resvigncont: Results contained in vignette Quick Manual
In RClone: Partially Clonal Populations Analysis
Description
Usage
Format
Author(s)
Examples
Description
This file contains data to fast generate the vignette: RClone_quickmanual.
Usage
1
data("resvigncont")
Format
The format is:
List of 14
$ resee :List of 2
..$ results :'data.frame': 1 obs. of 3 variables:
.. ..$ Ee : num 0.0779
.. ..$ pval_Ee : num 0.434
.. ..$ nbrepeat: num 1000
..$ simulations: num [1:1000] 0.0316 -0.1692 -0.1411 -0.1172 -0.1289 ...
$ resgen :'data.frame': 1 obs. of 24 variables:
..$ N :List of 1
.. ..$ : int 40
..$ Lineage :List of 1
.. ..$ : chr "MLG"
..$ nb_L :List of 1
.. ..$ : int 28
..$ nb_all :List of 1
.. ..$ : num 4.14
..$ SE :List of 1
.. ..$ : num 0.769
..$ Fis :List of 1
.. ..$ : num 0.0508
..$ pval_2sides :List of 1
.. ..$ : logi NA
..$ Fis_WR :List of 1
.. ..$ : num 0.0257
..$ pval_2sides :List of 1
.. ..$ : logi NA
..$ R :List of 1
.. ..$ : num 0.692
..$ Pareto_index:List of 1
.. ..$ : num 1.18
..$ Sp_Loiselle :List of 1
.. ..$ : num 0.00123
..$ pval_2sides :List of 1
.. ..$ : num NA
..$ Sp_L_WR :List of 1
.. ..$ : num 0.00124
..$ pval_2sides :List of 1
.. ..$ : num NA
..$ Sp_Ritland :List of 1
.. ..$ : num 0.000769
..$ pval_2sides :List of 1
.. ..$ : num NA
..$ Sp_R_WR :List of 1
.. ..$ : num 0.000803
..$ pval_2sides :List of 1
.. ..$ : num NA
..$ H” :List of 1
.. ..$ : num 3.15
..$ J' :List of 1
.. ..$ : num 0.945
..$ D :List of 1
.. ..$ : num 0.971
..$ V :List of 1
.. ..$ : num 0.792
..$ Hill :List of 1
.. ..$ : num 33.9
$ resagg :List of 2
..$ results : num [1, 1:3] 0.227 0 1000
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : NULL
.. .. ..$ : chr [1:3] "Ac" "pval" "nbrepeat"
..$ simulation: num [1:1000] 0.034 0.034 0.034 0.034 0.034 ...
$ rescs :List of 2
..$ : num 11.7
..$ clonal_sub_tab:List of 60
.. ..$ : int 97
.. ..$ : int 157
.. ..$ : int 119
.. ..$ : int 110
.. ..$ : int 121
.. ..$ : int 64
.. ..$ : int 34
.. ..$ : int 29
.. ..$ : int 31
.. ..$ : int 18
.. ..$ : num 0.5
.. ..$ : num 7.62
.. ..$ : num 15.2
.. ..$ : num 22.9
.. ..$ : num 30.5
.. ..$ : num 38
.. ..$ : num 46.1
.. ..$ : num 53.5
.. ..$ : num 61
.. ..$ : num 68.5
.. ..$ : num 7.52
.. ..$ : num 15.2
.. ..$ : num 22.8
.. ..$ : num 30.4
.. ..$ : num 38
.. ..$ : num 45.6
.. ..$ : num 53.1
.. ..$ : num 60.7
.. ..$ : num 68
.. ..$ : num 76
.. ..$ : num 4.68
.. ..$ : num 11.1
.. ..$ : num 18.8
.. ..$ : num 26.6
.. ..$ : num 34.2
.. ..$ : num 41.5
.. ..$ : num 49.6
.. ..$ : num 57.1
.. ..$ : num 64.7
.. ..$ : num 70.9
.. ..$ : num 0.165
.. ..$ : num 0.0446
.. ..$ : num 0
.. ..$ : num 0
.. ..$ : num 0
.. ..$ : num 0
.. ..$ : num 0
.. ..$ : num 0
.. ..$ : num 0
.. ..$ : num 0
.. ..$ : num -0.783
.. ..$ : num -1.35
.. ..$ : num -Inf
.. ..$ : num -Inf
.. ..$ : num -Inf
.. ..$ : num -Inf
.. ..$ : num -Inf
.. ..$ : num -Inf
.. ..$ : num -Inf
.. ..$ : num -Inf
.. ..- attr(*, "dim")= int [1:2] 10 6
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : chr [1:10] "1" "2" "3" "4" ...
