Fetch the names of individuals/genotypes in the core set generated from pcss.core Output

subset.pcss.core returns names of individuals/genotypes in the core collection from pcss.core Output.

Usage

# S3 method for class 'pcss.core'
subset(x, criterion = c("size", "variance", "logistic"), ...)

Arguments

x: An object of class pcss.core.
criterion: The core collection generation criterion. Either "size", "variance", or "logistic". See Details.
...: Unused.

Value

The names of individuals/genotypes in the core collection as a character vector.

Details

Use "size" to return names of individuals/genotypes in the core collection according to the threshold size criterion or use "variance" to return names according to the variability threshold criterion or use "logistic" to return names according to inflection point of rate of progress of cumulative variability retained identified by logistic regression.

Examples


#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Prepare example data
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

if (requireNamespace('EvaluateCore', quietly = TRUE)) {

  suppressPackageStartupMessages(library(EvaluateCore))

  # Get data from EvaluateCore

  data("cassava_EC", package = "EvaluateCore")
  data = cbind(Genotypes = rownames(cassava_EC), cassava_EC)
  quant <- c("NMSR", "TTRN", "TFWSR", "TTRW", "TFWSS", "TTSW", "TTPW",
             "AVPW", "ARSR", "SRDM")
  qual <- c("CUAL", "LNGS", "PTLC", "DSTA", "LFRT", "LBTEF", "CBTR", "NMLB",
            "ANGB", "CUAL9M", "LVC9M", "TNPR9M", "PL9M", "STRP", "STRC",
            "PSTR")
  rownames(data) <- NULL

  # Convert qualitative data columns to factor
  data[, qual] <- lapply(data[, qual], as.factor)

#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# With quantitative data
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

  out1 <- pcss.core(data = data, names = "Genotypes",
                    quantitative = quant,
                    qualitative = NULL, eigen.threshold = NULL, size = 0.2,
                    var.threshold = 0.75)

  # Core sets
  out1$cores.info

  # Fetch genotype names of core set by size criterion
  subset(x = out1, criterion = "size")

  # Fetch genotype names of core set by variance criterion
  subset(x = out1, criterion = "variance")

  # Fetch genotype names of core set by logistic regression criterion
  subset(x = out1, criterion = "logistic")

#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Get core sets with PCSS (qualitative data)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

  out2 <- pcss.core(data = data, names = "Genotypes", quantitative = NULL,
                    qualitative = qual, eigen.threshold = NULL,
                    size = 0.2, var.threshold = 0.75)

  # Core sets
  out2$cores.info

  # Fetch genotype names of core set by size criterion
  subset(x = out2, criterion = "size")

  # Fetch genotype names of core set by variance criterion
  subset(x = out2, criterion = "variance")

  # Fetch genotype names of core set by logistic regression criterion
  subset(x = out2, criterion = "logistic")
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Get core sets with PCSS (quantitative and qualitative data)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

  out3 <- pcss.core(data = data, names = "Genotypes",
                    quantitative = quant,
                    qualitative = qual, eigen.threshold = NULL)

