Run1_analysis
ERM
20230118
Last updated: 2023-02-10
Checks: 7 0
Knit directory: Cardiotoxicity/
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| File | Version | Author | Date | Message |
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| Rmd | 40fb340 | reneeisnowhere | 2023-02-10 | updates for the week |
| Rmd | accc241 | reneeisnowhere | 2023-02-10 | updates for the week |
| Rmd | 1fc5c19 | reneeisnowhere | 2023-02-09 | Git update |
Hello! I am first loading all the beautiful libraries I will need.
library(Biobase)
library(edgeR)
library(limma)
library(RColorBrewer)
library(mixOmics)
library(VennDiagram)
library(HTSFilter)
library(ggplot2)
library(gridExtra)
library(reshape2)
library(devtools)
library(AnnotationHub)
library(tidyverse)
library(scales)
library(biomaRt)
library(Homo.sapiens)
library(cowplot)
library(ggrepel)
library(corrplot)
library(Hmisc)The next step is to load all the data I will be using. Currently, I am not posting the raw data, but I will release in the future.
This is how I retrieved the gene symbols.
###now we add genenames to the geneid###
geneid <- rownames(mymatrix) ### pulls the names we have in the counts file
genes <- select(Homo.sapiens, keys=geneid, columns=c("SYMBOL"),
keytype="ENTREZID")
genes <- genes[!duplicated(genes$ENTREZID),]
mymatrix$genes <- genesFiltering out low count genes
Filtering the genes that are lowly expressed using several methods.
First method, removing only those rows with zero counts across all samples.
#
# old.par <- par(mar = c(0, 0, 0, 0))
# par(old.par)
# boxplot(data =RNAseqreads, total~Sample, main = "Boxplots of total reads",xaxt = "n", xlab= "")
# x_axis_labels(labels = samplenames, every_nth = 1, adj=1, srt =90, cex =0.4)
# ggplot(RNAseqreads, x = Sample, y = total)+
# geom_boxplot()
table(rowSums(mymatrix$counts==0)==72)
FALSE TRUE
24931 3464 This filtering would leave 24931 genes and remove 3464, That is too many leftover genes!
So now to try something a little more stringent using the built in function from the edgeR package.
keep <- filterByExpr.DGEList(mymatrix, group = group)
filter_test <- mymatrix[keep, , keep.lib.sizes=FALSE]
dim(filter_test)[1] 14448 72This method effectively uses a cutoff off that leaves 14448 genes.
The cutoff is determined by keeping genes that have a count-per-million
(CPM) above 10, (the default minimum set) in 6 samples. A set is
determined using the design matrix.
For my design, I grouped my 72 samples into sets of 6, one set includes
each individual + a specific treatment + a specific time.
The beginning cutoff-standard in our lab is to start by using the rowMeans >0 cutoff on the log10 of cpm.
cpm <- cpm(mymatrix)
lcpm <- cpm(mymatrix, log=TRUE) ### for determining the basic cutoffs
dim(lcpm)[1] 28395 72L <- mean(mymatrix$samples$lib.size) * 1e-6
M <- median(mymatrix$samples$lib.size) * 1e-6
c(L, M)[1] 4.679061 4.494188filcpm_matrix <- subset(lcpm, (rowMeans(lcpm)>0))
dim(filcpm_matrix)[1] 14823 72##method 2 with rowMeans
row_means <- rowMeans(lcpm)
x <- mymatrix[row_means > 0,]
dim(x)[1] 14823 72write.csv(x$counts, "data/norm_counts.csv")Both of the above methods leave 14823 genes from 28,395. I prefer the second method, which keeps the DGEList format of the data.
now I will produce the RIN x sample plots:###
Principal Component Analysis
PCA was done using code adopted from J. Blischak.
### Daunorubicin 
### Doxorubicin 
### Epirubicin 
### Mitoxantrone 
### Trastuzumab 
### Vehicle 
PCA of all 72 samples
Warning: `qplot()` was deprecated in ggplot2 3.4.0.
## Variance contribution from treatment, extraction time, or individual
on PC1 and PC2
Differential Expression
mm2 <- model.matrix(~0 + group1)
##made the matrix model using the interaction between Treatment and Time
colnames(mm2) <- c("A3", "X3", "E3","M3","T3", "V3","A24", "X24", "E24","M24","T24", "V24")
y2 <- voom(x, mm2)
corfit2 <- duplicateCorrelation(y2, mm2, block = indv)
v2 <- voom(x, mm2, block = indv, correlation = corfit2$consensus)
fit2 <- lmFit(v2, mm2, block = indv, correlation = corfit2$consensus)
vfit2 <- lmFit(y2, mm2)
vfit2<- contrasts.fit(vfit2, contrasts=cm2)
efit2 <- eBayes(vfit2)
V.DA.top= topTable(efit2, coef=1, adjust="BH", number=Inf, sort.by="p")
### sorting all top expressed genes for the Vehicle and Daunorubicin 3 hour treatments
sigVDA3 = V.DA.top[V.DA.top$adj.P.Val < .1 , ]
### this helped pull only those files that were at an adjusted p value of less than 0.1
### This p-value was used as the beginning examination of the data, considering I will run multiple runs of this RNA seq library.This is the example code I used to process my data. I used two model matrix initially, one set up was /~0 +drug +time and the second was /~0+group1, then blocking by individual. That is why you see the number 2 in the code above.
#DEG summary
Importance of components:
PC1 PC2 PC3 PC4 PC5 PC6
Standard deviation 60.2067 44.5108 32.3037 30.98489 27.1431 24.07762
Proportion of Variance 0.2445 0.1337 0.0704 0.06477 0.0497 0.03911
Cumulative Proportion 0.2445 0.3782 0.4486 0.51337 0.5631 0.60218
PC7 PC8 PC9 PC10 PC11 PC12
Standard deviation 23.26775 21.37712 20.13091 18.19509 17.63059 16.30004
Proportion of Variance 0.03652 0.03083 0.02734 0.02233 0.02097 0.01792
Cumulative Proportion 0.63870 0.66953 0.69687 0.71921 0.74018 0.75810
PC13 PC14 PC15 PC16 PC17 PC18
Standard deviation 15.87695 14.24554 13.51806 12.67177 11.84085 11.44481
Proportion of Variance 0.01701 0.01369 0.01233 0.01083 0.00946 0.00884
Cumulative Proportion 0.77511 0.78880 0.80113 0.81196 0.82142 0.83025
PC19 PC20 PC21 PC22 PC23 PC24 PC25
Standard deviation 11.08484 10.4711 9.86347 9.53287 9.25138 9.06027 8.70778
Proportion of Variance 0.00829 0.0074 0.00656 0.00613 0.00577 0.00554 0.00512
Cumulative Proportion 0.83854 0.8459 0.85250 0.85863 0.86441 0.86995 0.87506
PC26 PC27 PC28 PC29 PC30 PC31 PC32
Standard deviation 8.40220 8.26732 8.04037 7.85926 7.76676 7.67958 7.48930
Proportion of Variance 0.00476 0.00461 0.00436 0.00417 0.00407 0.00398 0.00378
Cumulative Proportion 0.87982 0.88444 0.88880 0.89296 0.89703 0.90101 0.90480
PC33 PC34 PC35 PC36 PC37 PC38 PC39
Standard deviation 7.34178 7.28566 7.22861 7.1043 6.99972 6.94542 6.83650
Proportion of Variance 0.00364 0.00358 0.00353 0.0034 0.00331 0.00325 0.00315
Cumulative Proportion 0.90843 0.91201 0.91554 0.9189 0.92225 0.92550 0.92866
PC40 PC41 PC42 PC43 PC44 PC45 PC46
Standard deviation 6.75717 6.73038 6.57835 6.54307 6.53123 6.4395 6.37432
Proportion of Variance 0.00308 0.00306 0.00292 0.00289 0.00288 0.0028 0.00274
Cumulative Proportion 0.93174 0.93479 0.93771 0.94060 0.94348 0.9463 0.94902
PC47 PC48 PC49 PC50 PC51 PC52 PC53
Standard deviation 6.34772 6.23190 6.17748 6.0816 6.01946 5.9644 5.89730
Proportion of Variance 0.00272 0.00262 0.00257 0.0025 0.00244 0.0024 0.00235
Cumulative Proportion 0.95173 0.95435 0.95693 0.9594 0.96187 0.9643 0.96661
PC54 PC55 PC56 PC57 PC58 PC59 PC60
Standard deviation 5.8378 5.80173 5.72099 5.69367 5.65008 5.60128 5.47568
Proportion of Variance 0.0023 0.00227 0.00221 0.00219 0.00215 0.00212 0.00202
Cumulative Proportion 0.9689 0.97118 0.97339 0.97558 0.97773 0.97985 0.98187
PC61 PC62 PC63 PC64 PC65 PC66 PC67
Standard deviation 5.46660 5.38710 5.31872 5.25710 5.11760 5.0166 4.83245
Proportion of Variance 0.00202 0.00196 0.00191 0.00186 0.00177 0.0017 0.00158
Cumulative Proportion 0.98389 0.98585 0.98776 0.98962 0.99139 0.9931 0.99466
PC68 PC69 PC70 PC71 PC72
Standard deviation 4.73475 4.57831 4.51242 3.92680 4.923e-14
Proportion of Variance 0.00151 0.00141 0.00137 0.00104 0.000e+00
Cumulative Proportion 0.99617 0.99759 0.99896 1.00000 1.000e+00 V.DA V.DX V.EP V.MT V.TR V.DA24 V.DX24 V.EP24 V.MT24 V.TR24
Down 63 3 11 13 0 3342 3013 2871 320 0
NotSig 14456 14814 14714 14780 14823 8279 8993 9034 13970 14823
Up 304 6 98 30 0 3202 2817 2918 533 0Graphing DE genes
I then created a counts table for each set of genes. Luckily, the counts are stored in the y2 object, which is an EList class object. I can ‘simplify’ this process because I kept the DEGList format initially. I first made an object called ‘countstotal’ from the EList y2. For ggploting later, I subsetted ‘countstotal’ by treatments.