.. .. ..$ : chr [1:6] "nb_pairs" "dist_min" "dist_max" "dist_mean" ...
$ resauto :List of 7
..$ Main_results :'data.frame': 10 obs. of 7 variables:
.. ..$ dist_min : num [1:10] 0.5 7.62 15.24 22.94 30.5 ...
.. ..$ dist_max : num [1:10] 7.52 15.21 22.8 30.41 38 ...
.. ..$ dist_mean : num [1:10] 4.68 11.15 18.81 26.65 34.21 ...
.. ..$ ln(dist_mean): num [1:10] 1.54 2.41 2.93 3.28 3.53 ...
.. ..$ nb_pairs : num [1:10] 97 157 119 110 121 64 34 29 31 18
.. ..$ mean_Ritland : num [1:10] 0.0892 0.0296 -0.0224 -0.0532 -0.0736 ...
.. ..$ pval_kin : num [1:10] 0 0 0.39 0 0 0 0.144 0.154 0.8 0.106
..$ Slope_and_Sp_index :'data.frame': 10 obs. of 4 variables:
.. ..$ b : num [1:10] -7.01e-04 1.96e-06 2.75e-04 -6.25e-04 4.65e-04 ...
.. ..$ b_log : num [1:10] -3.58e-02 3.47e-05 6.30e-03 -1.42e-02 1.01e-02 ...
.. ..$ Sp : num [1:10] 7.69e-04 -7.63e-07 2.73e-04 -4.58e-04 6.18e-04 ...
.. ..$ Sp_log: num [1:10] 3.93e-02 9.75e-06 6.24e-03 -9.86e-03 1.41e-02 ...
..$ Slope_resample :'data.frame': 1000 obs. of 4 variables:
.. ..$ b : num [1:1000] 8.95e-05 9.99e-05 1.64e-04 1.23e-04 1.53e-04 ...
.. ..$ b_log : num [1:1000] 0.004679 0.000447 0.000649 0.004408 0.003708 ...
.. ..$ Sp : num [1:1000] -8.65e-05 -9.98e-05 -1.65e-04 -1.19e-04 -1.50e-04 ...
.. ..$ Sp_log: num [1:1000] -0.004524 -0.000446 -0.000653 -0.004292 -0.003647 ...
..$ Kinship_resample : num [1:1000, 1:10] -0.03434 -0.00168 0.00721 -0.02697 -0.01677 ...
.. ..- attr(*, "dimnames")=List of 2
.. .. ..$ : NULL
.. .. ..$ : chr [1:10] "class_1" "class_2" "class_3" "class_4" ...
..$ Matrix_kinship_results:Class 'dist' atomic [1:780] -0.16518 -0.00174 -0.00174 -0.00174 -0.00174 ...
.. .. ..- attr(*, "Labels")= chr [1:40] "1" "2" "3" "4" ...
.. .. ..- attr(*, "Size")= int 40
.. .. ..- attr(*, "call")= language as.dist.default(m = mat_auto)
.. .. ..- attr(*, "Diag")= logi FALSE
.. .. ..- attr(*, "Upper")= logi FALSE
..$ Class_kinship_results :List of 10
.. ..$ : num [1:97] -0.16518 -0.00174 -0.00174 -0.00174 -0.03193 ...
.. ..$ : num [1:157] -0.00174 -0.00174 -0.02292 -0.08243 -0.15206 ...
.. ..$ : num [1:119] -0.0455 -0.0921 -0.0455 -0.0455 0.036 ...
.. ..$ : num [1:110] -0.0455 -0.1553 -0.1433 -0.047 -0.1513 ...
.. ..$ : num [1:121] -0.143 -0.143 -0.114 0.301 -0.181 ...
.. ..$ : num [1:64] -0.0918 -0.1236 -0.1236 -0.1024 -0.1236 ...
.. ..$ : num [1:34] -0.08461 0.10111 0.1034 -0.00678 0.05459 ...
.. ..$ : num [1:29] -0.00693 -0.00693 -0.00693 -0.00693 -0.00693 ...
