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Function dm2 conducts Diallel Method 2 analysis for RCBD and Alpha Lattice design.
Example 1: Diallel Method 2 analysis for RCBD design.
# Load the package
library(gpbStat)
#Load the dataset
data(dm2rcbd)
# View the structure of dataframe.
str(dm2rcbd)
#> tibble [240 × 4] (S3: tbl_df/tbl/data.frame)
#> $ rep : chr [1:240] "R1" "R1" "R1" "R1" ...
#> $ parent1: num [1:240] 1 1 1 1 1 1 1 1 1 1 ...
#> $ parent2: num [1:240] 1 2 3 4 5 6 7 8 9 10 ...
#> $ DTP : num [1:240] 66.1 58.5 64.6 64.2 59.3 ...
# Conduct Line x Tester analysis
result = dm2(dm2rcbd, rep, parent1, parent2, DTP)
# View the output
result
#> $Means
#> Parent2
#> Parent1 1 2 3 4 5 6 7 8
#> 1 65.31769 56.88736 62.87728 62.19819 57.24611 61.77934 60.23199 59.45378
#> 2 56.88736 63.30941 62.59786 59.43587 56.45149 57.55432 54.75840 56.11425
#> 3 62.87728 62.59786 58.36095 58.25634 60.71883 55.22639 55.12505 54.39954
#> 4 62.19819 59.43587 58.25634 63.77961 57.15805 63.32091 62.43797 55.12414
#> 5 57.24611 56.45149 60.71883 57.15805 65.04595 55.25778 63.89851 59.23282
#> 6 61.77934 57.55432 55.22639 63.32091 55.25778 56.88325 57.10090 58.62343
#> 7 60.23199 54.75840 55.12505 62.43797 63.89851 57.10090 62.30133 58.96640
#> 8 59.45378 56.11425 54.39954 55.12414 59.23282 58.62343 58.96640 58.63107
#> 9 59.99343 57.79246 54.50506 54.49473 54.72035 57.53263 62.70356 63.63800
#> 10 59.99797 58.12088 59.31957 60.58825 61.87032 61.72040 62.36893 62.04768
#> 11 59.14957 58.54128 64.32069 57.06435 62.42775 62.55616 59.98320 57.74982
#> 12 61.39705 62.77292 56.14993 55.74474 59.85430 58.16224 55.39976 62.39437
#> 13 60.53815 61.92330 58.71091 58.35329 58.69939 63.75573 62.00640 62.53515
#> 14 58.17887 59.62638 60.77991 56.50338 58.24740 60.36659 54.76567 55.49799
#> 15 60.59376 62.45391 56.91712 54.69967 56.86290 57.49282 57.68658 58.62889
#> Parent2
#> Parent1 9 10 11 12 13 14 15
#> 1 59.99343 59.99797 59.14957 61.39705 60.53815 58.17887 60.59376
#> 2 57.79246 58.12088 58.54128 62.77292 61.92330 59.62638 62.45391
#> 3 54.50506 59.31957 64.32069 56.14993 58.71091 60.77991 56.91712
#> 4 54.49473 60.58825 57.06435 55.74474 58.35329 56.50338 54.69967
#> 5 54.72035 61.87032 62.42775 59.85430 58.69939 58.24740 56.86290
#> 6 57.53263 61.72040 62.55616 58.16224 63.75573 60.36659 57.49282
#> 7 62.70356 62.36893 59.98320 55.39976 62.00640 54.76567 57.68658
#> 8 63.63800 62.04768 57.74982 62.39437 62.53515 55.49799 58.62889
#> 9 59.77470 62.65702 60.58196 62.10251 59.52592 58.40839 55.08259
#> 10 62.65702 63.39327 62.95963 58.22418 57.78493 57.43079 59.65661
#> 11 60.58196 62.95963 64.44419 62.62254 62.53704 64.48712 62.86311
#> 12 62.10251 58.22418 62.62254 64.76169 60.89386 59.95167 62.43614
#> 13 59.52592 57.78493 62.53704 60.89386 61.82842 55.83338 63.19762
#> 14 58.40839 57.43079 64.48712 59.95167 55.83338 63.09888 55.26263
#> 15 55.08259 59.65661 62.86311 62.43614 63.19762 55.26263 58.64814
#>
#> $ANOVA
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Replication 1 503.76789 503.7678929 979.33212 2.878133e-59
#> Genotypes 119 2050.09712 17.2277069 33.49091 1.434100e-58
