56 - Matrix Synergy ================ Steven Roberts 11 September, 2023 - 1 Will Redo methylation to get all samples.. - 1.1 sample metadata - 2 checking for consistency - 3 checking for consistency - 4 correlation We have a few matrices comparing samples but the are not directly comparable. Currently we have SNP data like this.. ![snp](http://gannet.fish.washington.edu/seashell/snaps/Monosnap_ceabigr__RStudio_Server_2023-08-31_11-04-02.png) Gene expression data like this.. ![gene](http://gannet.fish.washington.edu/seashell/snaps/Monosnap_Run_a_correlation_between_genetic_distance_and_gene_expression__methylation_distance_matrices__Issue_84__sr320ceabigr_2023-08-31_11-07-51.png) Methylation like .. ![meth](http://gannet.fish.washington.edu/seashell/snaps/Monosnap_ceabigr__RStudio_Server_2023-08-31_11-09-03.png) # 1 Will Redo methylation to get all samples.. ## 1.1 sample metadata | Sample.ID | OldSample.ID | Treatment | Sex | TreatmentN | Parent.ID | |:----------|:-------------|:----------|:----|:-----------|:----------| | 12M | S12M | Exposed | M | 3 | EM05 | | 13M | S13M | Control | M | 1 | CM04 | | 16F | S16F | Control | F | 2 | CF05 | | 19F | S19F | Control | F | 2 | CF08 | | 22F | S22F | Exposed | F | 4 | EF02 | | 23M | S23M | Exposed | M | 3 | EM04 | | 29F | S29F | Exposed | F | 4 | EF07 | | 31M | S31M | Exposed | M | 3 | EM06 | | 35F | S35F | Exposed | F | 4 | EF08 | | 36F | S36F | Exposed | F | 4 | EF05 | | 39F | S39F | Control | F | 2 | CF06 | | 3F | S3F | Exposed | F | 4 | EF06 | | 41F | S41F | Exposed | F | 4 | EF03 | | 44F | S44F | Control | F | 2 | CF03 | | 48M | S48M | Exposed | M | 3 | EM03 | | 50F | S50F | Exposed | F | 4 | EF01 | | 52F | S52F | Control | F | 2 | CF07 | | 53F | S53F | Control | F | 2 | CF02 | | 54F | S54F | Control | F | 2 | CF01 | | 59M | S59M | Exposed | M | 3 | EM01 | | 64M | S64M | Control | M | 1 | CM05 | | 6M | S6M | Control | M | 1 | CM02 | | 76F | S76F | Control | F | 2 | CF04 | | 77F | S77F | Exposed | F | 4 | EF04 | | 7M | S7M | Control | M | 1 | CM01 | | 9M | S9M | Exposed | M | 3 | EM02 | ``` bash cd ../data/big curl -O https://gannet.fish.washington.edu/seashell/bu-github/2018_L18-adult-methylation/analyses/myobj_oa ``` ``` r filtered.myobj=filterByCoverage(myobj_oa,lo.count=10,lo.perc=NULL, hi.count=NULL,hi.perc=98) meth_filter=unite(filtered.myobj, min.per.group=NULL, destrand=TRUE) clusterSamples(meth_filter, dist="correlation", method="ward", plot=TRUE) PCASamples(meth_filter) ``` Laura’s code ``` r perc.meth=percMethylation(meth_filter, rowids=T) ``` ``` r #Save % methylation df to object and .tab file save(perc.meth, file = "../output/56-matrix-synergy/all-perc.meth") #save object to file ``` ``` r load(file = "../output/56-matrix-synergy/all-perc.meth") #load object if needed ``` ``` r #write.table((as.data.frame(perc.meth) %>% tibble::rownames_to_column("contig")), file = "../output/55-methylation-matrix/male-perc.meth.tab", sep = '\t', na = "NA", row.names = FALSE, col.names = TRUE) ``` ``` r perc.meth_T <- t(perc.meth) ``` ``` r correlationMatrix <- cor(perc.meth_T) ``` ``` r distanceMatrix <- dist(perc.meth_T) ``` ``` r # Convert distance matrix to a regular matrix matrixForm <- as.matrix(distanceMatrix) # Display the matrix print(matrixForm) ``` ## 12M 13M 16F 19F 22F 23M 29F 31M ## 12M 0.00 23304.01 30773.35 29629.70 30346.25 23098.58 31184.73 23129.98 ## 13M 23304.01 0.00 31014.11 29879.93 30587.51 23344.65 30795.72 23356.35 ## 16F 30773.35 31014.11 0.00 21908.45 22130.65 31511.83 21954.90 31138.59 ## 19F 29629.70 29879.93 21908.45 0.00 21383.26 30272.65 21751.81 30048.86 ## 22F 30346.25 30587.51 22130.65 21383.26 0.00 31126.69 21748.06 30843.14 ## 23M 23098.58 23344.65 31511.83 30272.65 31126.69 0.00 31986.18 23189.74 ## 29F 31184.73 30795.72 21954.90 21751.81 21748.06 31986.18 0.00 31192.70 ## 31M 23129.98 23356.35 31138.59 30048.86 30843.14 23189.74 31192.70 