.. ..$ : num [1:31] 0.3935 -0.0646 -0.1289 -0.0656 -0.0825 ...
.. ..$ : num [1:18] 0.00503 0.26968 0.00414 -0.02171 -0.04514 ...
..$ Class_distance_results:List of 10
.. ..$ : num [1:97] 2 5.7 7.11 5.15 4.74 ...
.. ..$ : num [1:157] 8.06 8.28 9.96 8.08 13.73 ...
.. ..$ : num [1:119] 15.4 15.9 17.4 18.7 19.6 ...
.. ..$ : num [1:110] 24.5 26.1 26.9 24.1 24.9 ...
.. ..$ : num [1:121] 31.3 31.5 34.5 31.8 32.5 ...
.. ..$ : num [1:64] 38.5 38.1 38.5 39.5 39.5 ...
.. ..$ : num [1:34] 47.4 47.6 52 50 48.9 ...
.. ..$ : num [1:29] 60.6 60.7 59.8 58.7 56.5 ...
.. ..$ : num [1:31] 63.4 66 61.4 64.1 68 ...
.. ..$ : num [1:18] 70 70.8 70.5 73.1 76 ...
$ rescl :'data.frame': 1 obs. of 7 variables:
..$ G : num 28
..$ R : num 0.692
..$ H” : num 3.15
..$ J' : num 0.945
..$ D : num 0.971
..$ V : num 0.792
..$ Hill: num 33.9
$ ressimWS:List of 1
..$ distance_matrix:Class 'dist' atomic [1:499500] 59 126 71 59 63 120 119 164 105 80 ...
.. .. ..- attr(*, "Labels")= chr [1:1000] "1" "2" "3" "4" ...
.. .. ..- attr(*, "Size")= int 1000
.. .. ..- attr(*, "call")= language as.dist.default(m = dist_all)
.. .. ..- attr(*, "Diag")= logi FALSE
.. .. ..- attr(*, "Upper")= logi FALSE
$ ressim :List of 1
..$ distance_matrix:Class 'dist' atomic [1:499500] 143 98 138 93 106 98 106 113 109 102 ...
.. .. ..- attr(*, "Labels")= chr [1:1000] "1" "2" "3" "4" ...
.. .. ..- attr(*, "Size")= int 1000
.. .. ..- attr(*, "call")= language as.dist.default(m = dist_all)
.. .. ..- attr(*, "Diag")= logi FALSE
.. .. ..- attr(*, "Upper")= logi FALSE
$ respop :List of 1
..$ distance_matrix:Class 'dist' atomic [1:153] 173 178 2 173 178 1 1 84 133 100 ...
.. .. ..- attr(*, "Labels")= chr [1:18] "1" "2" "3" "4" ...
.. .. ..- attr(*, "Size")= int 18
.. .. ..- attr(*, "call")= language as.dist.default(m = dist_all)
.. .. ..- attr(*, "Diag")= logi FALSE
.. .. ..- attr(*, "Upper")= logi FALSE
$ res_PS4 :'data.frame': 6 obs. of 4 variables:
..$ pgenFis: num [1:6] 1.05e-05 1.09e-10 4.39e-05 4.39e-05 4.39e-05 ...
..$ genet : chr [1:6] "" "" "" "3" ...
..$ psexFis: chr [1:6] "" "" "" "0.00175402908240928" ...
..$ pvalue : chr [1:6] "" "" "" "0.258064516129032" ...
$ res_PS3 :List of 2
..$ :'data.frame': 40 obs. of 3 variables:
.. ..$ genet : chr [1:40] "" "" "" "3" ...
.. ..$ psexFis: chr [1:40] "" "" "" "0.00175402908240928" ...
.. ..$ pvalue : chr [1:40] "" "" "" "0.258064516129032" ...
..$ : num [1:31] 0.004048 0.00316 0.009211 0.000587 0.007884 ...
$ res_PS2 :'data.frame': 6 obs. of 4 variables:
..$ pgen : num [1:6] 2.19e-06 2.04e-10 4.77e-05 4.77e-05 4.77e-05 ...
..$ genet : chr [1:6] "" "" "" "3" ...
..$ psex : chr [1:6] "" "" "" "0.00190284159898287" ...
..$ pvalue: chr [1:6] "" "" "" "0.392857142857143" ...
$ res_PS1 :List of 2
..$ :'data.frame': 40 obs. of 3 variables:
.. ..$ genet : chr [1:40] "" "" "" "3" ...