countstotal <- y2$E
colnames(countstotal) <- smlabel
boxplot(countstotal, xaxt = "n", xlab="")
Da3counts <- as.data.frame(as.table(countstotal[,c(1,6,13,18,25,30,37,42,49,54,61,66)]))
x_axis_labels(labels = label, every_nth = 1, adj=1, srt =90, cex =0.4)
library(cowplot)
Volcano Plots
Da.1.3h Do.1.3h Ep.1.3h Mi.1.3h Tr.1.3h Ve.1.3h Da.1.24h
Da.1.3h 1.0000000 0.9750009 0.9819187 0.9750397 0.9670114 0.9672631 0.8798716
Do.1.3h 0.9750009 1.0000000 0.9812729 0.9805745 0.9773620 0.9799603 0.8856000
Ep.1.3h 0.9819187 0.9812729 1.0000000 0.9817512 0.9759275 0.9745966 0.8830084
Mi.1.3h 0.9750397 0.9805745 0.9817512 1.0000000 0.9776286 0.9772605 0.8843686
Tr.1.3h 0.9670114 0.9773620 0.9759275 0.9776286 1.0000000 0.9781408 0.8783519
Ve.1.3h 0.9672631 0.9799603 0.9745966 0.9772605 0.9781408 1.0000000 0.8786708
Da.1.24h 0.8798716 0.8856000 0.8830084 0.8843686 0.8783519 0.8786708 1.0000000
Do.1.24h 0.8342768 0.8412818 0.8364218 0.8388230 0.8327759 0.8337297 0.9059125
Ep.1.24h 0.8755706 0.8819487 0.8820155 0.8816722 0.8760134 0.8739264 0.9716528
Mi.1.24h 0.9417158 0.9537869 0.9489981 0.9537620 0.9541162 0.9522151 0.9231684
Tr.1.24h 0.9634662 0.9736999 0.9709712 0.9743358 0.9768900 0.9734314 0.8794038
Ve.1.24h 0.9624472 0.9737102 0.9684832 0.9715686 0.9748601 0.9739423 0.8773858
Da.2.3h 0.9102090 0.8986492 0.9039555 0.8989770 0.8907540 0.8922487 0.7974989
Do.2.3h 0.9027292 0.9029928 0.8999590 0.9000381 0.8963980 0.9008944 0.7999029
Ep.2.3h 0.9142383 0.9086090 0.9120992 0.9089450 0.9001160 0.9030954 0.8076164
Mi.2.3h 0.9119691 0.9054995 0.9089298 0.9085347 0.9006935 0.9024926 0.8077486
Tr.2.3h 0.8979414 0.8957848 0.8968039 0.8961954 0.8921060 0.8957863 0.7894072
Ve.2.3h 0.9030785 0.9056109 0.9020535 0.9046819 0.9029202 0.9067807 0.7952351
Da.2.24h 0.8541808 0.8519938 0.8551480 0.8537790 0.8440593 0.8448362 0.9233532
Do.2.24h 0.8333943 0.8324354 0.8328216 0.8327149 0.8226544 0.8252168 0.9058254
Ep.2.24h 0.8410323 0.8292228 0.8363069 0.8291917 0.8155801 0.8177729 0.8275214
Mi.2.24h 0.9049226 0.9007429 0.9027168 0.9036491 0.8993008 0.9001345 0.8296148
Tr.2.24h 0.9005961 0.8951984 0.8988347 0.8968318 0.8941245 0.8946371 0.7897035
Ve.2.24h 0.8948423 0.8877475 0.8914513 0.8891347 0.8869126 0.8886604 0.7785197
Da.3.3h 0.9319512 0.9225026 0.9241631 0.9209965 0.9132814 0.9144588 0.8300117
Do.3.3h 0.9310647 0.9352041 0.9326231 0.9332567 0.9289201 0.9308794 0.8334422
Ep.3.3h 0.9404014 0.9280220 0.9355110 0.9278036 0.9195856 0.9200323 0.8274232
Mi.3.3h 0.9301179 0.9205185 0.9250091 0.9222625 0.9124563 0.9141138 0.8196522
Tr.3.3h 0.9310105 0.9333273 0.9336036 0.9329442 0.9308929 0.9325504 0.8226232
Ve.3.3h 0.9281711 0.9229720 0.9254536 0.9235198 0.9210853 0.9205402 0.8135663
Da.3.24h 0.8739904 0.8701387 0.8750195 0.8722760 0.8627761 0.8636353 0.9301956
Do.3.24h 0.8616160 0.8600436 0.8600780 0.8586000 0.8506553 0.8541401 0.9194606
Ep.3.24h 0.8567431 0.8552229 0.8592945 0.8563004 0.8472015 0.8476827 0.9291292
Mi.3.24h 0.9245509 0.9230034 0.9251028 0.9264555 0.9211812 0.9214072 0.8631471
Tr.3.24h 0.9269675 0.9281541 0.9273675 0.9273672 0.9270419 0.9288847 0.8156204
Ve.3.24h 0.9142432 0.9148495 0.9145529 0.9134950 0.9122088 0.9126111 0.7978031
Da.4.3h 0.9652104 0.9615603 0.9646649 0.9606712 0.9533052 0.9546199 0.8631918
Do.4.3h 0.9643503 0.9649784 0.9650904 0.9625998 0.9578774 0.9604689 0.8592083
Ep.4.3h 0.9653609 0.9641171 0.9664620 0.9625394 0.9572996 0.9576933 0.8625445
Mi.4.3h 0.9609100 0.9625702 0.9629950 0.9633040 0.9585662 0.9601196 0.8637672
Tr.4.3h 0.9588647 0.9637644 0.9631052 0.9623286 0.9620751 0.9630988 0.8522685
Ve.4.3h 0.9557574 0.9625032 0.9611523 0.9610639 0.9610084 0.9621090 0.8553049
Da.4.24h 0.8888555 0.8886834 0.8923650 0.8885716 0.8787536 0.8805659 0.9583502
Do.4.24h 0.8898632 0.8927680 0.8953969 0.8927534 0.8829611 0.8860426 0.9553138
Ep.4.24h 0.8907498 0.8884543 0.8953452 0.8898975 0.8790457 0.8816249 0.9509203
Mi.4.24h 0.9470074 0.9530740 0.9526112 0.9539310 0.9500433 0.9512113 0.8928881
Tr.4.24h 0.9581093 0.9624521 0.9632557 0.9629274 0.9635518 0.9612795 0.8546325
Ve.4.24h 0.9526905 0.9599575 0.9566278 0.9589479 0.9596461 0.9592674 0.8559965
Da.5.3h 0.9251855 0.9169488 0.9212022 0.9187003 0.9090587 0.9084347 0.8455172
Do.5.3h 0.9256423 0.9277729 0.9294429 0.9295165 0.9238239 0.9240714 0.8470377
Ep.5.3h 0.9235453 0.9148518 0.9227641 0.9191107 0.9099688 0.9094219 0.8340229
Mi.5.3h 0.9235694 0.9178789 0.9218295 0.9220799 0.9114808 0.9128291 0.8355114
Tr.5.3h 0.9112021 0.9041599 0.9072484 0.9062446 0.9034204 0.9030968 0.8138187
Ve.5.3h 0.9068814 0.9033397 0.9043493 0.9058188 0.9037313 0.9047044 0.8162827
Da.5.24h 0.8601425 0.8555858 0.8564509 0.8572256 0.8515660 0.8524342 0.9003719
Do.5.24h 0.8727576 0.8669491 0.8720142 0.8692469 0.8617188 0.8623623 0.9147373
Ep.5.24h 0.8823364 0.8863643 0.8860914 0.8880706 0.8810528 0.8823772 0.9084563
Mi.5.24h 0.9083892 0.9125159 0.9143077 0.9163623 0.9113003 0.9098228 0.8751595
Tr.5.24h 0.9096053 0.9137166 0.9135395 0.9152429 0.9142400 0.9104863 0.8164823
Ve.5.24h 0.9108663 0.9199656 0.9152889 0.9190236 0.9193266 0.9187054 0.8276510
Da.6.3h 0.9528214 0.9451679 0.9509857 0.9453242 0.9380025 0.9388753 0.8453272
Do.6.3h 0.9444414 0.9436710 0.9439061 0.9421237 0.9395025 0.9400808 0.8360335
Ep.6.3h 0.9453039 0.9472987 0.9470185 0.9452692 0.9414110 0.9421992 0.8399094
Mi.6.3h 0.9463978 0.9439405 0.9450420 0.9451257 0.9388050 0.9406922 0.8429570
Tr.6.3h 0.9422835 0.9405363 0.9414746 0.9400737 0.9391404 0.9386595 0.8276872
Ve.6.3h 0.9440705 0.9423336 0.9424742 0.9427719 0.9417382 0.9419609 0.8306427
Da.6.24h 0.8925134 0.8903097 0.8933761 0.8916997 0.8841079 0.8844630 0.9367602
Do.6.24h 0.9159101 0.9158751 0.9178040 0.9154038 0.9086894 0.9125617 0.8969984
Ep.6.24h 0.9199926 0.9166706 0.9184108 0.9168236 0.9097779 0.9129955 0.9008743
Mi.6.24h 0.9342154 0.9321716 0.9322613 0.9326039 0.9304202 0.9314719 0.8642544
Tr.6.24h 0.9252461 0.9320758 0.9276547 0.9277794 0.9288798 0.9279800 0.8218928
Ve.6.24h 0.9402979 0.9375057 0.9379633 0.9366205 0.9352638 0.9364364 0.8276129
Do.1.24h Ep.1.24h Mi.1.24h Tr.1.24h Ve.1.24h Da.2.3h Do.2.3h
Da.1.3h 0.8342768 0.8755706 0.9417158 0.9634662 0.9624472 0.9102090 0.9027292
Do.1.3h 0.8412818 0.8819487 0.9537869 0.9736999 0.9737102 0.8986492 0.9029928