0.00 ## 35F 29283.62 29464.21 22231.28 21656.49 21939.90 29955.70 22065.75 29655.75 ## 36F 29251.41 29474.21 22292.71 21511.49 21806.09 29935.49 22170.41 29648.06 ## 39F 29579.97 29236.69 22057.29 21624.73 21906.64 30199.07 21423.26 29902.22 ## 3F 31919.23 31853.28 22432.76 21911.40 22252.87 32447.18 21904.46 31683.66 ## 41F 32063.83 32161.13 22808.30 22031.13 22128.82 32830.28 22217.91 32443.45 ## 44F 31068.04 31178.57 21399.95 21324.27 21368.22 31540.12 20634.29 31412.10 ## 48M 22942.88 22983.32 30990.10 29744.86 30423.65 22483.58 31359.26 23310.80 ## 50F 30802.18 30925.90 22163.84 21635.20 21877.25 31438.81 21873.67 31145.29 ## 52F 32363.67 32560.67 22081.44 22468.54 22479.71 33105.26 22489.10 32763.03 ## 53F 29715.85 29916.97 22096.18 21609.50 21920.39 30529.01 21910.00 30078.30 ## 54F 30263.18 30218.75 21707.26 21245.89 21462.58 30907.61 21081.23 30618.47 ## 59M 23373.46 22750.43 31684.28 30506.55 31287.24 21719.67 31365.02 23638.96 ## 64M 23109.80 23470.15 31088.76 29805.08 30607.09 23134.88 31270.04 23368.54 ## 6M 22788.21 22821.71 31009.81 29855.33 30526.70 23003.41 31223.09 23359.32 ## 76F 28416.24 28133.35 22821.71 21997.49 22735.05 28182.87 22293.72 28600.92 ## 77F 29508.27 29423.39 22009.22 21394.53 21836.51 29941.71 21642.05 29756.03 ## 7M 23029.43 23402.97 31265.45 30162.05 30724.11 23068.02 31741.13 23465.14 ## 9M 22958.67 23244.69 31048.02 29908.63 30620.98 23214.31 31179.96 22945.08 ## 35F 36F 39F 3F 41F 44F 48M 50F ## 12M 29283.62 29251.41 29579.97 31919.23 32063.83 31068.04 22942.88 30802.18 ## 13M 29464.21 29474.21 29236.69 31853.28 32161.13 31178.57 22983.32 30925.90 ## 16F 22231.28 22292.71 22057.29 22432.76 22808.30 21399.95 30990.10 22163.84 ## 19F 21656.49 21511.49 21624.73 21911.40 22031.13 21324.27 29744.86 21635.20 ## 22F 21939.90 21806.09 21906.64 22252.87 22128.82 21368.22 30423.65 21877.25 ## 23M 29955.70 29935.49 30199.07 32447.18 32830.28 31540.12 22483.58 31438.81 ## 29F 22065.75 22170.41 21423.26 21904.46 22217.91 20634.29 31359.26 21873.67 ## 31M 29655.75 29648.06 29902.22 31683.66 32443.45 31412.10 23310.80 31145.29 ## 35F 0.00 22013.48 21863.41 22476.44 23001.00 21806.94 29461.33 22206.57 ## 36F 22013.48 0.00 21946.62 22265.72 22625.56 21727.24 29237.54 22039.75 ## 39F 21863.41 21946.62 0.00 22223.98 22783.80 21444.18 29546.26 22094.86 ## 3F 22476.44 22265.72 22223.98 0.00 22331.44 21401.95 31986.42 22021.11 ## 41F 23001.00 22625.56 22783.80 22331.44 0.00 21778.71 32225.97 21921.02 ## 44F 21806.94 21727.24 21444.18 21401.95 21778.71 0.00 31055.08 21422.94 ## 48M 29461.33 29237.54 29546.26 31986.42 32225.97 31055.08 0.00 30972.88 ## 50F 22206.57 22039.75 22094.86 22021.11 21921.02 21422.94 30972.88 0.00 ## 52F 22885.74 22929.15 22604.14 22616.16 23005.97 21831.33 32573.71 22538.13 ## 53F 21911.35 21903.17 21895.49 22009.51 22388.48 21503.49 29991.58 21826.59 ## 54F 21600.18 21442.54 21312.10 21646.93 22041.85 20586.03 30095.88 21371.09 ## 59M 30049.34 30070.87 30074.60 32655.96 33083.72 31343.95 22089.64 31665.59 ## 64M 29515.73 29439.19 29731.60 31980.40 32138.93 31173.58 22999.28 30930.63 ## 6M 29538.67 29424.15 29381.81 32092.12 32304.58 31281.94 22890.16 31055.19 ## 76F 22279.71 22178.59 21720.06 22850.60 23668.90 21542.05 28105.05 22620.45 ## 77F 21759.72 21715.88 21211.64 22177.69 22708.95 21159.08 29112.22 22171.96 ## 7M 29702.59 29743.46 30021.30 32418.32 32604.45 31613.32 22890.79 31317.87 ## 9M 29555.82 29228.70 29783.48 31724.89 32318.57 31117.51 22928.40 31126.25 ## 52F 53F 54F 59M 64M 6M 76F 77F ## 12M 32363.67 29715.85 30263.18 23373.46 23109.80 22788.21 28416.24 29508.27 ## 13M 32560.67 29916.97 30218.75 22750.43 23470.15 22821.71 28133.35 29423.39 ## 16F 22081.44 22096.18 21707.26 31684.28 31088.76 31009.81 22821.71 22009.22 ## 19F 22468.54 21609.50 21245.89 30506.55 29805.08 29855.33 21997.49 21394.53 ## 22F 22479.71 21920.39 21462.58 31287.24 30607.09 30526.70 