#> Residuals 119 61.21353 0.5143994 NA NA
#>
#> $`Co efficient of ariation`
#> [1] 1.202472
#>
#> $`Diallel ANOVA`
#> Df Sum Sq Mean Sq F value Pr(>F)
#> gca 14 190.03 13.5738 52.775 < 2.2e-16 ***
#> sca 105 835.02 7.9525 30.920 < 2.2e-16 ***
#> Error 119 30.61 0.2572
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> $`Genetic variances`
#> Components
#> gca 0.7833266
#> sca 7.6953340
#> gca/sca 0.1017924
#>
#> $`Combining ability effects`
#> Parent1 Parent2 Parent3 Parent4 Parent5 Parent6
#> Parent1 0.9903421 -3.5909078 3.282732 2.2323001 -3.29618002 1.738335
#> Parent2 NA -0.1572282 4.150876 0.6175547 -2.94322206 -1.339114
#> Parent3 NA NA -1.040942 0.3217366 2.20783036 -2.783330
#> Parent4 NA NA NA -0.6696061 -1.72428674 4.939854
#> Parent5 NA NA NA NA -0.09320439 -3.699678
#> Parent6 NA NA NA NA NA -0.594485
#> Parent7 NA NA NA NA NA NA
#> Parent8 NA NA NA NA NA NA
#> Parent9 NA NA NA NA NA NA
#> Parent10 NA NA NA NA NA NA
#> Parent11 NA NA NA NA NA NA
#> Parent12 NA NA NA NA NA NA
#> Parent13 NA NA NA NA NA NA
#> Parent14 NA NA NA NA NA NA
#> Parent15 NA NA NA NA NA NA
#> Parent7 Parent8 Parent9 Parent10 Parent11 Parent12
#> Parent1 -0.2690067 -0.4373583 0.007025405 -1.6499496 -3.3924020 -0.02122193
#> Parent2 -4.5950278 -2.6293207 -1.046375687 -2.3794715 -2.8531208 2.50222266
#> Parent3 -3.3446630 -3.4603089 -3.450064238 -0.2970702 3.8099996 -3.23705191
#> Parent4 3.5969203 -3.1070514 -3.831733007 0.6002765 -3.8176735 -4.01358089
#> Parent5 4.4810596 0.4252294 -4.182515333 1.3059498 0.9693226 -0.48041658
#> Parent6 -1.8152715 0.3171145 -0.868947362 1.6573031 1.5990125 -1.67119915
#> Parent7 -0.1344958 0.2001023 3.841983864 1.8458473 -1.4339331 -4.89366893
#> Parent8 NA -0.7443537 5.386282248 2.1344515 -3.0574576 2.71080035
#> Parent9 NA NA -0.649082319 2.6485273 -0.3205932 2.32366496
#> Parent10 NA NA NA 1.0124292 0.3955646 -3.21617158
#> Parent11 NA NA NA NA 1.9064819 0.28813378
#> Parent12 NA NA NA NA NA 0.78277604
#> Parent13 NA NA NA NA NA NA
#> Parent14 NA NA NA NA NA NA
#> Parent15 NA NA NA NA NA NA
#> Parent13 Parent14 Parent15
#> Parent1 -1.01672572 -1.7045958 0.7342505
#> Parent2 1.51599938 0.8904886 3.7419789
#> Parent3 -0.81268115 2.9277286 -0.9111020
#> Parent4 -1.54164192 -1.7201357 -3.4998837
#> Parent5 -1.77193727 -0.5525174 -1.9130559
#> Parent6 3.78568415 2.0679497 -0.7818603
#> Parent7 1.57636353 -3.9929557 -1.0480845
#> Parent8 2.71496708 -2.6507822 0.5040763
#> Parent9 -0.38953293 0.1643507 -3.1374949
#> Parent10 -3.79202953 -2.4747643 -0.2249810
#> Parent11 0.06602831 3.6875123 2.0874612
#> Parent12 -0.45345331 0.2757705 2.7841964
#> Parent13 0.91938373 -3.9791285 3.4090766
#> Parent14 NA -0.7520286 -2.8545007
#> Parent15 NA NA -0.7759868
#>
#> $`Standard Error`
#> SE.gi SE.sii SE.sij SE.gi.gj SE.sii.sjj SE.sij.sik SE.sij.skl
#> 0.1188308 0.4783640 0.4456157 0.1739505 0.6271876 0.6958022 0.6737075
#>
#> $`Critical Diffiernece`
#> CD.gi CD.sii CD.sij CD.gi.gj CD.sii.sjj CD.sij.sik CD.sij.skl
#> 0.2352969 0.9472085 0.8823635 0.3444394 1.2418941 1.3777578 1.3340082Example 2: Diallel Method 2 analysis for Alpha Lattice design.