  # Core sets
  out3$cores.info

  # Fetch genotype names of core set by size criterion
  subset(x = out3, criterion = "size")

  # Fetch genotype names of core set by variance criterion
  subset(x = out3, criterion = "variance")

  # Fetch genotype names of core set by logistic regression criterion
  subset(x = out3, criterion = "logistic")

} else {
  message('Package "EvaluateCore" is required to run these examples.')
}
#>   [1] "TMe-3163" "TMe-603"  "TMe-3685" "TMe-3223" "TMe-2967" "TMe-3667"
#>   [7] "TMe-3736" "TMe-3292" "TMe-399"  "TMe-3605" "TMe-3705" "TMe-3800"
#>  [13] "TMe-3475" "TMe-2604" "TMe-3573" "TMe-3628" "TMe-616"  "TMe-1985"
#>  [19] "TMe-3392" "TMe-2943" "TMe-3065" "TMe-3396" "TMe-3319" "TMe-901" 
#>  [25] "TMe-2996" "TMe-2853" "TMe-2050" "TMe-3730" "TMe-3249" "TMe-3095"
#>  [31] "TMe-1769" "TMe-3387" "TMe-3398" "TMe-3701" "TMe-2035" "TMe-1730"
#>  [37] "TMe-390"  "TMe-3466" "TMe-812"  "TMe-761"  "TMe-41"   "TMe-608" 
#>  [43] "TMe-3549" "TMe-3281" "TMe-3323" "TMe-731"  "TMe-2531" "TMe-3266"
#>  [49] "TMe-3116" "TMe-2064" "TMe-3115" "TMe-3282" "TMe-696"  "TMe-756" 
#>  [55] "TMe-1416" "TMe-707"  "TMe-3264" "TMe-1661" "TMe-3389" "TMe-3694"
#>  [61] "TMe-3766" "TMe-13"   "TMe-2033" "TMe-3141" "TMe-3297" "TMe-2983"
#>  [67] "TMe-867"  "TMe-412"  "TMe-1239" "TMe-3140" "TMe-1723" "TMe-2352"
#>  [73] "TMe-2010" "TMe-2196" "TMe-138"  "TMe-1403" "TMe-2993" "TMe-606" 
#>  [79] "TMe-798"  "TMe-1919" "TMe-3252" "TMe-2195" "TMe-1124" "TMe-1294"
#>  [85] "TMe-1232" "TMe-717"  "TMe-3437" "TMe-997"  "TMe-2985" "TMe-1506"
#>  [91] "TMe-1307" "TMe-929"  "TMe-3054" "TMe-373"  "TMe-2308" "TMe-2963"
#>  [97] "TMe-1518" "TMe-1902" "TMe-35"   "TMe-620"  "TMe-2045" "TMe-2913"
#> [103] "TMe-241"  "TMe-2955" "TMe-1809" "TMe-588"  "TMe-3641" "TMe-514" 
#> [109] "TMe-3330" "TMe-1608" "TMe-1283" "TMe-1011" "TMe-2952" "TMe-1428"
#> [115] "TMe-1744" "TMe-3025" "TMe-1564" "TMe-3314" "TMe-1383" "TMe-527" 
#> [121] "TMe-3089" "TMe-432"  "TMe-2510" "TMe-623"  "TMe-3272" "TMe-1261"
#> [127] "TMe-705"  "TMe-3805" "TMe-3040" "TMe-465"  "TMe-3690" "TMe-3034"
#> [133] "TMe-3698" "TMe-728"  "TMe-2441" "TMe-3485" "TMe-2439" "TMe-1339"
#> [139] "TMe-86"   "TMe-3581" "TMe-1158" "TMe-2204" "TMe-427"  "TMe-1633"
#> [145] "TMe-659"  "TMe-751"  "TMe-725"  "TMe-3415" "TMe-861"  "TMe-815" 
#> [151] "TMe-421"  "TMe-2329" "TMe-2916" "TMe-1137" "TMe-2043" "TMe-289" 
#> [157] "TMe-93"   "TMe-3467" "TMe-3200" "TMe-3382" "TMe-3406" "TMe-85"  
#> [163] "TMe-1945" "TMe-27"   "TMe-2968" "TMe-1646" "TMe-1992" "TMe-3592"
#> [169] "TMe-1738" "TMe-1248" "TMe-2897" "TMe-5"    "TMe-267"  "TMe-584" 
#> [175] "TMe-3401" "TMe-3230" "TMe-926"  "TMe-3234" "TMe-2733" "TMe-3222"
#> [181] "TMe-3071" "TMe-3565" "TMe-3046" "TMe-3571" "TMe-832"  "TMe-3007"
#> [187] "TMe-1004" "TMe-2984" "TMe-3596" "TMe-2751" "TMe-1775" "TMe-2843"