22735.05 21836.51 ## 23M 33105.26 30529.01 30907.61 21719.67 23134.88 23003.41 28182.87 29941.71 ## 29F 22489.10 21910.00 21081.23 31365.02 31270.04 31223.09 22293.72 21642.05 ## 31M 32763.03 30078.30 30618.47 23638.96 23368.54 23359.32 28600.92 29756.03 ## 35F 22885.74 21911.35 21600.18 30049.34 29515.73 29538.67 22279.71 21759.72 ## 36F 22929.15 21903.17 21442.54 30070.87 29439.19 29424.15 22178.59 21715.88 ## 39F 22604.14 21895.49 21312.10 30074.60 29731.60 29381.81 21720.06 21211.64 ## 3F 22616.16 22009.51 21646.93 32655.96 31980.40 32092.12 22850.60 22177.69 ## 41F 23005.97 22388.48 22041.85 33083.72 32138.93 32304.58 23668.90 22708.95 ## 44F 21831.33 21503.49 20586.03 31343.95 31173.58 31281.94 21542.05 21159.08 ## 48M 32573.71 29991.58 30095.88 22089.64 22999.28 22890.16 28105.05 29112.22 ## 50F 22538.13 21826.59 21371.09 31665.59 30930.63 31055.19 22620.45 22171.96 ## 52F 0.00 22619.24 22269.99 33291.68 32613.68 32578.74 23697.28 22652.05 ## 53F 22619.24 0.00 20850.13 30789.88 29919.82 30063.84 22370.49 21719.54 ## 54F 22269.99 20850.13 0.00 30695.49 30366.81 30475.49 21760.94 20823.23 ## 59M 33291.68 30789.88 30695.49 0.00 23189.99 23272.60 27812.48 29895.81 ## 64M 32613.68 29919.82 30366.81 23189.99 0.00 23192.01 28615.15 29621.81 ## 6M 32578.74 30063.84 30475.49 23272.60 23192.01 0.00 28373.61 29473.32 ## 76F 23697.28 22370.49 21760.94 27812.48 28615.15 28373.61 0.00 21258.78 ## 77F 22652.05 21719.54 20823.23 29895.81 29621.81 29473.32 21258.78 0.00 ## 7M 32871.65 30334.13 30679.36 23290.29 23120.35 22998.42 28973.02 29872.25 ## 9M 32641.74 30154.49 30400.04 23362.47 23315.06 22998.20 28502.96 29486.18 ## 7M 9M ## 12M 23029.43 22958.67 ## 13M 23402.97 23244.69 ## 16F 31265.45 31048.02 ## 19F 30162.05 29908.63 ## 22F 30724.11 30620.98 ## 23M 23068.02 23214.31 ## 29F 31741.13 31179.96 ## 31M 23465.14 22945.08 ## 35F 29702.59 29555.82 ## 36F 29743.46 29228.70 ## 39F 30021.30 29783.48 ## 3F 32418.32 31724.89 ## 41F 32604.45 32318.57 ## 44F 31613.32 31117.51 ## 48M 22890.79 22928.40 ## 50F 31317.87 31126.25 ## 52F 32871.65 32641.74 ## 53F 30334.13 30154.49 ## 54F 30679.36 30400.04 ## 59M 23290.29 23362.47 ## 64M 23120.35 23315.06 ## 6M 22998.42 22998.20 ## 76F 28973.02 28502.96 ## 77F 29872.25 29486.18 ## 7M 0.00 22970.83 ## 9M 22970.83 0.00 ``` r heatmap(matrixForm, Rowv = NA, Colv = NA, col = cm.colors(256), scale = "none") ``` ``` r dataFrameForm <- as.data.frame(matrixForm) print(dataFrameForm) ``` ``` r write.table((as.data.frame(matrixForm) %>% tibble::rownames_to_column("sample")), file = "../output/56-matrix-synergy/all.meth-distance.tab", sep = '\t', na = "NA", row.names = FALSE, col.names = TRUE) ``` # 2 checking for consistency text file.. ``` bash head -2 ../output/56-matrix-synergy/all.meth-distance.tab ``` ## "sample" "12M" "13M" "16F" "19F" "22F" "23M" "29F" "31M" "35F" "36F" "39F" "3F" "41F" "44F" "48M" "50F" "52F" "53F" "54F" "59M" "64M" "6M" "76F" "77F" "7M" "9M" ## "12M" 0 23304.0069449018 30773.3548066289 29629.7022439496 30346.249437145 23098.5830496124 31184.7314314988 23129.978377816 29283.6227675114 29251.4098948392 29579.9714132613 31919.2256764399 32063.8313572642 31068.0409488934 22942.8760393046 30802.1750112176 32363.6733837327 29715.84843474 30263.1784448872 23373.4562991821 23109.804844686 22788.2103589562 28416.2384891171 29508.2720313387 23029.4325530648 22958.6680752021 ``` bash head -2 ../output/53-revisit-epi-SNPs/epiMATRIX_mbd_rab.txt ``` ## "sample" "12M" "13M" "16F" "19F" "22F" "23M" "29F" "31M" "35F" "36F" "39F" "3F" "41F" "44F" "48M" "50F" "52F" "53F" "54F" "59M" "64M" "6M" "76F" "77F" "7M" "9M" ## "12M" 0 0.051833 0.065087 0.074943 0.052083 0.056348 0.063667 0.057863 0.072606 0.067544 0.061042 0.042357 0.057715 0.067394 0.059371 0.055395 0.067694 0.060491 0.061507 0.050297 0.058001 0.059446 0.044517 0.058163 0.06416 0.055671 # 3 checking for consistency matrices.. ``` r load(file = "../output/53-revisit-epi-SNPs/distrab") #load object if needed ``` ``` r str(matrixForm) ``` ## num [1:26, 1:26] 0 23304 30773 29630 30346 ... ## - attr(*, "dimnames")=List of 2 ## ..