Ep.1.3h 0.8364218 0.8820155 0.9489981 0.9709712 0.9684832 0.9039555 0.8999590
Mi.1.3h 0.8388230 0.8816722 0.9537620 0.9743358 0.9715686 0.8989770 0.9000381
Tr.1.3h 0.8327759 0.8760134 0.9541162 0.9768900 0.9748601 0.8907540 0.8963980
Ve.1.3h 0.8337297 0.8739264 0.9522151 0.9734314 0.9739423 0.8922487 0.9008944
Da.1.24h 0.9059125 0.9716528 0.9231684 0.8794038 0.8773858 0.7974989 0.7999029
Do.1.24h 1.0000000 0.9049843 0.8726433 0.8337027 0.8339953 0.7661882 0.7657836
Ep.1.24h 0.9049843 1.0000000 0.9220055 0.8794611 0.8736893 0.7941135 0.7944286
Mi.1.24h 0.8726433 0.9220055 1.0000000 0.9559709 0.9536391 0.8530893 0.8597301
Tr.1.24h 0.8337027 0.8794611 0.9559709 1.0000000 0.9796735 0.8877993 0.8913143
Ve.1.24h 0.8339953 0.8736893 0.9536391 0.9796735 1.0000000 0.8871858 0.8908963
Da.2.3h 0.7661882 0.7941135 0.8530893 0.8877993 0.8871858 1.0000000 0.9705899
Do.2.3h 0.7657836 0.7944286 0.8597301 0.8913143 0.8908963 0.9705899 1.0000000
Ep.2.3h 0.7729539 0.8038963 0.8646545 0.8970599 0.8952264 0.9724149 0.9750952
Mi.2.3h 0.7749316 0.8050560 0.8669921 0.8982853 0.8968544 0.9732781 0.9762712
Tr.2.3h 0.7565248 0.7855643 0.8524656 0.8867408 0.8849494 0.9664444 0.9769611
Ve.2.3h 0.7622954 0.7910182 0.8621814 0.8991441 0.8983309 0.9661951 0.9784520
Da.2.24h 0.8618217 0.9255000 0.8727373 0.8409438 0.8376063 0.8598483 0.8640293
Do.2.24h 0.8475816 0.9084703 0.8504986 0.8212120 0.8196576 0.8466331 0.8512392
Ep.2.24h 0.7799137 0.8240382 0.8111449 0.8087849 0.8084308 0.8764981 0.8702428
Mi.2.24h 0.7955292 0.8310525 0.8979756 0.8982202 0.8937949 0.9445665 0.9488171
Tr.2.24h 0.7569038 0.7896055 0.8584457 0.8942769 0.8902877 0.9640091 0.9664680
Ve.2.24h 0.7484706 0.7770379 0.8473999 0.8843395 0.8824575 0.9636159 0.9681654
Da.3.3h 0.7915342 0.8246744 0.8855827 0.9134100 0.9120210 0.9489932 0.9468872
Do.3.3h 0.7974397 0.8303429 0.8975292 0.9292880 0.9290867 0.9447509 0.9486250
Ep.3.3h 0.7914791 0.8249328 0.8875707 0.9183543 0.9157540 0.9496848 0.9436578
Mi.3.3h 0.7840216 0.8164126 0.8810544 0.9096131 0.9078395 0.9472050 0.9468563
Tr.3.3h 0.7891081 0.8230688 0.8964122 0.9302259 0.9292053 0.9432514 0.9493347
Ve.3.3h 0.7796093 0.8120775 0.8854542 0.9202094 0.9169697 0.9443037 0.9463338
Da.3.24h 0.8776849 0.9362267 0.9001429 0.8614155 0.8582084 0.8454752 0.8445506
Do.3.24h 0.8708386 0.9262910 0.8832987 0.8471508 0.8470185 0.8456526 0.8488116
Ep.3.24h 0.8742969 0.9412060 0.8815531 0.8460977 0.8418408 0.8334370 0.8344009
Mi.3.24h 0.8270067 0.8658812 0.9310940 0.9213687 0.9183113 0.9185237 0.9217908
Tr.3.24h 0.7816226 0.8144762 0.8933662 0.9286039 0.9280436 0.9436753 0.9476406
Ve.3.24h 0.7641135 0.7954595 0.8683180 0.9120092 0.9107172 0.9448795 0.9456026
Da.4.3h 0.8202735 0.8554897 0.9245745 0.9507693 0.9510543 0.9169493 0.9133161
Do.4.3h 0.8160134 0.8521486 0.9265330 0.9531080 0.9538980 0.9179944 0.9213886
Ep.4.3h 0.8201682 0.8560043 0.9271063 0.9534200 0.9521434 0.9189952 0.9194670
Mi.4.3h 0.8192649 0.8574806 0.9307158 0.9551968 0.9542131 0.9158224 0.9210439
Tr.4.3h 0.8101134 0.8479038 0.9281268 0.9595347 0.9581831 0.9128340 0.9203900
Ve.4.3h 0.8124077 0.8503181 0.9301602 0.9595112 0.9579539 0.9082988 0.9161504
Da.4.24h 0.8943707 0.9560115 0.9166980 0.8755686 0.8727480 0.8291460 0.8318428
Do.4.24h 0.8970888 0.9593159 0.9213897 0.8815145 0.8791922 0.8244627 0.8289532
Ep.4.24h 0.8907220 0.9551319 0.9142972 0.8738444 0.8722747 0.8251954 0.8265801
Mi.4.24h 0.8481638 0.8924841 0.9642623 0.9504120 0.9487939 0.8848970 0.8910710
Tr.4.24h 0.8117346 0.8513759 0.9319313 0.9667471 0.9632483 0.9129507 0.9158161
Ve.4.24h 0.8138382 0.8512190 0.9315674 0.9632960 0.9632266 0.9055668 0.9100031
Da.5.3h 0.8042730 0.8423694 0.8915297 0.9108781 0.9061182 0.9346167 0.9295403
Do.5.3h 0.8093287 0.8479751 0.9033772 0.9250837 0.9212384 0.9338593 0.9362750
Ep.5.3h 0.7962217 0.8339930 0.8890403 0.9106477 0.9043326 0.9341510 0.9331700
Mi.5.3h 0.7974413 0.8320092 0.8924288 0.9104044 0.9062050 0.9367428 0.9365243
Tr.5.3h 0.7828324 0.8147371 0.8793167 0.9062162 0.9015712 0.9310612 0.9315397
Ve.5.3h 0.7852353 0.8155383 0.8816718 0.9058273 0.9027116 0.9204924 0.9247871
Da.5.24h 0.8584900 0.9038109 0.8831014 0.8522071 0.8496179 0.8497151 0.8520675
Do.5.24h 0.8682346 0.9218658 0.8958821 0.8608169 0.8577698 0.8590150 0.8588649
Ep.5.24h 0.8644601 0.9180848 0.9160977 0.8829341 0.8788683 0.8641728 0.8688877
Mi.5.24h 0.8342728 0.8796271 0.9308282 0.9125070 0.9061909 0.8971613 0.9030860
Tr.5.24h 0.7804022 0.8180976 0.8832136 0.9191880 0.9120229 0.9323852 0.9328277
Ve.5.24h 0.7910340 0.8281473 0.8908573 0.9239764 0.9187413 0.9295813 0.9344744
Da.6.3h 0.8033875 0.8398160 0.9045948 0.9332255 0.9305668 0.9425640 0.9408797
Do.6.3h 0.7959925 0.8314021 0.9041340 0.9371179 0.9345140 0.9349955 0.9387362
Ep.6.3h 0.8000445 0.8357717 0.9059984 0.9360575 0.9361974 0.9328630 0.9360773
Mi.6.3h 0.8018434 0.8367056 0.9082505 0.9346481 0.9334633 0.9337609 0.9377295
Tr.6.3h 0.7883463 0.8229473 0.9017494 0.9370284 0.9344558 0.9326991 0.9369869
Ve.6.3h 0.7914024 0.8248255 0.9047126 0.9389949 0.9376692 0.9306937 0.9363276
Da.6.24h 0.8797782 0.9368384 0.9153958 0.8807883 0.8767962 0.8554048 0.8591245
Do.6.24h 0.8543680 0.9004142 0.9231196 0.9024349 0.9008391 0.8837143 0.8902252
Ep.6.24h 0.8544273 0.9003598 0.9269639 0.9050811 0.9041244 0.8861732 0.8911879
Mi.6.24h 0.8235460 0.8608726 0.9345829 0.9283707 0.9250366 0.9101360 0.9163904
Tr.6.24h 0.7843357 0.8190736 0.8940943 0.9306204 0.9282138 0.9245144 0.9266815
Ve.6.24h 0.7902507 0.8218320 0.9011529 0.9348534 0.9343277 0.9334456 0.9365340
Ep.2.3h Mi.2.3h Tr.2.3h Ve.2.3h Da.2.24h Do.2.24h Ep.2.24h
Da.1.3h 0.9142383 0.9119691 0.8979414 0.9030785 0.8541808 0.8333943 0.8410323
Do.1.3h 0.9086090 0.9054995 0.8957848 0.9056109 0.8519938 0.8324354 0.8292228
Ep.1.3h 0.9120992 0.9089298 0.8968039 0.9020535 0.8551480 0.8328216 0.8363069
Mi.1.3h 0.9089450 0.9085347 0.8961954 0.9046819 0.8537790 0.8327149 0.8291917
Tr.1.3h 0.9001160 0.9006935 0.8921060 0.9029202 0.8440593 0.8226544 0.8155801
Ve.1.3h 0.9030954 0.9024926 0.8957863 0.9067807 0.8448362 0.8252168 0.8177729
Da.1.24h 0.8076164 0.8077486 0.7894072 0.7952351 0.9233532 0.9058254 0.8275214
Do.1.24h 0.7729539 0.7749316 0.7565248 0.7622954 0.8618217 0.8475816 0.7799137
Ep.1.24h 0.8038963 0.8050560 0.7855643 0.7910182 0.9255000 0.9084703 0.8240382