#> [193] "TMe-925"  "TMe-3299" "TMe-3329" "TMe-1388" "TMe-1273" "TMe-3721"
#> [199] "TMe-3663" "TMe-1098" "TMe-7"    "TMe-2906" "TMe-2151" "TMe-2940"
#> [205] "TMe-2756" "TMe-745"  "TMe-3572" "TMe-3451" "TMe-742"  "TMe-3130"
#> [211] "TMe-3659" "TMe-3277" "TMe-473"  "TMe-2995" "TMe-2998" "TMe-3493"
#> [217] "TMe-2976" "TMe-863"  "TMe-3087" "TMe-2802" "TMe-3066" "TMe-3302"
#> [223] "TMe-835"  "TMe-1579" "TMe-698"  "TMe-2914" "TMe-1600" "TMe-1580"
#> [229] "TMe-64"   "TMe-842"  "TMe-3631" "TMe-3346" "TMe-3085" "TMe-3255"
#> [235] "TMe-3544" "TMe-853"  "TMe-1817" "TMe-438"  "TMe-3533" "TMe-589" 
#> [241] "TMe-886"  "TMe-2862" "TMe-2119" "TMe-365"  "TMe-3207" "TMe-2811"
#> [247] "TMe-2361" "TMe-44"   "TMe-2355" "TMe-1160" "TMe-3599" "TMe-3531"
#> [253] "TMe-39"   "TMe-635"  "TMe-1218" "TMe-6"    "TMe-1725" "TMe-3498"
#> [259] "TMe-1286" "TMe-3238" "TMe-3118" "TMe-3352" "TMe-1958" "TMe-1398"
#> [265] "TMe-694"  "TMe-1401" "TMe-2981" "TMe-203"  "TMe-773"  "TMe-2901"
#> [271] "TMe-304"  "TMe-3101" "TMe-1444" "TMe-1792" "TMe-3088" "TMe-2040"
#> [277] "TMe-3133" "TMe-1079" "TMe-2912" "TMe-34"   "TMe-3575" "TMe-3608"
#> [283] "TMe-312"  "TMe-787"  "TMe-3440" "TMe-3433" "TMe-700"  "TMe-601" 
#> [289] "TMe-2551" "TMe-2004" "TMe-394"  "TMe-2518" "TMe-946"  "TMe-3707"
#> [295] "TMe-1838" "TMe-3026" "TMe-2374" "TMe-3434" "TMe-2748" "TMe-617" 
#> [301] "TMe-2910" "TMe-3043" "TMe-400"  "TMe-2966" "TMe-1875" "TMe-976" 
#> [307] "TMe-3112" "TMe-360"  "TMe-2860" "TMe-3480" "TMe-3209" "TMe-2957"
#> [313] "TMe-196"  "TMe-3569" "TMe-2158" "TMe-2304" "TMe-363"  "TMe-1472"
#> [319] "TMe-3772" "TMe-43"   "TMe-1461" "TMe-1988" "TMe-3055" "TMe-15"  
#> [325] "TMe-656"  "TMe-434"  "TMe-3324" "TMe-391"  "TMe-1147" "TMe-33"  
#> [331] "TMe-154"  "TMe-3443" "TMe-148"  "TMe-59"   "TMe-3601" "TMe-1198"
#> [337] "TMe-3114" "TMe-3032" "TMe-160"  "TMe-298"  "TMe-1311" "TMe-3185"
#> [343] "TMe-2128" "TMe-3458" "TMe-3781" "TMe-1819" "TMe-830"  "TMe-1814"
#> [349] "TMe-1787" "TMe-3148" "TMe-3359" "TMe-3357" "TMe-340"  "TMe-2814"
#> [355] "TMe-2530" "TMe-47"   "TMe-645"  "TMe-2383" "TMe-2809" "TMe-2973"
#> [361] "TMe-1622" "TMe-1026" "TMe-3639" "TMe-729"  "TMe-25"   "TMe-3633"
#> [367] "TMe-2937" "TMe-2226" "TMe-404"  "TMe-1006" "TMe-1101" "TMe-3445"
#> [373] "TMe-383"  "TMe-4"    "TMe-2997" "TMe-2285" "TMe-1074" "TMe-1272"
#> [379] "TMe-3326" "TMe-477"  "TMe-1250" "TMe-3383" "TMe-1312" "TMe-736" 
#> [385] "TMe-3284" "TMe-280"  "TMe-995"  "TMe-1505" "TMe-3256" "TMe-878" 
#> [391] "TMe-930"  "TMe-2257" "TMe-826"  "TMe-3679" "TMe-1420" "TMe-1521"
#> [397] "TMe-1766" "TMe-1042" "TMe-3020" "TMe-3128" "TMe-279"  "TMe-123" 
#> [403] "TMe-3557" "TMe-1762" "TMe-2217" "TMe-1227" "TMe-1790" "TMe-600" 
#> [409] "TMe-2956" "TMe-754"  "TMe-3481" "TMe-2242"

Fetch the names of individuals/genotypes in the core set generated from `pcss.core` Output

Usage

Arguments

Value

Details

See also

Examples