$ : chr [1:26] "12M" "13M" "16F" "19F" ... ## ..$ : chr [1:26] "12M" "13M" "16F" "19F" ... ``` r str(distrab) ``` ## num [1:26, 1:26] 0 0.0518 0.0651 0.0749 0.0521 ... ## - attr(*, "dimnames")=List of 2 ## ..$ : chr [1:26] "12M" "13M" "16F" "19F" ... ## ..$ : chr [1:26] "12M" "13M" "16F" "19F" ... # 4 correlation ``` r cor_matrix <- cor(matrixForm,distrab) ``` ``` r heatmap(cor_matrix) ```

``` r # Create a data frame from the correlation matrix cor_melted <- as.data.frame(as.table(cor_matrix)) # Create the heatmap ggplot(data=cor_melted, aes(x=Var1, y=Var2)) + geom_tile(aes(fill=Freq), color='white') + scale_fill_gradient2(low="blue", high="red", mid="white", midpoint=0) + # geom_text(aes(label=sprintf("%.2f", Freq)), vjust=1) + theme_minimal() + labs(fill="Correlation") ```

``` r cor_long <- as.data.frame(as.table(cor_matrix)) cor_long_sorted <- cor_long %>% filter(Var1 != Var2) %>% arrange(desc(abs(Freq))) print(cor_long_sorted) ``` ## Var1 Var2 Freq ## 1 59M 76F -0.5958548721 ## 2 76F 59M -0.4731418012 ## 3 59M 29F -0.4005978750 ## 4 19F 12M -0.3859781485 ## 5 39F 6M -0.3849202691 ## 6 36F 9M -0.3785606877 ## 7 13M 29F -0.3755641839 ## 8 35F 12M -0.3625761112 ## 9 52F 7M -0.3615916264 ## 10 29F 9M -0.3607029960 ## 11 39F 13M -0.3579498902 ## 12 29F 13M -0.3568732686 ## 13 19F 7M -0.3428635431 ## 14 54F 53F -0.3418980839 ## 15 59M 23M -0.3398098801 ## 16 9M 3F -0.3333974660 ## 17 52F 12M -0.3315183087 ## 18 16F 7M -0.3248913238 ## 19 36F 7M -0.3248006321 ## 20 59M 22F 0.3232793764 ## 21 44F 12M -0.3218638583 ## 22 22F 76F 0.3214810844 ## 23 44F 9M -0.3204748893 ## 24 76F 23M -0.3197749738 ## 25 23M 76F -0.3175789109 ## 26 23M 59M -0.3135704981 ## 27 9M 29F -0.3115060769 ## 28 36F 12M -0.3089921957 ## 29 77F 48M -0.3083561070 ## 30 54F 7M -0.3032553477 ## 31 16F 12M -0.3030487002 ## 32 53F 76F 0.2978910887 ## 33 41F 29F 0.2965878275 ## 34 29F 6M -0.2938804443 ## 35 29F 12M -0.2898694635 ## 36 35F 22F -0.2847618833 ## 37 77F 9M -0.2794185184 ## 38 3F 9M -0.2785544158 ## 39 31M 3F -0.2774884786 ## 40 9M 31M -0.2774160775 ## 41 59M 53F 0.2746245981 ## 42 76F 44F -0.2741093729 ## 43 35F 7M -0.2738426095 ## 44 31M 7M 0.2726752287 ## 45 22F 29F 0.2709407214 ## 46 54F 12M -0.2682967258 ## 47 6M 29F -0.2679065310 ## 48 77F 6M -0.2665468348 ## 49 52F 76F 0.2640992044 ## 50 53F 64M -0.2640634566 ## 51 44F 7M -0.2639337882 ## 52 13M 39F -0.2634213535 ## 53 31M 22F 0.2599438501 ## 54 41F 76F 0.2588279247 ## 55 59M 12M 0.2587169682 ## 56 23M 44F -0.2577109631 ## 57 3F 29F 0.2569075176 ## 58 59M 9M 0.2569043984 ## 59 48M 77F -0.2560015968 ## 60 16F 22F -0.2552088338 ## 61 50F 7M -0.2551453419 ## 62 29F 64M -0.2547145634 ## 63 50F 29F 0.2538060950 ## 64 19F 76F 0.2502249560 ## 65 48M 76F -0.2501274369 ## 66 39F 12M -0.2492073243 ## 67 16F 76F 0.2482472849 ## 68 44F 23M -0.2478931437 ## 69 53F 54F -0.2475069372 ## 70 59M 50F 0.2456519174 ## 71 53F 12M -0.2445990689 ## 72 23M 9M 0.2439689854 ## 73 76F 48M -0.2439305559 ## 74 39F 7M -0.2428607944 ## 75 3F 76F 0.2427587857 ## 76 54F 9M -0.2413975900 ## 77 77F 54F -0.2389313129 ## 78 13M 12M 0.2386103231 ## 79 41F 12M -0.2359274846 ## 80 16F 9M -0.2355854762 ## 81 54F 48M -0.2341688541 ## 82 31M 29F -0.2338554430 ## 83 54F 64M -0.2322243495 ## 84 50F 22F -0.2314524686 ## 85 6M 39F -0.2314375979 ## 86 48M 59M -0.2312471418 ## 87 19F 50F -0.2295367321 ## 88 35F 76F 0.2274858923 ## 89 6M 9M 0.2270109412 ## 90 50F 41F -0.2269464285 ## 91 59M 41F 0.2256083102 ## 92 77F 12M -0.2230645743 ## 93 59M 35F 0.2219517072 ## 94 19F 29F 0.2219308112 ## 95 29F 31M -0.2214621327 ## 96 52F 22F -0.2205802874 ## 97 77F 7M -0.2202637742 ## 98 13M 7M 0.2202614432 ## 99 53F 50F -0.2180172262 ## 100 50F 76F 0.2177038358 ## 101 44F 64M -0.2175488372 ## 102 19F 41F -0.2164027684 ## 103 36F 22F -0.2163403563 ## 104 13M 22F 0.2159048560 ## 105 41F 22F -0.2141623343 ## 106 36F 76F 0.2111820243 ## 107 41F 50F -0.2102510244 ## 108 16F 29F 0.2102157220 ## 109 53F 29F 0.2101917349 ## 110 19F 22F -0.2097814983 ## 111 50F 12M -0.2088308435 ## 112 3F 59M 0.2083918364 ## 113 29F 7M -0.2071118589 ## 114 52F 9M -0.2070577612 ## 115 52F 50F -0.2067840144 ## 116 23M 12M 0.2066599757 ## 117 35F 52F -0.2064845361 ## 118 59M 3F 0.2064444678 ## 119 54F 22F -0.2060258693 ## 120 41F 7M -0.2057259139 ## 121 59M 7M 0.2053226897 ## 122 9M 36F -0.2052465017 ## 123 9M 12M 0.2044519087 ## 124 54F 13M -0.2042403342 ## 125 23M 7M 0.2035478167 ## 126 3F 39F 0.2034682631 ## 127 36F 16F -0.2014138591 ## 128 3F 77F 0.2002359695 ## 129 12M 29F -0.1979862287 ## 130 22F 7M -0.1973244447 ## 131 13M 59M -0.1958749342 ## 132 53F 7M -0.1947589303 ## 133 35F 9M -0.1938199288 ## 134 31M 6M 0.1936642564 ## 135 19F 9M -0.1928992829 ## 136 76F 53F 0.1926258238 ## 137 13M 76F -0.1910019563 ## 138 76F 13M -0.1905852670 ## 139 64M 9M 0.1905081494 ## 140 76F 19F 0.1898436853 ## 141 64M 29F -0.1886187567 ## 142 53F 41F -0.1885692611 ## 143 59M 48M -0.1881857910 ## 144 19F 52F -0.1865885922 ## 145 52F 29F 0.1856616365 ## 146 39F 64M -0.1852744587 ## 147 31M 12M 0.1851114923 ## 148 41F 64M -0.1830885907 ## 149 36F 52F -0.1814249867 ## 150 59M 44F -0.1807593073 ## 151 36F 64M -0.1806566959 ## 152 52F 35F -0.1802339811 ## 153 53F 22F -0.1799292341 ## 154 36F 29F 0.1797888406 ## 155 22F 12M -0.1794617429 ## 156 35F 50F -0.1788392453 ## 157 16F 64M -0.1785873830 ## 158 19F 53F -0.1765503140 ## 159 64M 12M 0.1763392616 ## 160 29F 54F -0.1756986180 ## 161 52F 41F -0.1756243222 ## 162 7M 52F -0.1744210746 ## 163 77F 13M -0.1742491860 ## 164 35F 41F -0.1736700502 ## 165 44F 22F -0.1731985287 ## 166 19F 35F -0.1725508345 ## 167 64M 7M 0.1713948989 ## 168 6M 12M 0.1705784197 ## 169 41F 77F 0.1705737807 ## 170 48M 12M 0.1689832554 ## 171 76F 77F -0.1687281108 ## 172 3F 31M -0.1681005593 ## 173 22F 59M 0.1677131324 ## 174 12M 9M 0.1673133510 ## 175 41F 44F 0.1669011678 ## 176 9M 44F -0.1666694489 ## 177 48M 9M 0.1663924255 ## 178 39F 9M -0.1655076181 ## 179 9M 22F 0.1653326009 ## 180 16F 6M -0.1645411943 ## 181 13M 9M 0.1641968769 ## 182 16F 41F -0.1632970998 ## 183 36F 19F -0.1623810739 ## 184 6M 7M 0.1616821121 ## 185 35F 6M -0.1616310950 ## 186 31M 48M 0.1608373215 ## 187 50F 53F -0.1605809120 ## 188 19F 64M -0.1595763685 ## 189 54F 6M -0.1594596570 ## 190 53F 77F 0.1589964862 ## 191 16F 35F -0.1580561260 ## 192 54F 52F -0.1579264006 ## 193 52F 53F -0.1563739358 ## 194 59M 31M 0.1550199659 ## 195 44F 54F -0.1547360645 ## 196 22F 77F 0.1541335716 ## 197 53F 39F 0.1540436839 ## 198 19F 6M -0.1540133684 ## 199 6M 31M 0.1511704161 ## 200 6M 64M 0.1511676134 ## 201 36F 35F -0.1506847568 ## 202 41F 59M 0.1505214287 ## 203 54F 35F -0.1499360117 ## 204 50F 64M -0.1493560578 ## 205 9M 53F 0.1492905120 ## 206 77F 64M -0.1491359654 ## 207 35F 16F -0.1484647720 ## 208 22F 50F -0.1481378079 ## 209 7M 29F -0.1479037218 ## 210 22F 39F 0.1474057161 ## 211 52F 64M -0.1457696942 ## 212 76F 9M -0.1457670885 ## 213 39F 16F -0.1452352859 ## 214 76F 22F 0.1451682633 ## 215 36F 50F -0.1446946889 ## 216 19F 16F -0.1443924001 ## 217 9M 77F -0.1440169006 ## 218 19F 36F -0.1433101058 ## 219 44F 48M -0.1432467750 ## 220 9M 76F -0.1413667486 ## 221 54F 76F 0.1409917200 ## 222 76F 16F 0.1409148440 ## 223 39F 22F -0.1403861055 ## 224 36F 48M -0.1399274821 ## 225 22F 44F 0.1395049021 ## 226 76F 36F 0.1387035990 ## 227 39F 50F -0.1387030669 ## 228 44F 52F -0.1379555366 ## 229 53F 59M 0.1373451504 ## 230 54F 50F -0.1371853156 ## 231 41F 39F 0.1370986099 ## 232 6M 77F -0.1367259548 ## 233 16F 52F -0.1358433253 ## 234 53F 52F -0.1356414461 ## 235 31M 35F 0.1350559832 ## 236 23M 35F 0.1349838499 ## 237 48M 53F 0.1344454659 ## 