Mi.1.24h 0.8646545 0.8669921 0.8524656 0.8621814 0.8727373 0.8504986 0.8111449
Tr.1.24h 0.8970599 0.8982853 0.8867408 0.8991441 0.8409438 0.8212120 0.8087849
Ve.1.24h 0.8952264 0.8968544 0.8849494 0.8983309 0.8376063 0.8196576 0.8084308
Da.2.3h 0.9724149 0.9732781 0.9664444 0.9661951 0.8598483 0.8466331 0.8764981
Do.2.3h 0.9750952 0.9762712 0.9769611 0.9784520 0.8640293 0.8512392 0.8702428
Ep.2.3h 1.0000000 0.9743014 0.9719302 0.9708555 0.8671117 0.8522774 0.8755643
Mi.2.3h 0.9743014 1.0000000 0.9739892 0.9718603 0.8692054 0.8565722 0.8766766
Tr.2.3h 0.9719302 0.9739892 1.0000000 0.9761218 0.8592362 0.8436683 0.8631002
Ve.2.3h 0.9708555 0.9718603 0.9761218 1.0000000 0.8585616 0.8447287 0.8617919
Da.2.24h 0.8671117 0.8692054 0.8592362 0.8585616 1.0000000 0.9663841 0.8863551
Do.2.24h 0.8522774 0.8565722 0.8436683 0.8447287 0.9663841 1.0000000 0.8954128
Ep.2.24h 0.8755643 0.8766766 0.8631002 0.8617919 0.8863551 0.8954128 1.0000000
Mi.2.24h 0.9466472 0.9494473 0.9492839 0.9541295 0.8894501 0.8698542 0.8575363
Tr.2.24h 0.9641563 0.9669042 0.9673050 0.9713199 0.8545253 0.8376339 0.8541634
Ve.2.24h 0.9606920 0.9680169 0.9694273 0.9696732 0.8502389 0.8306731 0.8548037
Da.3.3h 0.9516667 0.9506865 0.9389602 0.9421481 0.8603349 0.8463004 0.8656057
Do.3.3h 0.9494577 0.9472499 0.9402013 0.9519940 0.8587276 0.8469090 0.8522310
Ep.3.3h 0.9500770 0.9508407 0.9394384 0.9418908 0.8571467 0.8388784 0.8588752
Mi.3.3h 0.9511857 0.9518358 0.9425333 0.9457019 0.8559729 0.8367134 0.8575115
Tr.3.3h 0.9492438 0.9506362 0.9461725 0.9562970 0.8519013 0.8397426 0.8451512
Ve.3.3h 0.9481883 0.9486133 0.9446488 0.9511823 0.8482484 0.8284335 0.8436845
Da.3.24h 0.8505629 0.8537097 0.8397213 0.8428792 0.9447768 0.9226031 0.8447778
Do.3.24h 0.8487769 0.8526038 0.8422465 0.8463828 0.9455021 0.9299424 0.8478318
Ep.3.24h 0.8425422 0.8429572 0.8308222 0.8315071 0.9537477 0.9392398 0.8469197
Mi.3.24h 0.9231606 0.9263459 0.9195926 0.9256289 0.8891174 0.8677430 0.8469894
Tr.3.24h 0.9440162 0.9467760 0.9446293 0.9563489 0.8465755 0.8327570 0.8399806
Ve.3.24h 0.9441703 0.9441494 0.9438895 0.9541408 0.8355915 0.8219614 0.8375679
Da.4.3h 0.9230977 0.9187399 0.9054593 0.9129207 0.8515114 0.8338594 0.8494456
Do.4.3h 0.9268824 0.9226853 0.9145164 0.9227238 0.8510367 0.8313855 0.8404159
Ep.4.3h 0.9260613 0.9232669 0.9128256 0.9201298 0.8543849 0.8338779 0.8459510
Mi.4.3h 0.9262142 0.9244977 0.9161758 0.9233260 0.8573056 0.8365004 0.8420831
Tr.4.3h 0.9249273 0.9216335 0.9171252 0.9258615 0.8447307 0.8251959 0.8297657
Ve.4.3h 0.9208712 0.9177452 0.9123657 0.9216124 0.8452954 0.8258670 0.8276904
Da.4.24h 0.8416656 0.8376113 0.8260662 0.8270021 0.9410446 0.9205201 0.8484133
Do.4.24h 0.8385593 0.8359666 0.8219882 0.8248664 0.9335391 0.9168737 0.8383863
Ep.4.24h 0.8371284 0.8335156 0.8233201 0.8234413 0.9362517 0.9121768 0.8453572
Mi.4.24h 0.8963637 0.8954169 0.8875448 0.8947390 0.8725712 0.8512825 0.8261426
Tr.4.24h 0.9224788 0.9203649 0.9139382 0.9231734 0.8436131 0.8238775 0.8246577
Ve.4.24h 0.9141658 0.9133365 0.9061954 0.9169280 0.8410378 0.8219384 0.8196852
Da.5.3h 0.9376817 0.9395908 0.9221783 0.9274810 0.8705591 0.8550083 0.8697579
Do.5.3h 0.9406960 0.9420930 0.9296762 0.9397909 0.8682807 0.8547143 0.8551251
Ep.5.3h 0.9432972 0.9423218 0.9312828 0.9310277 0.8650496 0.8461416 0.8544332
Mi.5.3h 0.9432117 0.9452434 0.9336895 0.9352239 0.8634318 0.8453640 0.8582018
Tr.5.3h 0.9299433 0.9428093 0.9277644 0.9327352 0.8452076 0.8310601 0.8343009
Ve.5.3h 0.9236402 0.9366607 0.9218454 0.9264562 0.8410655 0.8312172 0.8303590
Da.5.24h 0.8533626 0.8682366 0.8477624 0.8450885 0.9205625 0.9068049 0.8378232
Do.5.24h 0.8620280 0.8698806 0.8543580 0.8562606 0.9366743 0.9153713 0.8436964
Ep.5.24h 0.8738472 0.8761809 0.8628307 0.8681258 0.9190544 0.9004744 0.8360639
Mi.5.24h 0.9084571 0.9090897 0.9015189 0.9065428 0.8924338 0.8721566 0.8404452
Tr.5.24h 0.9361241 0.9368132 0.9315384 0.9435850 0.8451503 0.8295416 0.8357042
Ve.5.24h 0.9340655 0.9352518 0.9300916 0.9437356 0.8512957 0.8377178 0.8386796
Da.6.3h 0.9448931 0.9444501 0.9373739 0.9398553 0.8675045 0.8469662 0.8671174
Do.6.3h 0.9374478 0.9390938 0.9337673 0.9437370 0.8535812 0.8334325 0.8442316
Ep.6.3h 0.9360645 0.9366685 0.9297198 0.9404717 0.8548138 0.8366993 0.8465603
Mi.6.3h 0.9395844 0.9408465 0.9343475 0.9385464 0.8601540 0.8391274 0.8519810
Tr.6.3h 0.9366111 0.9375374 0.9344040 0.9424575 0.8467084 0.8257305 0.8371828
Ve.6.3h 0.9361856 0.9379729 0.9342082 0.9408513 0.8470566 0.8256720 0.8345320
Da.6.24h 0.8637816 0.8647905 0.8559304 0.8557232 0.9422365 0.9196746 0.8500187
Do.6.24h 0.8919741 0.8909499 0.8871698 0.8906804 0.9076868 0.8827186 0.8412057
Ep.6.24h 0.8938287 0.8927932 0.8879388 0.8888703 0.9082624 0.8825277 0.8452743
Mi.6.24h 0.9156257 0.9172329 0.9153063 0.9188890 0.8758025 0.8509642 0.8353814
Tr.6.24h 0.9240755 0.9242409 0.9214547 0.9349693 0.8352300 0.8190487 0.8276731
Ve.6.24h 0.9364668 0.9390819 0.9359471 0.9391976 0.8452882 0.8259444 0.8357285
Mi.2.24h Tr.2.24h Ve.2.24h Da.3.3h Do.3.3h Ep.3.3h Mi.3.3h
Da.1.3h 0.9049226 0.9005961 0.8948423 0.9319512 0.9310647 0.9404014 0.9301179
Do.1.3h 0.9007429 0.8951984 0.8877475 0.9225026 0.9352041 0.9280220 0.9205185
Ep.1.3h 0.9027168 0.8988347 0.8914513 0.9241631 0.9326231 0.9355110 0.9250091
Mi.1.3h 0.9036491 0.8968318 0.8891347 0.9209965 0.9332567 0.9278036 0.9222625
Tr.1.3h 0.8993008 0.8941245 0.8869126 0.9132814 0.9289201 0.9195856 0.9124563
Ve.1.3h 0.9001345 0.8946371 0.8886604 0.9144588 0.9308794 0.9200323 0.9141138
Da.1.24h 0.8296148 0.7897035 0.7785197 0.8300117 0.8334422 0.8274232 0.8196522
Do.1.24h 0.7955292 0.7569038 0.7484706 0.7915342 0.7974397 0.7914791 0.7840216
Ep.1.24h 0.8310525 0.7896055 0.7770379 0.8246744 0.8303429 0.8249328 0.8164126
Mi.1.24h 0.8979756 0.8584457 0.8473999 0.8855827 0.8975292 0.8875707 0.8810544
Tr.1.24h 0.8982202 0.8942769 0.8843395 0.9134100 0.9292880 0.9183543 0.9096131
Ve.1.24h 0.8937949 0.8902877 0.8824575 0.9120210 0.9290867 0.9157540 0.9078395
Da.2.3h 0.9445665 0.9640091 0.9636159 0.9489932 0.9447509 0.9496848 0.9472050
Do.2.3h 0.9488171 0.9664680 0.9681654 0.9468872 0.9486250 0.9436578 0.9468563
Ep.2.3h 0.9466472 0.9641563 0.9606920 0.9516667 0.9494577 0.9500770 0.9511857
Mi.2.3h 0.9494473 0.9669042 0.9680169 0.9506865 0.9472499 0.9508407 0.9518358