.. ..$ psex : chr [1:40] "" "" "" "0.00190284159898287" ...
.. ..$ pvalue: chr [1:40] "" "" "" "0.392857142857143" ...
..$ : num [1:28] 0.00268 0.00135 0.0034 0.00154 0.0043 ...
$ res_SU1 :List of 5
..$ res_MLG :'data.frame': 7 obs. of 5 variables:
.. ..$ nb_loci : int [1:7] 1 2 3 4 5 6 7
.. ..$ min : int [1:7] 3 7 11 19 22 25 28
.. ..$ max : int [1:7] 13 21 26 27 28 28 28
.. ..$ mean_MLG: num [1:7] 6.26 14.27 20.14 23.57 25.44 ...
.. ..$ SE : num [1:7] 0.1047 0.1362 0.0966 0.0618 0.046 ...
..$ res_alleles:'data.frame': 7 obs. of 7 variables:
.. ..$ nb_loci : int [1:7] 1 2 3 4 5 6 7
.. ..$ min : int [1:7] 2 5 8 11 15 22 29
.. ..$ max : int [1:7] 7 14 18 21 24 27 29
.. ..$ mean_all: num [1:7] 4.09 8.33 12.42 16.53 20.7 ...
.. ..$ SE : num [1:7] NA 132.3 88.3 70.2 60.7 ...
.. ..$ He : num [1:7] 0.549 0.549 0.55 0.55 0.55 ...
.. ..$ SE : num [1:7] NA 1.217 0.803 0.646 0.552 ...
..$ raw_He :'data.frame': 1000 obs. of 7 variables:
.. ..$ 1_locus: num [1:1000] 0.531 0.38 0.488 0.488 0.657 ...
.. ..$ 2_loci : num [1:1000] 0.621 0.771 0.459 0.519 0.509 ...
.. ..$ 3_loci : num [1:1000] 0.483 0.691 0.677 0.558 0.658 ...
.. ..$ 4_loci : num [1:1000] 0.517 0.616 0.613 0.559 0.616 ...
.. ..$ 5_loci : num [1:1000] 0.538 0.523 0.588 0.517 0.538 ...
.. ..$ 6_loci : num [1:1000] 0.534 0.534 0.512 0.6 0.534 ...
.. ..$ 7_loci : num [1:1000] 0.551 0.551 0.551 0.551 0.551 ...
..$ raw_MLG :'data.frame': 1000 obs. of 7 variables:
.. ..$ 1_locus: int [1:1000] 4 3 6 6 6 6 9 6 6 3 ...
.. ..$ 2_loci : int [1:1000] 19 20 12 12 13 12 21 14 17 19 ...
.. ..$ 3_loci : int [1:1000] 18 21 23 24 24 19 18 20 18 20 ...
.. ..$ 4_loci : int [1:1000] 24 25 21 26 25 23 26 20 21 26 ...
.. ..$ 5_loci : int [1:1000] 26 27 24 26 26 25 24 27 26 25 ...
.. ..$ 6_loci : int [1:1000] 25 25 26 27 25 27 28 28 28 26 ...
.. ..$ 7_loci : int [1:1000] 28 28 28 28 28 28 28 28 28 28 ...
..$ raw_all :'data.frame': 1000 obs. of 7 variables:
.. ..$ 1_locus: int [1:1000] 4 2 3 3 3 3 7 3 3 2 ...
.. ..$ 2_loci : int [1:1000] 10 14 6 5 7 5 10 6 9 10 ...
.. ..$ 3_loci : int [1:1000] 10 18 17 13 14 8 8 9 9 14 ...
.. ..$ 4_loci : int [1:1000] 17 17 20 17 17 12 17 16 19 17 ...
.. ..$ 5_loci : int [1:1000] 20 19 23 19 20 24 23 24 19 18 ...
.. ..$ 6_loci : int [1:1000] 26 26 22 26 26 26 26 27 27 22 ...
.. ..$ 7_loci : int [1:1000] 29 29 29 29 29 29 29 29 29 29 ...
Author(s)
Creator/Author: Diane Bailleul <diane.bailleul.pro@gmail.com>
Author: Sophie Arnaud-Haond <sophie.arnaud@ifremer.fr>
Contributor: Solenn Stoeckel
The R implementation of RClone was written by Diane Bailleul.