# Load the package
library(gpbStat)
#Load the dataset
data(dm2alpha)
# View the structure of dataframe.
str(dm2alpha)
#> 'data.frame': 240 obs. of 5 variables:
#> $ replication: chr "r1" "r1" "r1" "r1" ...
#> $ block : chr "b2" "b5" "b6" "b12" ...
#> $ parent1 : int 1 1 2 1 2 3 1 2 3 4 ...
#> $ parent2 : int 1 2 2 3 3 3 4 4 4 4 ...
#> $ TW : num 27.7 27.7 44.6 44.6 34.1 ...
# Conduct Diallel Analysis
result1 = dm2(dm2alpha, replication, parent1, parent2, TW, block)
# View the output
result1
#> $Means
#> Parent2
#> Parent1 1 2 3 4 5 6 7 8
#> 1 34.43711 34.43711 39.37157 33.06467 37.36522 34.53972 39.23268 41.75649
#> 2 34.43711 39.37157 38.69548 33.06467 37.36522 35.71489 36.45700 41.75649
#> 3 39.37157 38.69548 38.69548 27.84591 33.95838 35.71489 36.45700 32.21106
#> 4 33.06467 33.06467 27.84591 27.84591 33.95838 34.76627 37.79556 32.21106
#> 5 37.36522 37.36522 33.95838 33.95838 34.53972 34.76627 37.79556 36.55245
#> 6 34.53972 35.71489 35.71489 34.76627 34.76627 39.23268 32.30785 36.55245
#> 7 39.23268 36.45700 36.45700 37.79556 37.79556 32.30785 32.30785 29.98739
#> 8 41.75649 41.75649 32.21106 32.21106 36.55245 36.55245 29.98739 29.98739
#> 9 35.18432 35.18432 40.37017 40.37017 37.10259 37.10259 41.15481 41.15481
#> 10 37.65202 36.53618 36.53618 39.03769 39.03769 34.00577 34.00577 29.19375
#> 11 35.24205 31.97488 31.97488 32.49791 32.49791 42.04574 42.04574 28.60725
#> 12 37.11366 37.11366 34.85844 34.85844 35.99001 35.99001 32.81075 32.81075
#> 13 30.38480 30.38480 40.39449 40.39449 42.50756 42.50756 33.31475 33.31475
#> 14 32.96673 36.88250 36.88250 40.06831 40.06831 34.73526 34.73526 36.98097
#> 15 36.19758 34.07647 34.07647 35.96782 35.96782 34.17183 34.17183 33.36153
#> Parent2
#> Parent1 9 10 11 12 13 14 15
#> 1 35.18432 37.65202 35.24205 37.11366 30.38480 32.96673 36.19758
#> 2 35.18432 36.53618 31.97488 37.11366 30.38480 36.88250 34.07647
#> 3 40.37017 36.53618 31.97488 34.85844 40.39449 36.88250 34.07647
#> 4 40.37017 39.03769 32.49791 34.85844 40.39449 40.06831 35.96782
#> 5 37.10259 39.03769 32.49791 35.99001 42.50756 40.06831 35.96782
#> 6 37.10259 34.00577 42.04574 35.99001 42.50756 34.73526 34.17183
#> 7 41.15481 34.00577 42.04574 32.81075 33.31475 34.73526 34.17183
#> 8 41.15481 29.19375 28.60725 32.81075 33.31475 36.98097 33.36153
#> 9 37.65202 29.19375 28.60725 28.81494 36.98787 36.98097 33.36153
#> 10 29.19375 35.24205 34.70764 28.81494 36.98787 34.43934 40.02420
#> 11 28.60725 34.70764 34.70764 29.38373 32.50283 34.43934 40.02420
#> 12 28.81494 28.81494 29.38373 29.38373 32.50283 29.15149 37.41538
#> 13 36.98787 36.98787 32.50283 32.50283 32.96673 29.15149 37.41538
#> 14 36.98097 34.43934 34.43934 29.15149 29.15149 36.19758 30.95810
#> 15 33.36153 40.02420 40.02420 37.41538 37.41538 30.95810 30.95810
#>
#> $ANOVA
#> Df Sum Sq Mean Sq F value Pr(>F)
#> Replication 1 81.1883 81.18830 2.3477738 0.1287171
#> Treatments 119 3086.8726 25.94011 0.7501265 0.9324158
#> Replication:Block 22 774.0140 35.18245 1.0173933 0.4515091
#> Residuals 97 3354.3545 34.58097 NA NA