Tr.2.3h 0.9492839 0.9673050 0.9694273 0.9389602 0.9402013 0.9394384 0.9425333
Ve.2.3h 0.9541295 0.9713199 0.9696732 0.9421481 0.9519940 0.9418908 0.9457019
Da.2.24h 0.8894501 0.8545253 0.8502389 0.8603349 0.8587276 0.8571467 0.8559729
Do.2.24h 0.8698542 0.8376339 0.8306731 0.8463004 0.8469090 0.8388784 0.8367134
Ep.2.24h 0.8575363 0.8541634 0.8548037 0.8656057 0.8522310 0.8588752 0.8575115
Mi.2.24h 1.0000000 0.9568316 0.9508896 0.9316304 0.9360357 0.9328557 0.9334560
Tr.2.24h 0.9568316 1.0000000 0.9717571 0.9400161 0.9415656 0.9444877 0.9445238
Ve.2.24h 0.9508896 0.9717571 1.0000000 0.9375508 0.9344915 0.9410164 0.9420269
Da.3.3h 0.9316304 0.9400161 0.9375508 1.0000000 0.9635737 0.9779043 0.9758327
Do.3.3h 0.9360357 0.9415656 0.9344915 0.9635737 1.0000000 0.9637348 0.9620550
Ep.3.3h 0.9328557 0.9444877 0.9410164 0.9779043 0.9637348 1.0000000 0.9765144
Mi.3.3h 0.9334560 0.9445238 0.9420269 0.9758327 0.9620550 0.9765144 1.0000000
Tr.3.3h 0.9420835 0.9481229 0.9426355 0.9606716 0.9783721 0.9650841 0.9634194
Ve.3.3h 0.9396605 0.9504871 0.9482731 0.9742022 0.9662597 0.9769231 0.9747965
Da.3.24h 0.8883486 0.8428194 0.8349778 0.8745498 0.8760563 0.8773763 0.8718519
Do.3.24h 0.8825751 0.8425593 0.8393845 0.8703317 0.8724196 0.8703292 0.8691354
Ep.3.24h 0.8703758 0.8311032 0.8202219 0.8624665 0.8641284 0.8635483 0.8585566
Mi.3.24h 0.9580727 0.9256677 0.9213507 0.9430727 0.9505538 0.9467345 0.9454437
Tr.3.24h 0.9444290 0.9527667 0.9499401 0.9565629 0.9719036 0.9608144 0.9598494
Ve.3.24h 0.9313862 0.9505941 0.9472943 0.9548230 0.9632672 0.9606691 0.9585284
Da.4.3h 0.9025457 0.9048838 0.9012317 0.9406310 0.9428199 0.9447516 0.9372826
Do.4.3h 0.9108193 0.9124155 0.9102824 0.9444897 0.9502406 0.9499720 0.9440547
Ep.4.3h 0.9099186 0.9109100 0.9090935 0.9429002 0.9463699 0.9489679 0.9420399
Mi.4.3h 0.9147610 0.9147204 0.9110490 0.9439523 0.9490868 0.9488666 0.9455019
Tr.4.3h 0.9123954 0.9159884 0.9122849 0.9400416 0.9499515 0.9467285 0.9407909
Ve.4.3h 0.9097498 0.9107537 0.9061023 0.9348259 0.9466553 0.9405619 0.9353934
Da.4.24h 0.8642900 0.8233832 0.8150411 0.8593784 0.8603697 0.8618314 0.8552497
Do.4.24h 0.8623202 0.8207942 0.8113844 0.8568135 0.8626126 0.8596145 0.8515994
Ep.4.24h 0.8609720 0.8216637 0.8151419 0.8531568 0.8550235 0.8602036 0.8532863
Mi.4.24h 0.9242806 0.8915539 0.8845496 0.9171808 0.9280590 0.9222878 0.9171286
Tr.4.24h 0.9155746 0.9198187 0.9120150 0.9404097 0.9498697 0.9465714 0.9391870
Ve.4.24h 0.9073627 0.9094493 0.9043524 0.9320432 0.9443321 0.9359995 0.9302318
Da.5.3h 0.9228157 0.9275561 0.9198757 0.9482972 0.9358360 0.9472278 0.9424501
Do.5.3h 0.9303152 0.9330177 0.9237426 0.9398338 0.9512530 0.9419778 0.9376814
Ep.5.3h 0.9270951 0.9330459 0.9245882 0.9462035 0.9363548 0.9478354 0.9435996
Mi.5.3h 0.9300098 0.9344930 0.9274742 0.9463984 0.9365860 0.9460325 0.9472219
Tr.5.3h 0.9261508 0.9363464 0.9334849 0.9362011 0.9310996 0.9404525 0.9350667
Ve.5.3h 0.9178207 0.9259452 0.9217456 0.9251729 0.9259087 0.9299461 0.9221300
Da.5.24h 0.8802357 0.8450832 0.8418194 0.8653549 0.8624283 0.8647301 0.8580008
Do.5.24h 0.8981966 0.8590910 0.8553006 0.8728755 0.8712405 0.8760745 0.8705455
Ep.5.24h 0.9101047 0.8679059 0.8567502 0.8838980 0.8905454 0.8837907 0.8795592
Mi.5.24h 0.9398966 0.9070190 0.8951939 0.9094269 0.9185063 0.9136078 0.9098337
Tr.5.24h 0.9280635 0.9452214 0.9310607 0.9335422 0.9403740 0.9377271 0.9344148
Ve.5.24h 0.9257563 0.9400059 0.9270453 0.9303001 0.9423690 0.9330383 0.9292742
Da.6.3h 0.9284145 0.9358771 0.9361519 0.9557381 0.9519342 0.9590234 0.9557557
Do.6.3h 0.9272572 0.9374282 0.9356307 0.9498276 0.9540471 0.9550412 0.9517904
Ep.6.3h 0.9230838 0.9327742 0.9300138 0.9448233 0.9545895 0.9514469 0.9472243
Mi.6.3h 0.9268302 0.9336252 0.9335234 0.9517162 0.9504321 0.9540049 0.9544246
Tr.6.3h 0.9277930 0.9393935 0.9387152 0.9516417 0.9519361 0.9573729 0.9545789
Ve.6.3h 0.9251535 0.9346754 0.9350717 0.9489812 0.9511736 0.9533672 0.9506932
Da.6.24h 0.8947999 0.8545366 0.8487196 0.8804099 0.8812579 0.8812495 0.8774172
Do.6.24h 0.9211467 0.8879782 0.8868250 0.9030382 0.9104198 0.9094570 0.9068410
Ep.6.24h 0.9210295 0.8880871 0.8880177 0.9111267 0.9094608 0.9139480 0.9124990
Mi.6.24h 0.9445596 0.9189094 0.9184895 0.9328823 0.9336674 0.9366198 0.9357577
Tr.6.24h 0.9175878 0.9322201 0.9268185 0.9379919 0.9440045 0.9424418 0.9391237
Ve.6.24h 0.9259933 0.9379377 0.9397354 0.9496691 0.9476678 0.9548709 0.9506285
Tr.3.3h Ve.3.3h Da.3.24h Do.3.24h Ep.3.24h Mi.3.24h Tr.3.24h
Da.1.3h 0.9310105 0.9281711 0.8739904 0.8616160 0.8567431 0.9245509 0.9269675
Do.1.3h 0.9333273 0.9229720 0.8701387 0.8600436 0.8552229 0.9230034 0.9281541
Ep.1.3h 0.9336036 0.9254536 0.8750195 0.8600780 0.8592945 0.9251028 0.9273675
Mi.1.3h 0.9329442 0.9235198 0.8722760 0.8586000 0.8563004 0.9264555 0.9273672
Tr.1.3h 0.9308929 0.9210853 0.8627761 0.8506553 0.8472015 0.9211812 0.9270419
Ve.1.3h 0.9325504 0.9205402 0.8636353 0.8541401 0.8476827 0.9214072 0.9288847
Da.1.24h 0.8226232 0.8135663 0.9301956 0.9194606 0.9291292 0.8631471 0.8156204
Do.1.24h 0.7891081 0.7796093 0.8776849 0.8708386 0.8742969 0.8270067 0.7816226
Ep.1.24h 0.8230688 0.8120775 0.9362267 0.9262910 0.9412060 0.8658812 0.8144762
Mi.1.24h 0.8964122 0.8854542 0.9001429 0.8832987 0.8815531 0.9310940 0.8933662
Tr.1.24h 0.9302259 0.9202094 0.8614155 0.8471508 0.8460977 0.9213687 0.9286039
Ve.1.24h 0.9292053 0.9169697 0.8582084 0.8470185 0.8418408 0.9183113 0.9280436
Da.2.3h 0.9432514 0.9443037 0.8454752 0.8456526 0.8334370 0.9185237 0.9436753
Do.2.3h 0.9493347 0.9463338 0.8445506 0.8488116 0.8344009 0.9217908 0.9476406
Ep.2.3h 0.9492438 0.9481883 0.8505629 0.8487769 0.8425422 0.9231606 0.9440162
Mi.2.3h 0.9506362 0.9486133 0.8537097 0.8526038 0.8429572 0.9263459 0.9467760
Tr.2.3h 0.9461725 0.9446488 0.8397213 0.8422465 0.8308222 0.9195926 0.9446293
Ve.2.3h 0.9562970 0.9511823 0.8428792 0.8463828 0.8315071 0.9256289 0.9563489
Da.2.24h 0.8519013 0.8482484 0.9447768 0.9455021 0.9537477 0.8891174 0.8465755
Do.2.24h 0.8397426 0.8284335 0.9226031 0.9299424 0.9392398 0.8677430 0.8327570
Ep.2.24h 0.8451512 0.8436845 0.8447778 0.8478318 0.8469197 0.8469894 0.8399806
Mi.2.24h 0.9420835 0.9396605 0.8883486 0.8825751 0.8703758 0.9580727 0.9444290
Tr.2.24h 0.9481229 0.9504871 0.8428194 0.8425593 0.8311032 0.9256677 0.9527667