The design was inspired by GenClone program described in Arnaud-Haond & Belkhir (2007).
Examples
1
2
#v1 <- vignette("RClone_quickmanual")
#print(v1)
RClone documentation built on May 15, 2021, 5:07 p.m.
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Description Usage Format Author(s) Examples
Description
This file contains data to fast generate the vignette: RClone_quickmanual.
Usage
1 | data("resvigncont")
|
Format
The format is: List of 14 $ resee :List of 2 ..$ results :'data.frame': 1 obs. of 3 variables: .. ..$ Ee : num 0.0779 .. ..$ pval_Ee : num 0.434 .. ..$ nbrepeat: num 1000 ..$ simulations: num [1:1000] 0.0316 -0.1692 -0.1411 -0.1172 -0.1289 ... $ resgen :'data.frame': 1 obs. of 24 variables: ..$ N :List of 1 .. ..$ : int 40 ..$ Lineage :List of 1 .. ..$ : chr "MLG" ..$ nb_L :List of 1 .. ..$ : int 28 ..$ nb_all :List of 1 .. ..$ : num 4.14 ..$ SE :List of 1 .. ..$ : num 0.769 ..$ Fis :List of 1 .. ..$ : num 0.0508 ..$ pval_2sides :List of 1 .. ..$ : logi NA ..$ Fis_WR :List of 1 .. ..$ : num 0.0257 ..$ pval_2sides :List of 1 .. ..$ : logi NA ..$ R :List of 1 .. ..$ : num 0.692 ..$ Pareto_index:List of 1 .. ..$ : num 1.18 ..$ Sp_Loiselle :List of 1 .. ..$ : num 0.00123 ..$ pval_2sides :List of 1 .. ..$ : num NA ..$ Sp_L_WR :List of 1 .. ..$ : num 0.00124 ..$ pval_2sides :List of 1 .. ..$ : num NA ..$ Sp_Ritland :List of 1 .. ..$ : num 0.000769 ..$ pval_2sides :List of 1 .. ..$ : num NA ..$ Sp_R_WR :List of 1 .. ..$ : num 0.000803 ..$ pval_2sides :List of 1 .. ..$ : num NA ..$ H” :List of 1 .. ..$ : num 3.15 ..$ J' :List of 1 .. ..$ : num 0.945 ..$ D :List of 1 .. ..$ : num 0.971 ..$ V :List of 1 .. ..$ : num 0.792 ..$ Hill :List of 1 .. ..$ : num 33.9 $ resagg :List of 2 ..$ results : num [1, 1:3] 0.227 0 1000 .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : NULL .. .. ..$ : chr [1:3] "Ac" "pval" "nbrepeat" ..$ simulation: num [1:1000] 0.034 0.034 0.034 0.034 0.034 ... $ rescs :List of 2 ..$ : num 11.7 ..$ clonal_sub_tab:List of 60 .. ..$ : int 97 .. ..$ : int 157 .. ..$ : int 119 .. ..$ : int 110 .. ..$ : int 121 .. ..$ : int 64 .. ..$ : int 34 .. ..$ : int 29 .. ..$ : int 31 .. ..$ : int 18 .. ..$ : num 0.5 .. ..$ : num 7.62 .. ..$ : num 15.2 .. ..$ : num 22.9 .. ..$ : num 30.5 .. ..$ : num 38 .. ..$ : num 46.1 .. ..$ : num 53.5 .. ..$ : num 61 .. ..$ : num 68.5 .. ..$ : num 7.52 .. ..$ : num 15.2 .. ..$ : num 22.8 .. ..$ : num 30.4 .. ..$ : num 38 .. ..$ : num 45.6 .. ..$ : num 53.1 .. ..$ : num 60.7 .. ..$ : num 68 .. ..$ : num 76 .. ..$ : num 4.68 .. ..$ : num 11.1 .. ..$ : num 18.8 .. ..$ : num 26.6 .. ..$ : num 34.2 .. ..$ : num 41.5 .. ..$ : num 49.6 .. ..$ : num 57.1 .. ..$ : num 64.7 .. ..$ : num 70.9 .. ..$ : num 0.165 .. ..$ : num 0.0446 .. ..$ : num 0 .. ..$ : num 0 .. ..$ : num 0 .. ..$ : num 0 .. ..