238 22F 41F -0.1343911666 ## 239 41F 9M -0.1342323705 ## 240 50F 59M 0.1332047175 ## 241 48M 64M 0.1324475358 ## 242 77F 39F -0.1321336757 ## 243 44F 31M -0.1317495820 ## 244 3F 44F 0.1316655123 ## 245 12M 52F -0.1301425405 ## 246 39F 48M -0.1298297047 ## 247 31M 50F 0.1297070171 ## 248 29F 39F -0.1292232640 ## 249 13M 64M 0.1291307528 ## 250 59M 16F 0.1289822380 ## 251 39F 77F -0.1287892036 ## 252 23M 22F 0.1287530607 ## 253 59M 19F 0.1286740270 ## 254 13M 50F 0.1277581897 ## 255 77F 22F -0.1274222518 ## 256 54F 77F -0.1266237022 ## 257 31M 54F 0.1264704492 ## 258 3F 19F 0.1263344396 ## 259 41F 53F -0.1260974008 ## 260 59M 64M 0.1260532722 ## 261 35F 64M -0.1258318907 ## 262 50F 52F -0.1248556518 ## 263 29F 59M -0.1246617964 ## 264 7M 16F -0.1245239971 ## 265 16F 36F -0.1243150127 ## 266 76F 35F 0.1240565543 ## 267 35F 53F -0.1237703706 ## 268 48M 31M 0.1227984017 ## 269 6M 76F -0.1224654502 ## 270 19F 48M -0.1219899445 ## 271 12M 19F -0.1218641538 ## 272 50F 77F 0.1216331962 ## 273 59M 77F -0.1214727151 ## 274 23M 3F -0.1210087322 ## 275 6M 50F 0.1209897935 ## 276 50F 44F 0.1207710654 ## 277 7M 12M 0.1204826679 ## 278 29F 22F -0.1197849361 ## 279 39F 35F -0.1194157391 ## 280 76F 52F 0.1192766106 ## 281 44F 13M -0.1184154773 ## 282 35F 29F 0.1177562503 ## 283 16F 50F -0.1175542464 ## 284 23M 13M 0.1174448887 ## 285 59M 36F 0.1173541320 ## 286 31M 36F 0.1168450369 ## 287 9M 64M 0.1167932766 ## 288 54F 16F -0.1167573923 ## 289 64M 35F 0.1165539411 ## 290 3F 54F 0.1164541056 ## 291 59M 13M -0.1163708442 ## 292 52F 6M -0.1159459501 ## 293 54F 41F -0.1159408597 ## 294 9M 50F 0.1142023416 ## 295 76F 6M -0.1137968868 ## 296 44F 50F -0.1137665108 ## 297 12M 44F -0.1136156465 ## 298 35F 13M -0.1130074954 ## 299 19F 31M -0.1126907913 ## 300 13M 16F 0.1126548045 ## 301 16F 31M -0.1124953625 ## 302 3F 7M -0.1122151737 ## 303 64M 22F 0.1116959732 ## 304 35F 19F -0.1105631716 ## 305 6M 59M -0.1103021878 ## 306 44F 35F -0.1101676292 ## 307 29F 35F -0.1099915434 ## 308 9M 6M 0.1096051894 ## 309 13M 6M -0.1090757293 ## 310 22F 3F 0.1088342247 ## 311 6M 53F 0.1086528116 ## 312 39F 54F -0.1085498936 ## 313 36F 6M -0.1082481863 ## 314 59M 52F 0.1069140411 ## 315 50F 9M -0.1067757292 ## 316 44F 19F -0.1067174047 ## 317 12M 7M 0.1057110470 ## 318 7M 36F -0.1056000477 ## 319 22F 35F -0.1055324708 ## 320 35F 48M -0.1051825029 ## 321 31M 52F 0.1051223330 ## 322 16F 53F -0.1050315260 ## 323 52F 48M -0.1045933024 ## 324 23M 6M 0.1044877514 ## 325 48M 44F -0.1042422099 ## 326 48M 22F 0.1041741827 ## 327 3F 12M -0.1033828864 ## 328 36F 41F -0.1031664332 ## 329 7M 76F -0.1027637543 ## 330 44F 16F -0.1022662218 ## 331 53F 13M -0.1017981775 ## 332 39F 31M -0.1009586816 ## 333 52F 16F -0.0999909915 ## 334 52F 19F -0.0991223662 ## 335 52F 59M 0.0980017010 ## 336 50F 3F 0.0979463930 ## 337 53F 6M -0.0974706586 ## 338 35F 54F -0.0973234554 ## 339 36F 53F -0.0971109047 ## 340 48M 23M -0.0970592907 ## 341 39F 76F 0.0962539184 ## 342 77F 50F -0.0962330765 ## 343 19F 54F -0.0958258021 ## 344 31M 9M -0.0956744002 ## 345 77F 44F -0.0955966460 ## 346 64M 6M 0.0954744641 ## 347 16F 48M -0.0954338433 ## 348 44F 6M -0.0951463316 ## 349 22F 31M 0.0950436299 ## 350 53F 44F 0.0947264722 ## 351 7M 3F -0.0944409788 ## 352 53F 31M -0.0943641324 ## 353 48M 7M 0.0941325032 ## 354 77F 29F 0.0938391836 ## 355 48M 50F 0.0937896877 ## 356 19F 13M -0.0933216145 ## 357 7M 19F -0.0932737838 ## 358 48M 54F -0.0928220013 ## 359 3F 41F -0.0927763054 ## 360 23M 53F 0.0927450275 ## 361 22F 6M -0.0927444717 ## 362 16F 19F -0.0925118350 ## 363 23M 41F 0.0924624991 ## 364 13M 77F -0.0920397422 ## 365 13M 3F -0.0919519379 ## 366 48M 41F 0.0916354244 ## 367 39F 52F -0.0912102421 ## 368 53F 9M -0.0910720472 ## 369 50F 39F 0.0910683097 ## 370 23M 29F -0.0904752563 ## 371 44F 53F -0.0903031735 ## 372 39F 41F -0.0898564179 ## 373 54F 19F -0.0895645872 ## 374 77F 23M -0.0895126545 ## 375 3F 