Load a hap.py results directory

Read a directory of hap.py output files into an R data structure.

read_happy(happy_prefix, lazy = TRUE, quietly = FALSE)

Arguments

happy_prefix	hap.py output prefix (and path)
lazy	store lesser-used output as unevaluated promises rather than reading everything at once
quietly	inhibit logging messages as files are loaded

Value

A list structure containing hap.py output

Examples

# NOT RUN {
# run hap.py from commandline:
#  hap.py truth.vcf query.vcf -o /output/path/prefix

# load result into R
happy <- read_happy('/output/path/prefix')
# }

# load demo data supplied with package
happy_input <- system.file("extdata", "happy_demo.summary.csv", package = "happyR")
happy_prefix <- sub(".summary.csv", "", happy_input)

hapdata <- read_happy(happy_prefix)
#> Reading summary table
#> Reading extended table
#> Reading precision-recall curve data
print(hapdata)
#>   Hap.py result containing:  summary, extended, pr_curve 
#>    Loaded from:  /Users/mgonzalez/workspace/happyR_v2.0/inst/extdata/happy_demo  (hap.py version: v0.3.9)
#> 
#> # A tibble: 4 x 17
#>   Type  Filter TRUTH.TOTAL TRUTH.TP TRUTH.FN QUERY.TOTAL QUERY.FP QUERY.UNK
#>   <chr> <chr>        <dbl>    <dbl>    <dbl>       <dbl>    <dbl>     <dbl>
#> 1 INDEL ALL           8937     7839     1098       11812      343      3520
#> 2 INDEL PASS          8937     7550     1387        9971      283      1964
#> 3 SNP   ALL          52494    52125      369       90092      582     37348
#> 4 SNP   PASS         52494    46920     5574       48078      143       992
#> # … with 9 more variables: FP.gt <dbl>, METRIC.Recall <dbl>,
#> #   METRIC.Precision <dbl>, METRIC.Frac_NA <dbl>, METRIC.F1_Score <dbl>,
#> #   TRUTH.TOTAL.TiTv_ratio <dbl>, QUERY.TOTAL.TiTv_ratio <dbl>,
#> #   TRUTH.TOTAL.het_hom_ratio <dbl>, QUERY.TOTAL.het_hom_ratio <dbl>