$ : num 0 .. ..$ : num 0 .. ..$ : num 0 .. ..$ : num 0 .. ..$ : num -0.783 .. ..$ : num -1.35 .. ..$ : num -Inf .. ..$ : num -Inf .. ..$ : num -Inf .. ..$ : num -Inf .. ..$ : num -Inf .. ..$ : num -Inf .. ..$ : num -Inf .. ..$ : num -Inf .. ..- attr(*, "dim")= int [1:2] 10 6 .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : chr [1:10] "1" "2" "3" "4" ... .. .. ..$ : chr [1:6] "nb_pairs" "dist_min" "dist_max" "dist_mean" ... $ resauto :List of 7 ..$ Main_results :'data.frame': 10 obs. of 7 variables: .. ..$ dist_min : num [1:10] 0.5 7.62 15.24 22.94 30.5 ... .. ..$ dist_max : num [1:10] 7.52 15.21 22.8 30.41 38 ... .. ..$ dist_mean : num [1:10] 4.68 11.15 18.81 26.65 34.21 ... .. ..$ ln(dist_mean): num [1:10] 1.54 2.41 2.93 3.28 3.53 ... .. ..$ nb_pairs : num [1:10] 97 157 119 110 121 64 34 29 31 18 .. ..$ mean_Ritland : num [1:10] 0.0892 0.0296 -0.0224 -0.0532 -0.0736 ... .. ..$ pval_kin : num [1:10] 0 0 0.39 0 0 0 0.144 0.154 0.8 0.106 ..$ Slope_and_Sp_index :'data.frame': 10 obs. of 4 variables: .. ..$ b : num [1:10] -7.01e-04 1.96e-06 2.75e-04 -6.25e-04 4.65e-04 ... .. ..$ b_log : num [1:10] -3.58e-02 3.47e-05 6.30e-03 -1.42e-02 1.01e-02 ... .. ..$ Sp : num [1:10] 7.69e-04 -7.63e-07 2.73e-04 -4.58e-04 6.18e-04 ... .. ..$ Sp_log: num [1:10] 3.93e-02 9.75e-06 6.24e-03 -9.86e-03 1.41e-02 ... ..$ Slope_resample :'data.frame': 1000 obs. of 4 variables: .. ..$ b : num [1:1000] 8.95e-05 9.99e-05 1.64e-04 1.23e-04 1.53e-04 ... .. ..$ b_log : num [1:1000] 0.004679 0.000447 0.000649 0.004408 0.003708 ... .. ..$ Sp : num [1:1000] -8.65e-05 -9.98e-05 -1.65e-04 -1.19e-04 -1.50e-04 ... .. ..$ Sp_log: num [1:1000] -0.004524 -0.000446 -0.000653 -0.004292 -0.003647 ... ..$ Kinship_resample : num [1:1000, 1:10] -0.03434 -0.00168 0.00721 -0.02697 -0.01677 ... .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : NULL .. .. ..$ : chr [1:10] "class_1" "class_2" "class_3" "class_4" ... ..$ Matrix_kinship_results:Class 'dist' atomic [1:780] -0.16518 -0.00174 -0.00174 -0.00174 -0.00174 ... .. .. ..- attr(*, "Labels")= chr [1:40] "1" "2" "3" "4" ... .. .. ..- attr(*, "Size")= int 40 .. .. ..- attr(*, "call")= language as.dist.default(m = mat_auto) .. .. ..- attr(*, "Diag")= logi FALSE .. .. ..- attr(*, "Upper")= logi FALSE ..$ Class_kinship_results :List of 10 .. ..$ : num [1:97] -0.16518 -0.00174 -0.00174 -0.00174 -0.03193 ... .. ..$ : num [1:157] -0.00174 -0.00174 -0.02292 -0.08243 -0.15206 ... .. ..$ : num [1:119] -0.0455 -0.0921 -0.0455 -0.0455 0.036 ... .. ..$ : num [1:110] -0.0455 -0.1553 -0.1433 -0.047 -0.1513 ... .. ..$ : num [1:121] -0.143 -0.143 -0.114 0.301 -0.181 ... .. ..$ : num [1:64] -0.0918 -0.1236 -0.1236 -0.1024 -0.1236 ... .. ..$ : num [1:34] -0.08461 0.10111 0.1034 -0.00678 0.05459 ... .. ..$ : num [1:29] -0.00693 -0.00693 -0.00693 -0.00693 -0.00693 ... .. ..