#>
#> $`Co efficient of Variation`
#> [1] 16.69164
#>
#> $`Diallel ANOVA`
#> Df Sum Sq Mean Sq F value Pr(>F)
#> gca 14 214.93 15.352 0.8879 0.5740
#> sca 105 1328.50 12.652 0.7318 0.9414
#> Error 97 1677.18 17.291
#>
#> $`Genetic variances`
#> Components
#> gca -0.11400667
#> sca -4.63807702
#> gca/sca 0.02458059
#>
#> $`Combining ability effects`
#> Parent1 Parent2 Parent3 Parent4 Parent5 Parent6
#> Parent1 0.5702231 -2.2282544 2.8031705 -2.0245991 0.36891376 -2.4197435
#> Parent2 NA 0.8645744 1.8327300 -2.3189504 0.07456246 -1.5389250
#> Parent3 NA NA 0.7676086 -7.4407375 -3.23531254 -1.4419592
#> Parent4 NA NA NA -0.7115204 -1.75618353 -0.9114479
#> Parent5 NA NA NA NA 1.19551556 -2.8184839
#> Parent6 NA NA NA NA NA 1.1586731
#> Parent7 NA NA NA NA NA NA
#> Parent8 NA NA NA NA NA NA
#> Parent9 NA NA NA NA NA NA
#> Parent10 NA NA NA NA NA NA
#> Parent11 NA NA NA NA NA NA
#> Parent12 NA NA NA NA NA NA
#> Parent13 NA NA NA NA NA NA
#> Parent14 NA NA NA NA NA NA
#> Parent15 NA NA NA NA NA NA
#> Parent7 Parent8 Parent9 Parent10 Parent11 Parent12
#> Parent1 3.2437392 6.971173 -1.39206575 2.0295979 0.4837521 3.5065499
#> Parent2 0.1737017 6.676821 -1.68641706 0.6194025 -3.0777614 3.2121986
#> Parent3 0.2706675 -2.771642 3.59640003 0.7163682 -2.9807956 1.0539489
#> Parent4 3.0883589 -1.292513 5.07552903 4.6970040 -0.9786428 2.5330779
#> Parent5 1.1813229 1.141844 -0.09908242 2.7899680 -2.8856788 1.7576095
#> Parent6 -4.2695400 1.178686 -0.06223995 -2.2051039 6.6989990 1.7944520
#> Parent7 0.1881555 -4.415855 4.96049545 -1.2345864 7.6695165 -0.4142896
#> Parent8 NA -1.015472 6.16412289 -4.8429771 -4.5653485 0.7893378
#> Parent9 NA NA 0.77559560 -6.6340446 -6.3564160 -4.9975405
#> Parent10 NA NA NA -0.1783598 0.6979297 -4.0435851
#> Parent11 NA NA NA NA -1.0424929 -2.6106636
#> Parent12 NA NA NA NA NA -2.1936764
#> Parent13 NA NA NA NA NA NA
#> Parent14 NA NA NA NA NA NA
#> Parent15 NA NA NA NA NA NA
#> Parent13 Parent14 Parent15
#> Parent1 -5.47456663 -2.6662196 0.6663589
#> Parent2 -5.76891793 0.9552010 -1.7490983
#> Parent3 4.33773631 1.0521668 -1.6521325
#> Parent4 5.81686532 5.7171100 1.7183466
#> Parent5 6.02289319 3.8100741 -0.1886894
#> Parent6 6.05973565 -1.4861358 -1.9478368
#> Parent7 -2.16254868 -0.5156182 -0.9773192
#> Parent8 -0.95892124 2.9337212 -0.5839923
#> Parent9 0.92312510 1.1426537 -2.3750598
#> Parent10 1.87708054 -0.4450236 5.2415658
#> Parent11 -1.74382435 0.4191094 6.1056988
#> Parent12 -0.59264080 -3.7175549 4.6480600
#> Parent13 0.05858292 -5.9698143 2.3958007
#> Parent14 NA -0.1678390 -3.8350536
#> Parent15 NA NA -0.2695682
#>
#> $`Standard Error`
#> SE.gi SE.sii SE.sij SE.gi.gj SE.sii.sjj SE.sij.sik SE.sij.skl
#> 0.9743109 3.9221739 3.6536657 1.4262451 5.1423997 5.7049802 5.5238233
#>
#> $`Critical Diffiernece`
#> CD.gi CD.sii CD.sij CD.gi.gj CD.sii.sjj CD.sij.sik CD.sij.skl
#> 1.933737 7.784429 7.251515 2.830702 10.206240 11.322806 10.963260These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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