Ve.2.24h 0.9426355 0.9482731 0.8349778 0.8393845 0.8202219 0.9213507 0.9499401
Da.3.3h 0.9606716 0.9742022 0.8745498 0.8703317 0.8624665 0.9430727 0.9565629
Do.3.3h 0.9783721 0.9662597 0.8760563 0.8724196 0.8641284 0.9505538 0.9719036
Ep.3.3h 0.9650841 0.9769231 0.8773763 0.8703292 0.8635483 0.9467345 0.9608144
Mi.3.3h 0.9634194 0.9747965 0.8718519 0.8691354 0.8585566 0.9454437 0.9598494
Tr.3.3h 1.0000000 0.9726815 0.8734405 0.8697386 0.8607974 0.9553915 0.9790549
Ve.3.3h 0.9726815 1.0000000 0.8675675 0.8645082 0.8542979 0.9504338 0.9695546
Da.3.24h 0.8734405 0.8675675 1.0000000 0.9676162 0.9695606 0.9206502 0.8661466
Do.3.24h 0.8697386 0.8645082 0.9676162 1.0000000 0.9701005 0.9129585 0.8675990
Ep.3.24h 0.8607974 0.8542979 0.9695606 0.9701005 1.0000000 0.9022657 0.8515367
Mi.3.24h 0.9553915 0.9504338 0.9206502 0.9129585 0.9022657 1.0000000 0.9542995
Tr.3.24h 0.9790549 0.9695546 0.8661466 0.8675990 0.8515367 0.9542995 1.0000000
Ve.3.24h 0.9690983 0.9671222 0.8508359 0.8538559 0.8404625 0.9375544 0.9712099
Da.4.3h 0.9416363 0.9364279 0.8656141 0.8575428 0.8518785 0.9249333 0.9358367
Do.4.3h 0.9504530 0.9462675 0.8682374 0.8628247 0.8530217 0.9322771 0.9463612
Ep.4.3h 0.9460012 0.9421350 0.8695336 0.8612442 0.8542916 0.9305213 0.9420747
Mi.4.3h 0.9509782 0.9471739 0.8721348 0.8643356 0.8587260 0.9360057 0.9456603
Tr.4.3h 0.9554468 0.9494873 0.8624102 0.8547693 0.8481093 0.9337918 0.9500072
Ve.4.3h 0.9504746 0.9440535 0.8623976 0.8518979 0.8476940 0.9309793 0.9448421
Da.4.24h 0.8567555 0.8490869 0.9544104 0.9461110 0.9525639 0.8960787 0.8462980
Do.4.24h 0.8604954 0.8478063 0.9539178 0.9468758 0.9544238 0.8977888 0.8486795
Ep.4.24h 0.8535513 0.8469083 0.9498973 0.9437691 0.9495689 0.8937563 0.8447271
Mi.4.24h 0.9317202 0.9224702 0.9046636 0.8914603 0.8848836 0.9548084 0.9278806
Tr.4.24h 0.9546916 0.9491411 0.8630958 0.8511829 0.8490306 0.9352622 0.9515430
Ve.4.24h 0.9475800 0.9391386 0.8597853 0.8510996 0.8449847 0.9303312 0.9451441
Da.5.3h 0.9321448 0.9396624 0.8717300 0.8606107 0.8581065 0.9235936 0.9278274
Do.5.3h 0.9502117 0.9401800 0.8772849 0.8677243 0.8646307 0.9342704 0.9428965
Ep.5.3h 0.9368774 0.9434063 0.8691039 0.8548883 0.8569747 0.9269511 0.9297376
Mi.5.3h 0.9371499 0.9426560 0.8665900 0.8564612 0.8532354 0.9290230 0.9323651
Tr.5.3h 0.9387189 0.9431705 0.8532676 0.8459047 0.8374918 0.9242729 0.9371415
Ve.5.3h 0.9334435 0.9330434 0.8485305 0.8395122 0.8346837 0.9166193 0.9276478
Da.5.24h 0.8618212 0.8569441 0.9316463 0.9237431 0.9243063 0.8971671 0.8522163
Do.5.24h 0.8719487 0.8683547 0.9553551 0.9498908 0.9462771 0.9156399 0.8665244
Ep.5.24h 0.8893987 0.8798044 0.9470549 0.9345525 0.9358476 0.9282627 0.8812129
Mi.5.24h 0.9219800 0.9141484 0.9088599 0.8929341 0.8943775 0.9502110 0.9165599
Tr.5.24h 0.9430257 0.9424556 0.8498121 0.8429081 0.8399918 0.9228753 0.9445246
Ve.5.24h 0.9437529 0.9379176 0.8540418 0.8485911 0.8455858 0.9214518 0.9440509
Da.6.3h 0.9513114 0.9545141 0.8701109 0.8653734 0.8558929 0.9351703 0.9505835
Do.6.3h 0.9539875 0.9559460 0.8619189 0.8585999 0.8470857 0.9339508 0.9553979
Ep.6.3h 0.9552190 0.9500723 0.8641699 0.8629421 0.8508868 0.9327204 0.9550118
Mi.6.3h 0.9508483 0.9545701 0.8648663 0.8611292 0.8506788 0.9345278 0.9507202
Tr.6.3h 0.9570309 0.9632214 0.8549520 0.8525929 0.8412836 0.9344653 0.9580823
Ve.6.3h 0.9558454 0.9579041 0.8551449 0.8507649 0.8404771 0.9345760 0.9556189
Da.6.24h 0.8787789 0.8736104 0.9604804 0.9518485 0.9520654 0.9191496 0.8724314
Do.6.24h 0.9145399 0.9070158 0.9374232 0.9339138 0.9222519 0.9424562 0.9108917
Ep.6.24h 0.9113835 0.9104108 0.9334199 0.9295633 0.9169379 0.9419878 0.9091810
Mi.6.24h 0.9383897 0.9409337 0.8978898 0.8925991 0.8769434 0.9604872 0.9410499
Tr.6.24h 0.9473078 0.9476530 0.8467667 0.8496115 0.8366218 0.9248102 0.9526619
Ve.6.24h 0.9535113 0.9580342 0.8546983 0.8535577 0.8412829 0.9338696 0.9550625
Ve.3.24h Da.4.3h Do.4.3h Ep.4.3h Mi.4.3h Tr.4.3h Ve.4.3h
Da.1.3h 0.9142432 0.9652104 0.9643503 0.9653609 0.9609100 0.9588647 0.9557574
Do.1.3h 0.9148495 0.9615603 0.9649784 0.9641171 0.9625702 0.9637644 0.9625032
Ep.1.3h 0.9145529 0.9646649 0.9650904 0.9664620 0.9629950 0.9631052 0.9611523
Mi.1.3h 0.9134950 0.9606712 0.9625998 0.9625394 0.9633040 0.9623286 0.9610639
Tr.1.3h 0.9122088 0.9533052 0.9578774 0.9572996 0.9585662 0.9620751 0.9610084
Ve.1.3h 0.9126111 0.9546199 0.9604689 0.9576933 0.9601196 0.9630988 0.9621090
Da.1.24h 0.7978031 0.8631918 0.8592083 0.8625445 0.8637672 0.8522685 0.8553049
Do.1.24h 0.7641135 0.8202735 0.8160134 0.8201682 0.8192649 0.8101134 0.8124077
Ep.1.24h 0.7954595 0.8554897 0.8521486 0.8560043 0.8574806 0.8479038 0.8503181
Mi.1.24h 0.8683180 0.9245745 0.9265330 0.9271063 0.9307158 0.9281268 0.9301602
Tr.1.24h 0.9120092 0.9507693 0.9531080 0.9534200 0.9551968 0.9595347 0.9595112
Ve.1.24h 0.9107172 0.9510543 0.9538980 0.9521434 0.9542131 0.9581831 0.9579539
Da.2.3h 0.9448795 0.9169493 0.9179944 0.9189952 0.9158224 0.9128340 0.9082988
Do.2.3h 0.9456026 0.9133161 0.9213886 0.9194670 0.9210439 0.9203900 0.9161504
Ep.2.3h 0.9441703 0.9230977 0.9268824 0.9260613 0.9262142 0.9249273 0.9208712
Mi.2.3h 0.9441494 0.9187399 0.9226853 0.9232669 0.9244977 0.9216335 0.9177452
Tr.2.3h 0.9438895 0.9054593 0.9145164 0.9128256 0.9161758 0.9171252 0.9123657
Ve.2.3h 0.9541408 0.9129207 0.9227238 0.9201298 0.9233260 0.9258615 0.9216124
Da.2.24h 0.8355915 0.8515114 0.8510367 0.8543849 0.8573056 0.8447307 0.8452954
Do.2.24h 0.8219614 0.8338594 0.8313855 0.8338779 0.8365004 0.8251959 0.8258670
Ep.2.24h 0.8375679 0.8494456 0.8404159 0.8459510 0.8420831 0.8297657 0.8276904
Mi.2.24h 0.9313862 0.9025457 0.9108193 0.9099186 0.9147610 0.9123954 0.9097498
Tr.2.24h 0.9505941 0.9048838 0.9124155 0.9109100 0.9147204 0.9159884 0.9107537
Ve.2.24h 0.9472943 0.9012317 0.9102824 0.9090935 0.9110490 0.9122849 0.9061023
Da.3.3h 0.9548230 0.9406310 0.9444897 0.9429002 0.9439523 0.9400416 0.9348259
Do.3.3h 0.9632672 0.9428199 0.9502406 0.9463699 0.9490868 0.9499515 0.9466553
Ep.3.3h 0.9606691 0.9447516 0.9499720 0.9489679 0.9488666 0.9467285 0.9405619
Mi.3.3h 0.9585284 0.9372826 0.9440547 0.9420399 0.9455019 0.9407909 0.9353934
Tr.3.3h 0.9690983 0.9416363 0.9504530 0.9460012 0.9509782 0.9554468 0.9504746
Ve.3.3h 0.9671222 0.9364279 0.9462675 0.9421350 0.9471739 0.9494873 0.9440535
