Enzymatic polymorphism in Leuciscus cephalus

This data set contains a list of three components: spatial map, allellic profiles and sample sizes.

Usage

data(chevaine)

Format

This data set is a list of three components:

tab

a data frame with 27 populations and 9 allelic frequencies (4 locus)

coo

a list containing all the elements to build a spatial map

eff

a numeric containing the numbers of fish samples per station

References

Guinand B., Bouvet Y. and Brohon B. (1996) Spatial aspects of genetic differentiation of the European chub in the Rhone River basin. Journal of Fish Biology, 49, 714--726.

See a data description at http://pbil.univ-lyon1.fr/R/pdf/pps054.pdf (in French).

Examples

data(chevaine)
names(chevaine)
#> [1] "tab" "coo" "eff"
str(chevaine)
#> List of 3
#>  $ tab:'data.frame':	27 obs. of  9 variables:
#>   ..$ PGM-2*.090 : num [1:27] 0.017 0.083 0.107 0.067 0.103 0.179 0.216 0.25 0.175 0.282 ...
#>   ..$ PGM-2*.098 : num [1:27] 0.15 0.216 0.179 0.2 0.19 0.125 0.2 0.115 0.05 0 ...
#>   ..$ PGM-2*.100 : num [1:27] 0.833 0.701 0.714 0.733 0.707 0.696 0.584 0.635 0.775 0.718 ...
#>   ..$ IDHP-1*.100: num [1:27] 1 1 0.982 1 1 0.981 0.983 1 0.975 0.976 ...
#>   ..$ IDHP-1*.145: num [1:27] 0 0 0.018 0 0 0.019 0.017 0 0.025 0.024 ...
#>   ..$ EST-2*.098 : num [1:27] 0.3 0.3 0.25 0.467 0.362 0.25 0.217 0.308 0.25 0.31 ...
#>   ..$ EST-2*.100 : num [1:27] 0.7 0.7 0.75 0.533 0.638 0.75 0.783 0.692 0.75 0.69 ...
#>   ..$ G3PDH*.085 : num [1:27] 0.217 0.167 0.179 0.217 0.103 0.154 0.1 0.038 0.05 0.119 ...
#>   ..$ G3PDH*.100 : num [1:27] 0.783 0.833 0.821 0.783 0.897 0.846 0.9 0.962 0.95 0.881 ...
#>  $ coo:List of 4
#>   ..$ lac:List of 2
#>   .. ..$ geneve :List of 2
#>   .. .. ..$ x: num [1:16] 248 252 269 299 330 ...
#>   .. .. ..$ y: num [1:16] 554 585 609 625 621 ...
#>   .. ..$ bourget:List of 2
#>   .. .. ..$ x: num [1:10] 210 229 243 252 250 ...
#>   .. .. ..$ y: num [1:10] 476 481 461 435 426 ...
#>   ..$ poi:'data.frame':	10 obs. of  2 variables:
#>   .. ..$ x: num [1:10] 26.4 141 150 58.3 146.4 ...
#>   .. ..$ y: num [1:10] 565 674 566 501 482 ...
#>   ..$ riv:List of 7
#>   .. ..$ seille   :'data.frame':	6 obs. of  2 variables:
#>   .. .. ..$ x: num [1:6] 73.1 109.2 116.6 142.1 154.8 ...
#>   .. .. ..$ y: num [1:6] 594 628 649 658 658 ...
#>   .. ..$ reyssouze:'data.frame':	6 obs. of  2 variables:
#>   .. .. ..$ x: num [1:6] 68.9 84.8 96.5 112.4 114.5 ...
#>   .. .. ..$ y: num [1:6] 572 579 571 542 530 ...
#>   .. ..$ saone    :'data.frame':	16 obs. of  2 variables:
#>   .. .. ..$ x: num [1:16] 95.4 85.9 82.7 88 76.3 ...
#>   .. .. ..$ y: num [1:16] 723 716 709 698 680 ...
#>   .. ..$ rhone    :'data.frame':	31 obs. of  2 variables:
#>   .. .. ..$ x: num [1:31] 248 229 220 203 207 ...
#>   .. .. ..$ y: num [1:31] 553 541 525 511 496 ...
#>   .. ..$ grosne   :'data.frame':	6 obs. of  2 variables:
#>   .. .. ..$ x: num [1:6] 64.6 46.6 26.4 34.9 24.3 ...
#>   .. .. ..$ y: num [1:6] 633 625 604 583 558 ...
#>   .. ..$ shunt    :'data.frame':	3 obs. of  2 variables:
#>   .. .. ..$ x: num [1:3] 93.3 88 93.3
#>   .. .. ..$ y: num [1:3] 163 131 112
#>   .. ..$ ardeche  :'data.frame':	6 obs. of  2 variables:
#>   .. .. ..$ x: num [1:6] 102.8 99.7 93.3 75.3 50.8 ...
#>   .. .. ..$ y: num [1:6] 83 101 115 119 133 ...
#>   ..$ sta:'data.frame':	27 obs. of  2 variables:
#>   .. ..$ x: num [1:27] 23.4 33.2 26.2 36 42.9 ...
#>   .. ..$ y: num [1:27] 541 582 605 620 628 ...
#>  $ eff: num [1:27] 30 30 28 30 29 26 30 26 20 21 ...