53F -0.0893647837 ## 376 12M 16F -0.0887542455 ## 377 13M 36F 0.0881214521 ## 378 64M 13M 0.0876165983 ## 379 53F 35F -0.0868644564 ## 380 64M 48M 0.0860300810 ## 381 77F 52F -0.0858671773 ## 382 7M 59M -0.0857492160 ## 383 12M 13M 0.0856589277 ## 384 36F 54F -0.0855491423 ## 385 35F 59M 0.0854242615 ## 386 16F 59M 0.0851627967 ## 387 41F 52F -0.0848575758 ## 388 29F 52F -0.0846046137 ## 389 53F 3F -0.0844489530 ## 390 13M 35F 0.0830435698 ## 391 48M 29F -0.0824112862 ## 392 9M 7M 0.0822919126 ## 393 48M 3F -0.0821822432 ## 394 9M 23M 0.0818342522 ## 395 64M 3F -0.0818325428 ## 396 50F 35F -0.0815559474 ## 397 64M 76F -0.0810797072 ## 398 12M 35F -0.0805808065 ## 399 52F 54F -0.0805178440 ## 400 23M 77F -0.0800582189 ## 401 12M 36F -0.0799030828 ## 402 7M 13M 0.0797926096 ## 403 16F 54F -0.0795507910 ## 404 48M 39F -0.0793205234 ## 405 52F 77F 0.0792831309 ## 406 7M 9M 0.0792163220 ## 407 31M 53F 0.0784446075 ## 408 6M 22F 0.0782317301 ## 409 35F 36F -0.0778596229 ## 410 7M 31M 0.0773763832 ## 411 13M 53F 0.0769228024 ## 412 29F 76F 0.0766269153 ## 413 53F 19F -0.0765703984 ## 414 77F 19F -0.0764701738 ## 415 7M 39F -0.0764184936 ## 416 77F 31M -0.0759389938 ## 417 52F 36F -0.0758304151 ## 418 54F 3F 0.0756772044 ## 419 36F 77F 0.0752908029 ## 420 7M 44F -0.0751616131 ## 421 13M 19F 0.0751110203 ## 422 12M 76F -0.0750254375 ## 423 31M 13M 0.0746960297 ## 424 13M 23M 0.0746151364 ## 425 6M 13M -0.0734799088 ## 426 12M 41F -0.0733402670 ## 427 36F 3F -0.0727370138 ## 428 3F 16F 0.0726682114 ## 429 77F 35F -0.0720929285 ## 430 64M 59M -0.0718945389 ## 431 52F 39F 0.0706451717 ## 432 6M 23M 0.0703602332 ## 433 22F 64M -0.0701546066 ## 434 6M 41F 0.0696939055 ## 435 59M 39F -0.0695495495 ## 436 7M 77F -0.0689602961 ## 437 44F 29F 0.0688833613 ## 438 77F 16F -0.0686375735 ## 439 23M 54F 0.0683482133 ## 440 12M 39F -0.0680476891 ## 441 52F 3F 0.0680443460 ## 442 44F 41F -0.0677914247 ## 443 41F 31M -0.0676084077 ## 444 3F 64M -0.0673782681 ## 445 41F 36F 0.0673257949 ## 446 41F 35F -0.0670636919 ## 447 9M 16F -0.0669047062 ## 448 12M 3F -0.0664862358 ## 449 36F 59M 0.0664004929 ## 450 23M 48M -0.0663267570 ## 451 23M 16F 0.0661261506 ## 452 6M 35F 0.0657383088 ## 453 44F 77F -0.0653667237 ## 454 52F 13M -0.0645149687 ## 455 6M 54F 0.0638363513 ## 456 76F 31M 0.0635360417 ## 457 77F 3F 0.0634490484 ## 458 50F 23M -0.0632152563 ## 459 12M 59M -0.0631566532 ## 460 76F 7M -0.0630665694 ## 461 7M 64M 0.0629265993 ## 462 39F 3F 0.0625039001 ## 463 22F 16F -0.0624019602 ## 464 3F 52F 0.0622927755 ## 465 54F 44F -0.0621514249 ## 466 64M 19F 0.0620737943 ## 467 3F 35F 0.0616002535 ## 468 19F 59M 0.0615161021 ## 469 54F 23M -0.0609485839 ## 470 29F 53F -0.0605605439 ## 471 22F 52F -0.0603834422 ## 472 54F 36F -0.0603584682 ## 473 59M 54F 0.0601861024 ## 474 35F 31M -0.0601425204 ## 475 54F 31M -0.0599209748 ## 476 29F 50F -0.0597932418 ## 477 22F 9M -0.0595459723 ## 478 6M 36F 0.0593581045 ## 479 39F 19F -0.0589097453 ## 480 16F 77F 0.0586938058 ## 481 50F 19F -0.0579976584 ## 482 12M 77F -0.0574991095 ## 483 76F 41F 0.0571901062 ## 484 48M 52F -0.0569070839 ## 485 41F 13M -0.0565676786 ## 486 36F 13M -0.0565038562 ## 487 22F 53F -0.0553251135 ## 488 44F 39F 0.0548144257 ## 489 50F 6M -0.0547437047 ## 490 36F 23M -0.0547401781 ## 491 12M 64M 0.0546176505 ## 492 7M 53F 0.0541418969 ## 493 9M 13M 0.0534886632 ## 494 23M 19F 0.0526545276 ## 495 31M 19F 0.0525910229 ## 496 3F 36F 0.0523584382 ## 497 35F 77F 0.0522684911 ## 498 29F 19F 0.0521958689 ## 499 19F 23M -0.0521569254 ## 500 19F 3F 0.0519659325 ## 501 64M 31M -0.0518122471 ## 502 3F 6M 0.0512326649 ## 503 7M 41F -0.0509309323 ## 504 64M 41F -0.0507183423 ## 505 44F 36F -0.0498737647 ## 506 23M 64M 0.0497427257 ## 507 39F 44F 0.0497320742 ## 508 44F 59M -0.0497142877 ## 509 48M 35F 0.0496122480 ## 510 76F 3F 0.0494718876 ## 511 41F 6M -0.0494461828 ## 512 31M 76F -0.0489378809 ## 