$ : num [1:31] 0.3935 -0.0646 -0.1289 -0.0656 -0.0825 ... .. ..$ : num [1:18] 0.00503 0.26968 0.00414 -0.02171 -0.04514 ... ..$ Class_distance_results:List of 10 .. ..$ : num [1:97] 2 5.7 7.11 5.15 4.74 ... .. ..$ : num [1:157] 8.06 8.28 9.96 8.08 13.73 ... .. ..$ : num [1:119] 15.4 15.9 17.4 18.7 19.6 ... .. ..$ : num [1:110] 24.5 26.1 26.9 24.1 24.9 ... .. ..$ : num [1:121] 31.3 31.5 34.5 31.8 32.5 ... .. ..$ : num [1:64] 38.5 38.1 38.5 39.5 39.5 ... .. ..$ : num [1:34] 47.4 47.6 52 50 48.9 ... .. ..$ : num [1:29] 60.6 60.7 59.8 58.7 56.5 ... .. ..$ : num [1:31] 63.4 66 61.4 64.1 68 ... .. ..$ : num [1:18] 70 70.8 70.5 73.1 76 ... $ rescl :'data.frame': 1 obs. of 7 variables: ..$ G : num 28 ..$ R : num 0.692 ..$ H” : num 3.15 ..$ J' : num 0.945 ..$ D : num 0.971 ..$ V : num 0.792 ..$ Hill: num 33.9 $ ressimWS:List of 1 ..$ distance_matrix:Class 'dist' atomic [1:499500] 59 126 71 59 63 120 119 164 105 80 ... .. .. ..- attr(*, "Labels")= chr [1:1000] "1" "2" "3" "4" ... .. .. ..- attr(*, "Size")= int 1000 .. .. ..- attr(*, "call")= language as.dist.default(m = dist_all) .. .. ..- attr(*, "Diag")= logi FALSE .. .. ..- attr(*, "Upper")= logi FALSE $ ressim :List of 1 ..$ distance_matrix:Class 'dist' atomic [1:499500] 143 98 138 93 106 98 106 113 109 102 ... .. .. ..- attr(*, "Labels")= chr [1:1000] "1" "2" "3" "4" ... .. .. ..- attr(*, "Size")= int 1000 .. .. ..- attr(*, "call")= language as.dist.default(m = dist_all) .. .. ..- attr(*, "Diag")= logi FALSE .. .. ..- attr(*, "Upper")= logi FALSE $ respop :List of 1 ..$ distance_matrix:Class 'dist' atomic [1:153] 173 178 2 173 178 1 1 84 133 100 ... .. .. ..- attr(*, "Labels")= chr [1:18] "1" "2" "3" "4" ... .. .. ..- attr(*, "Size")= int 18 .. .. ..- attr(*, "call")= language as.dist.default(m = dist_all) .. .. ..- attr(*, "Diag")= logi FALSE .. .. ..- attr(*, "Upper")= logi FALSE $ res_PS4 :'data.frame': 6 obs. of 4 variables: ..$ pgenFis: num [1:6] 1.05e-05 1.09e-10 4.39e-05 4.39e-05 4.39e-05 ... ..$ genet : chr [1:6] "" "" "" "3" ... ..$ psexFis: chr [1:6] "" "" "" "0.00175402908240928" ... ..$ pvalue : chr [1:6] "" "" "" "0.258064516129032" ... $ res_PS3 :List of 2 ..$ :'data.frame': 40 obs. of 3 variables: .. ..$ genet : chr [1:40] "" "" "" "3" ... .. ..$ psexFis: chr [1:40] "" "" "" "0.00175402908240928" ... .. ..$ pvalue : chr [1:40] "" "" "" "0.258064516129032" ... ..$ : num [1:31] 0.004048 0.00316 0.009211 0.000587 0.007884 ... $ res_PS2 :'data.frame': 6 obs. of 4 variables: ..$ pgen : num [1:6] 2.19e-06 2.04e-10 4.77e-05 4.77e-05 4.77e-05 ... ..$ genet : chr [1:6] "" "" "" "3" ... ..$ psex : chr [1:6] "" "" "" "0.00190284159898287" ... ..$ pvalue: chr [1:6] "" "" "" "0.392857142857143" ... $ res_PS1 :List of 2 ..$ :'data.frame': 40 obs. of 3 variables: .. ..