Da.3.24h 0.8508359 0.8656141 0.8682374 0.8695336 0.8721348 0.8624102 0.8623976
Do.3.24h 0.8538559 0.8575428 0.8628247 0.8612442 0.8643356 0.8547693 0.8518979
Ep.3.24h 0.8404625 0.8518785 0.8530217 0.8542916 0.8587260 0.8481093 0.8476940
Mi.3.24h 0.9375544 0.9249333 0.9322771 0.9305213 0.9360057 0.9337918 0.9309793
Tr.3.24h 0.9712099 0.9358367 0.9463612 0.9420747 0.9456603 0.9500072 0.9448421
Ve.3.24h 1.0000000 0.9262788 0.9365652 0.9311024 0.9343179 0.9392469 0.9335673
Da.4.3h 0.9262788 1.0000000 0.9808518 0.9814203 0.9781217 0.9766880 0.9739218
Do.4.3h 0.9365652 0.9808518 1.0000000 0.9845110 0.9835978 0.9852957 0.9803580
Ep.4.3h 0.9311024 0.9814203 0.9845110 1.0000000 0.9821430 0.9818876 0.9779398
Mi.4.3h 0.9343179 0.9781217 0.9835978 0.9821430 1.0000000 0.9840320 0.9809871
Tr.4.3h 0.9392469 0.9766880 0.9852957 0.9818876 0.9840320 1.0000000 0.9867573
Ve.4.3h 0.9335673 0.9739218 0.9803580 0.9779398 0.9809871 0.9867573 1.0000000
Da.4.24h 0.8313825 0.8909044 0.8918585 0.8928831 0.8953126 0.8860799 0.8850283
Do.4.24h 0.8316092 0.8905925 0.8922314 0.8924007 0.8953355 0.8888215 0.8876681
Ep.4.24h 0.8281481 0.8904014 0.8921083 0.8934275 0.8953730 0.8864499 0.8833698
Mi.4.24h 0.9058957 0.9535085 0.9598960 0.9576208 0.9624663 0.9632516 0.9599611
Tr.4.24h 0.9410597 0.9719181 0.9785055 0.9762340 0.9792298 0.9853978 0.9825936
Ve.4.24h 0.9323641 0.9686359 0.9744448 0.9735285 0.9753743 0.9805544 0.9775643
Da.5.3h 0.9196602 0.9298320 0.9297389 0.9322323 0.9311662 0.9251773 0.9233914
Do.5.3h 0.9319616 0.9315938 0.9354134 0.9356382 0.9365863 0.9350333 0.9338844
Ep.5.3h 0.9211838 0.9261831 0.9294610 0.9302751 0.9319579 0.9283939 0.9260080
Mi.5.3h 0.9235836 0.9274573 0.9301927 0.9309759 0.9345472 0.9279726 0.9256351
Tr.5.3h 0.9263197 0.9119609 0.9182121 0.9178097 0.9210501 0.9218268 0.9173557
Ve.5.3h 0.9189477 0.9097962 0.9147709 0.9137511 0.9172057 0.9197768 0.9177904
Da.5.24h 0.8376521 0.8538268 0.8551674 0.8571386 0.8591629 0.8502682 0.8520295
Do.5.24h 0.8496427 0.8631940 0.8669829 0.8688646 0.8709386 0.8614195 0.8604740
Ep.5.24h 0.8649322 0.8771429 0.8807072 0.8805630 0.8852534 0.8792379 0.8803820
Mi.5.24h 0.9022243 0.9062831 0.9122567 0.9108887 0.9170427 0.9145889 0.9144789
Tr.5.24h 0.9459633 0.9160605 0.9210579 0.9202987 0.9235001 0.9267644 0.9243517
Ve.5.24h 0.9453635 0.9198813 0.9249312 0.9236802 0.9266499 0.9308786 0.9289531
Da.6.3h 0.9432901 0.9623014 0.9658456 0.9663264 0.9636879 0.9616502 0.9571330
Do.6.3h 0.9497187 0.9533293 0.9617866 0.9604958 0.9603695 0.9620895 0.9572930
Ep.6.3h 0.9503082 0.9559766 0.9635270 0.9610347 0.9607597 0.9630300 0.9577612
Mi.6.3h 0.9424001 0.9569386 0.9637693 0.9629552 0.9654311 0.9634194 0.9587618
Tr.6.3h 0.9515675 0.9528389 0.9634865 0.9605551 0.9627351 0.9672528 0.9605149
Ve.6.3h 0.9476778 0.9544795 0.9634370 0.9610375 0.9631553 0.9667625 0.9627477
Da.6.24h 0.8570419 0.8879780 0.8906466 0.8925028 0.8951565 0.8866752 0.8861563
Do.6.24h 0.8962989 0.9129494 0.9217208 0.9190624 0.9225841 0.9193438 0.9145806
Ep.6.24h 0.8913668 0.9177314 0.9248859 0.9236646 0.9265042 0.9205284 0.9178257
Mi.6.24h 0.9224016 0.9349239 0.9443170 0.9417809 0.9463184 0.9450070 0.9401703
Tr.6.24h 0.9557961 0.9338249 0.9429781 0.9380089 0.9403578 0.9466275 0.9404918
Ve.6.24h 0.9509475 0.9482949 0.9572719 0.9539978 0.9562418 0.9606959 0.9545815
Da.4.24h Do.4.24h Ep.4.24h Mi.4.24h Tr.4.24h Ve.4.24h Da.5.3h
Da.1.3h 0.8888555 0.8898632 0.8907498 0.9470074 0.9581093 0.9526905 0.9251855
Do.1.3h 0.8886834 0.8927680 0.8884543 0.9530740 0.9624521 0.9599575 0.9169488
Ep.1.3h 0.8923650 0.8953969 0.8953452 0.9526112 0.9632557 0.9566278 0.9212022
Mi.1.3h 0.8885716 0.8927534 0.8898975 0.9539310 0.9629274 0.9589479 0.9187003
Tr.1.3h 0.8787536 0.8829611 0.8790457 0.9500433 0.9635518 0.9596461 0.9090587
Ve.1.3h 0.8805659 0.8860426 0.8816249 0.9512113 0.9612795 0.9592674 0.9084347
Da.1.24h 0.9583502 0.9553138 0.9509203 0.8928881 0.8546325 0.8559965 0.8455172
Do.1.24h 0.8943707 0.8970888 0.8907220 0.8481638 0.8117346 0.8138382 0.8042730
Ep.1.24h 0.9560115 0.9593159 0.9551319 0.8924841 0.8513759 0.8512190 0.8423694
Mi.1.24h 0.9166980 0.9213897 0.9142972 0.9642623 0.9319313 0.9315674 0.8915297
Tr.1.24h 0.8755686 0.8815145 0.8738444 0.9504120 0.9667471 0.9632960 0.9108781
Ve.1.24h 0.8727480 0.8791922 0.8722747 0.9487939 0.9632483 0.9632266 0.9061182
Da.2.3h 0.8291460 0.8244627 0.8251954 0.8848970 0.9129507 0.9055668 0.9346167
Do.2.3h 0.8318428 0.8289532 0.8265801 0.8910710 0.9158161 0.9100031 0.9295403
Ep.2.3h 0.8416656 0.8385593 0.8371284 0.8963637 0.9224788 0.9141658 0.9376817
Mi.2.3h 0.8376113 0.8359666 0.8335156 0.8954169 0.9203649 0.9133365 0.9395908
Tr.2.3h 0.8260662 0.8219882 0.8233201 0.8875448 0.9139382 0.9061954 0.9221783
Ve.2.3h 0.8270021 0.8248664 0.8234413 0.8947390 0.9231734 0.9169280 0.9274810
Da.2.24h 0.9410446 0.9335391 0.9362517 0.8725712 0.8436131 0.8410378 0.8705591
Do.2.24h 0.9205201 0.9168737 0.9121768 0.8512825 0.8238775 0.8219384 0.8550083
Ep.2.24h 0.8484133 0.8383863 0.8453572 0.8261426 0.8246577 0.8196852 0.8697579
Mi.2.24h 0.8642900 0.8623202 0.8609720 0.9242806 0.9155746 0.9073627 0.9228157
Tr.2.24h 0.8233832 0.8207942 0.8216637 0.8915539 0.9198187 0.9094493 0.9275561
Ve.2.24h 0.8150411 0.8113844 0.8151419 0.8845496 0.9120150 0.9043524 0.9198757
Da.3.3h 0.8593784 0.8568135 0.8531568 0.9171808 0.9404097 0.9320432 0.9482972
Do.3.3h 0.8603697 0.8626126 0.8550235 0.9280590 0.9498697 0.9443321 0.9358360
Ep.3.3h 0.8618314 0.8596145 0.8602036 0.9222878 0.9465714 0.9359995 0.9472278
Mi.3.3h 0.8552497 0.8515994 0.8532863 0.9171286 0.9391870 0.9302318 0.9424501
Tr.3.3h 0.8567555 0.8604954 0.8535513 0.9317202 0.9546916 0.9475800 0.9321448
Ve.3.3h 0.8490869 0.8478063 0.8469083 0.9224702 0.9491411 0.9391386 0.9396624
Da.3.24h 0.9544104 0.9539178 0.9498973 0.9046636 0.8630958 0.8597853 0.8717300
Do.3.24h 0.9461110 0.9468758 0.9437691 0.8914603 0.8511829 0.8510996 0.8606107
Ep.3.24h 0.9525639 0.9544238 0.9495689 0.8848836 0.8490306 0.8449847 0.8581065
Mi.3.24h 0.8960787 0.8977888 0.8937563 0.9548084 0.9352622 0.9303312 0.9235936
Tr.3.24h 0.8462980 0.8486795 0.8447271 0.9278806 0.9515430 0.9451441 0.9278274
Ve.3.24h 0.8313825 0.8316092 0.8281481 0.9058957 0.9410597 0.9323641 0.9196602
Da.4.3h 0.8909044 0.8905925 0.8904014 0.9535085 0.9719181 0.9686359 0.9298320