513 64M 44F -0.0481821587 ## 514 12M 22F 0.0473421826 ## 515 7M 50F -0.0473188604 ## 516 53F 16F -0.0472280192 ## 517 29F 44F -0.0459812656 ## 518 3F 22F -0.0459453888 ## 519 9M 48M 0.0457525528 ## 520 64M 50F 0.0450063170 ## 521 13M 52F 0.0447832276 ## 522 9M 35F 0.0446960269 ## 523 22F 13M 0.0430991157 ## 524 39F 29F -0.0429972256 ## 525 48M 36F -0.0429687008 ## 526 9M 52F -0.0427876279 ## 527 52F 23M -0.0426712844 ## 528 6M 19F 0.0417660820 ## 529 41F 23M 0.0414084182 ## 530 6M 3F 0.0409739133 ## 531 31M 44F -0.0407168066 ## 532 35F 3F 0.0404454196 ## 533 3F 13M -0.0399537633 ## 534 77F 59M -0.0398871760 ## 535 77F 41F -0.0397442436 ## 536 41F 16F -0.0392101656 ## 537 76F 54F -0.0390830433 ## 538 76F 12M -0.0389989206 ## 539 9M 59M -0.0386224715 ## 540 16F 3F 0.0382333918 ## 541 7M 48M -0.0352753508 ## 542 48M 13M 0.0351535645 ## 543 6M 44F 0.0348714838 ## 544 52F 44F 0.0348020140 ## 545 41F 19F -0.0341104146 ## 546 41F 48M 0.0340455424 ## 547 29F 36F 0.0338433138 ## 548 3F 50F 0.0330165324 ## 549 64M 39F -0.0325663923 ## 550 64M 54F 0.0325071388 ## 551 39F 36F -0.0323244720 ## 552 13M 48M 0.0321391474 ## 553 54F 29F 0.0317750513 ## 554 53F 23M -0.0315857824 ## 555 22F 36F 0.0306103765 ## 556 50F 13M -0.0304602565 ## 557 19F 44F -0.0302732809 ## 558 13M 31M 0.0300523162 ## 559 13M 41F 0.0295383466 ## 560 76F 39F -0.0286760629 ## 561 22F 23M 0.0274238369 ## 562 35F 44F 0.0270559916 ## 563 16F 44F 0.0261651560 ## 564 23M 36F 0.0256005715 ## 565 41F 54F 0.0255986545 ## 566 50F 36F 0.0252136809 ## 567 36F 39F 0.0249665318 ## 568 44F 3F -0.0249263273 ## 569 9M 19F 0.0248639146 ## 570 16F 13M -0.0247972265 ## 571 22F 19F 0.0247351063 ## 572 76F 50F -0.0240636514 ## 573 50F 31M -0.0230029348 ## 574 12M 54F 0.0227725327 ## 575 7M 54F -0.0226640926 ## 576 48M 16F -0.0225434718 ## 577 41F 3F -0.0224449847 ## 578 77F 36F 0.0222932448 ## 579 9M 39F -0.0217205405 ## 580 64M 77F -0.0210845372 ## 581 36F 31M -0.0208924858 ## 582 12M 48M 0.0205873217 ## 583 9M 41F 0.0201837553 ## 584 76F 29F -0.0201516767 ## 585 7M 23M 0.0198520351 ## 586 54F 59M 0.0196247263 ## 587 12M 53F 0.0195792439 ## 588 64M 36F 0.0190498142 ## 589 12M 50F 0.0188197312 ## 590 6M 52F 0.0181541073 ## 591 77F 76F 0.0177587681 ## 592 64M 23M -0.0176681371 ## 593 13M 54F -0.0175186826 ## 594 29F 41F -0.0171871018 ## 595 53F 36F 0.0169045366 ## 596 39F 59M -0.0168127135 ## 597 19F 39F 0.0167351936 ## 598 64M 52F 0.0150102160 ## 599 48M 6M -0.0147324408 ## 600 13M 44F -0.0147043255 ## 601 6M 16F -0.0144114234 ## 602 39F 23M -0.0140563613 ## 603 31M 39F -0.0138355645 ## 604 7M 6M 0.0134402637 ## 605 3F 48M 0.0133820513 ## 606 7M 22F 0.0129181328 ## 607 31M 41F 0.0128672896 ## 608 12M 31M -0.0128593810 ## 609 12M 23M 0.0128556753 ## 610 29F 77F 0.0127141710 ## 611 35F 23M -0.0125017672 ## 612 29F 23M 0.0123678131 ## 613 54F 39F -0.0116543929 ## 614 23M 39F 0.0111898869 ## 615 22F 54F 0.0111724695 ## 616 35F 39F 0.0110818691 ## 617 64M 53F -0.0110614733 ## 618 12M 6M 0.0109701901 ## 619 31M 59M -0.0104522703 ## 620 52F 31M -0.0100676040 ## 621 9M 54F 0.0094830313 ## 622 29F 3F 0.0093607010 ## 623 7M 35F -0.0092290334 ## 624 31M 64M 0.0088905242 ## 625 16F 39F -0.0087855916 ## 626 50F 16F -0.0085539542 ## 627 50F 48M -0.0085355208 ## 628 59M 6M 0.0078735859 ## 629 76F 64M -0.0077920687 ## 630 36F 44F 0.0075353405 ## 631 31M 16F 0.0067545939 ## 632 39F 53F -0.0061843433 ## 633 53F 48M -0.0061656721 ## 634 29F 16F -0.0061502518 ## 635 23M 50F 0.0059206014 ## 636 50F 54F 0.0054048597 ## 637 31M 23M 0.0048394490 ## 638 31M 77F -0.0047653051 ## 639 77F 53F 0.0044374828 ## 640 16F 23M -0.0042830154 ## 641 19F 77F 0.0040145572 ## 642 3F 23M -0.0040023851 ## 643 23M 31M 0.0038292279 ## 644 23M 52F -0.0036669821 ## 645 48M 19F -0.0031344337 ## 646 64M 16F 0.0024176264 ## 647 6M 48M 0.0017065403 ## 648 44F 76F -0.0016070404 ## 649 22F 48M -0.0010679395 ## 650 29F 48M 0.0006227683