$ genet : chr [1:40] "" "" "" "3" ... .. ..$ psex : chr [1:40] "" "" "" "0.00190284159898287" ... .. ..$ pvalue: chr [1:40] "" "" "" "0.392857142857143" ... ..$ : num [1:28] 0.00268 0.00135 0.0034 0.00154 0.0043 ... $ res_SU1 :List of 5 ..$ res_MLG :'data.frame': 7 obs. of 5 variables: .. ..$ nb_loci : int [1:7] 1 2 3 4 5 6 7 .. ..$ min : int [1:7] 3 7 11 19 22 25 28 .. ..$ max : int [1:7] 13 21 26 27 28 28 28 .. ..$ mean_MLG: num [1:7] 6.26 14.27 20.14 23.57 25.44 ... .. ..$ SE : num [1:7] 0.1047 0.1362 0.0966 0.0618 0.046 ... ..$ res_alleles:'data.frame': 7 obs. of 7 variables: .. ..$ nb_loci : int [1:7] 1 2 3 4 5 6 7 .. ..$ min : int [1:7] 2 5 8 11 15 22 29 .. ..$ max : int [1:7] 7 14 18 21 24 27 29 .. ..$ mean_all: num [1:7] 4.09 8.33 12.42 16.53 20.7 ... .. ..$ SE : num [1:7] NA 132.3 88.3 70.2 60.7 ... .. ..$ He : num [1:7] 0.549 0.549 0.55 0.55 0.55 ... .. ..$ SE : num [1:7] NA 1.217 0.803 0.646 0.552 ... ..$ raw_He :'data.frame': 1000 obs. of 7 variables: .. ..$ 1_locus: num [1:1000] 0.531 0.38 0.488 0.488 0.657 ... .. ..$ 2_loci : num [1:1000] 0.621 0.771 0.459 0.519 0.509 ... .. ..$ 3_loci : num [1:1000] 0.483 0.691 0.677 0.558 0.658 ... .. ..$ 4_loci : num [1:1000] 0.517 0.616 0.613 0.559 0.616 ... .. ..$ 5_loci : num [1:1000] 0.538 0.523 0.588 0.517 0.538 ... .. ..$ 6_loci : num [1:1000] 0.534 0.534 0.512 0.6 0.534 ... .. ..$ 7_loci : num [1:1000] 0.551 0.551 0.551 0.551 0.551 ... ..$ raw_MLG :'data.frame': 1000 obs. of 7 variables: .. ..$ 1_locus: int [1:1000] 4 3 6 6 6 6 9 6 6 3 ... .. ..$ 2_loci : int [1:1000] 19 20 12 12 13 12 21 14 17 19 ... .. ..$ 3_loci : int [1:1000] 18 21 23 24 24 19 18 20 18 20 ... .. ..$ 4_loci : int [1:1000] 24 25 21 26 25 23 26 20 21 26 ... .. ..$ 5_loci : int [1:1000] 26 27 24 26 26 25 24 27 26 25 ... .. ..$ 6_loci : int [1:1000] 25 25 26 27 25 27 28 28 28 26 ... .. ..$ 7_loci : int [1:1000] 28 28 28 28 28 28 28 28 28 28 ... ..$ raw_all :'data.frame': 1000 obs. of 7 variables: .. ..$ 1_locus: int [1:1000] 4 2 3 3 3 3 7 3 3 2 ... .. ..$ 2_loci : int [1:1000] 10 14 6 5 7 5 10 6 9 10 ... .. ..$ 3_loci : int [1:1000] 10 18 17 13 14 8 8 9 9 14 ... .. ..$ 4_loci : int [1:1000] 17 17 20 17 17 12 17 16 19 17 ... .. ..$ 5_loci : int [1:1000] 20 19 23 19 20 24 23 24 19 18 ... .. ..$ 6_loci : int [1:1000] 26 26 22 26 26 26 26 27 27 22 ... .. ..$ 7_loci : int [1:1000] 29 29 29 29 29 29 29 29 29 29 ...
Author(s)
Creator/Author: Diane Bailleul <diane.bailleul.pro@gmail.com>
Author: Sophie Arnaud-Haond <sophie.arnaud@ifremer.fr>
Contributor: Solenn Stoeckel
The R implementation of RClone was written by Diane Bailleul.
The design was inspired by GenClone program described in Arnaud-Haond & Belkhir (2007).
Examples
1 2 | #v1 <- vignette("RClone_quickmanual")
#print(v1)
|
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