <- data.frame(variant_id = vids, pip = c(0.1, 0.7, 0.2))
fe <- fineMappingRow(variantIds = vids, susieFit = fit, topLoci = tl)
extractTopPipInfo(fe, sumstats = list(z = c(1.0, 3.5, -0.5)))
#> $cs_name
#> [1] NA
#> 
#> $variants_per_cs
#> [1] NA
#> 
#> $top_variant
#> [1] "chr1:200:C:T"
#> 
#> $top_variant_index
#> [1] 2
#> 
#> $top_pip
#> [1] 0.7
#> 
#> $top_z
#> [1] 3.5
#> 
#> $p_value
#> [1] 0.0004652582
#> 
#> $cs_corr_max
#> [1] NA
#> 
#> $cs_corr_min
#> [1] NA
#>