Do.4.3h 0.8918585 0.8922314 0.8921083 0.9598960 0.9785055 0.9744448 0.9297389
Ep.4.3h 0.8928831 0.8924007 0.8934275 0.9576208 0.9762340 0.9735285 0.9322323
Mi.4.3h 0.8953126 0.8953355 0.8953730 0.9624663 0.9792298 0.9753743 0.9311662
Tr.4.3h 0.8860799 0.8888215 0.8864499 0.9632516 0.9853978 0.9805544 0.9251773
Ve.4.3h 0.8850283 0.8876681 0.8833698 0.9599611 0.9825936 0.9775643 0.9233914
Da.4.24h 1.0000000 0.9825758 0.9814257 0.9233822 0.8826263 0.8801674 0.8677534
Do.4.24h 0.9825758 1.0000000 0.9784794 0.9277125 0.8864622 0.8845484 0.8642322
Ep.4.24h 0.9814257 0.9784794 1.0000000 0.9239208 0.8818611 0.8791049 0.8630201
Mi.4.24h 0.9233822 0.9277125 0.9239208 1.0000000 0.9632879 0.9605816 0.9116465
Tr.4.24h 0.8826263 0.8864622 0.8818611 0.9632879 1.0000000 0.9841696 0.9273283
Ve.4.24h 0.8801674 0.8845484 0.8791049 0.9605816 0.9841696 1.0000000 0.9197103
Da.5.3h 0.8677534 0.8642322 0.8630201 0.9116465 0.9273283 0.9197103 1.0000000
Do.5.3h 0.8705007 0.8728096 0.8678853 0.9248046 0.9373094 0.9307327 0.9650565
Ep.5.3h 0.8643306 0.8618681 0.8620130 0.9142562 0.9306386 0.9198047 0.9723356
Mi.5.3h 0.8623466 0.8596784 0.8595948 0.9157945 0.9289520 0.9203412 0.9717528
Tr.5.3h 0.8419393 0.8418757 0.8387362 0.9052425 0.9226275 0.9151239 0.9559939
Ve.5.3h 0.8411053 0.8449840 0.8351311 0.9031867 0.9198345 0.9131088 0.9479551
Da.5.24h 0.9210796 0.9222374 0.9131622 0.8842275 0.8524954 0.8510282 0.8912701
Do.5.24h 0.9416402 0.9418656 0.9388200 0.9013035 0.8618636 0.8595660 0.9002784
Ep.5.24h 0.9321779 0.9373198 0.9267314 0.9202275 0.8819033 0.8781345 0.9107682
Mi.5.24h 0.9006656 0.9022655 0.8966314 0.9411567 0.9167138 0.9092061 0.9338877
Tr.5.24h 0.8388379 0.8400540 0.8349217 0.9069010 0.9355575 0.9244891 0.9530954
Ve.5.24h 0.8461141 0.8489318 0.8404214 0.9094360 0.9356161 0.9278172 0.9484859
Da.6.3h 0.8772361 0.8727698 0.8764443 0.9336844 0.9563217 0.9500770 0.9409377
Do.6.3h 0.8648026 0.8628884 0.8636261 0.9320511 0.9583589 0.9536874 0.9327901
Ep.6.3h 0.8698920 0.8691907 0.8694241 0.9343270 0.9571687 0.9535413 0.9279505
Mi.6.3h 0.8732082 0.8698553 0.8725630 0.9357304 0.9572998 0.9529996 0.9364268
Tr.6.3h 0.8600761 0.8578694 0.8595924 0.9331753 0.9622841 0.9564594 0.9315271
Ve.6.3h 0.8601592 0.8592926 0.8588233 0.9340499 0.9624066 0.9579247 0.9299057
Da.6.24h 0.9620683 0.9598673 0.9559787 0.9199268 0.8846248 0.8828708 0.8812780
Do.6.24h 0.9345763 0.9361657 0.9346807 0.9437077 0.9126086 0.9097703 0.8930055
Ep.6.24h 0.9343298 0.9335314 0.9357111 0.9448748 0.9154502 0.9145750 0.9009265
Mi.6.24h 0.8944419 0.8943044 0.8936960 0.9576235 0.9427770 0.9393327 0.9176514
Tr.6.24h 0.8441093 0.8462306 0.8421687 0.9208149 0.9482093 0.9415586 0.9108645
Ve.6.24h 0.8578100 0.8570850 0.8554175 0.9314514 0.9581444 0.9536817 0.9271688
Do.5.3h Ep.5.3h Mi.5.3h Tr.5.3h Ve.5.3h Da.5.24h Do.5.24h
Da.1.3h 0.9256423 0.9235453 0.9235694 0.9112021 0.9068814 0.8601425 0.8727576
Do.1.3h 0.9277729 0.9148518 0.9178789 0.9041599 0.9033397 0.8555858 0.8669491
Ep.1.3h 0.9294429 0.9227641 0.9218295 0.9072484 0.9043493 0.8564509 0.8720142
Mi.1.3h 0.9295165 0.9191107 0.9220799 0.9062446 0.9058188 0.8572256 0.8692469
Tr.1.3h 0.9238239 0.9099688 0.9114808 0.9034204 0.9037313 0.8515660 0.8617188
Ve.1.3h 0.9240714 0.9094219 0.9128291 0.9030968 0.9047044 0.8524342 0.8623623
Da.1.24h 0.8470377 0.8340229 0.8355114 0.8138187 0.8162827 0.9003719 0.9147373
Do.1.24h 0.8093287 0.7962217 0.7974413 0.7828324 0.7852353 0.8584900 0.8682346
Ep.1.24h 0.8479751 0.8339930 0.8320092 0.8147371 0.8155383 0.9038109 0.9218658
Mi.1.24h 0.9033772 0.8890403 0.8924288 0.8793167 0.8816718 0.8831014 0.8958821
Tr.1.24h 0.9250837 0.9106477 0.9104044 0.9062162 0.9058273 0.8522071 0.8608169
Ve.1.24h 0.9212384 0.9043326 0.9062050 0.9015712 0.9027116 0.8496179 0.8577698
Da.2.3h 0.9338593 0.9341510 0.9367428 0.9310612 0.9204924 0.8497151 0.8590150
Do.2.3h 0.9362750 0.9331700 0.9365243 0.9315397 0.9247871 0.8520675 0.8588649
Ep.2.3h 0.9406960 0.9432972 0.9432117 0.9299433 0.9236402 0.8533626 0.8620280
Mi.2.3h 0.9420930 0.9423218 0.9452434 0.9428093 0.9366607 0.8682366 0.8698806
Tr.2.3h 0.9296762 0.9312828 0.9336895 0.9277644 0.9218454 0.8477624 0.8543580
Ve.2.3h 0.9397909 0.9310277 0.9352239 0.9327352 0.9264562 0.8450885 0.8562606
Da.2.24h 0.8682807 0.8650496 0.8634318 0.8452076 0.8410655 0.9205625 0.9366743
Do.2.24h 0.8547143 0.8461416 0.8453640 0.8310601 0.8312172 0.9068049 0.9153713
Ep.2.24h 0.8551251 0.8544332 0.8582018 0.8343009 0.8303590 0.8378232 0.8436964
Mi.2.24h 0.9303152 0.9270951 0.9300098 0.9261508 0.9178207 0.8802357 0.8981966
Tr.2.24h 0.9330177 0.9330459 0.9344930 0.9363464 0.9259452 0.8450832 0.8590910
Ve.2.24h 0.9237426 0.9245882 0.9274742 0.9334849 0.9217456 0.8418194 0.8553006
Da.3.3h 0.9398338 0.9462035 0.9463984 0.9362011 0.9251729 0.8653549 0.8728755
Do.3.3h 0.9512530 0.9363548 0.9365860 0.9310996 0.9259087 0.8624283 0.8712405
Ep.3.3h 0.9419778 0.9478354 0.9460325 0.9404525 0.9299461 0.8647301 0.8760745
Mi.3.3h 0.9376814 0.9435996 0.9472219 0.9350667 0.9221300 0.8580008 0.8705455
Tr.3.3h 0.9502117 0.9368774 0.9371499 0.9387189 0.9334435 0.8618212 0.8719487
Ve.3.3h 0.9401800 0.9434063 0.9426560 0.9431705 0.9330434 0.8569441 0.8683547
Da.3.24h 0.8772849 0.8691039 0.8665900 0.8532676 0.8485305 0.9316463 0.9553551
Do.3.24h 0.8677243 0.8548883 0.8564612 0.8459047 0.8395122 0.9237431 0.9498908
Ep.3.24h 0.8646307 0.8569747 0.8532354 0.8374918 0.8346837 0.9243063 0.9462771
Mi.3.24h 0.9342704 0.9269511 0.9290230 0.9242729 0.9166193 0.8971671 0.9156399
Tr.3.24h 0.9428965 0.9297376 0.9323651 0.9371415 0.9276478 0.8522163 0.8665244
Ve.3.24h 0.9319616 0.9211838 0.9235836 0.9263197 0.9189477 0.8376521 0.8496427
Da.4.3h 0.9315938 0.9261831 0.9274573 0.9119609 0.9097962 0.8538268 0.8631940
Do.4.3h 0.9354134 0.9294610 0.9301927 0.9182121 0.9147709 0.8551674 0.8669829
Ep.4.3h 0.9356382 0.9302751 0.9309759 0.9178097 0.9137511 0.8571386 0.8688646
Mi.4.3h 0.9365863 0.9319579 0.9345472 0.9210501 0.9172057 0.8591629 0.8709386
Tr.4.3h 0.9350333 0.9283939 0.9279726 0.9218268 0.9197768 0.8502682 0.8614195
Ve.4.3h 0.9338844 0.9260080 0.9256351 0.9173557 0.9177904 0.8520295 0.8604740
Da.4.24h 0.8705007 0.8643306 0.8623466 0.8419393 0.8411053 0.9210796 0.9416402
Do.4.24h 0.8728096 0.8618681 0.8596784 0.8418757 0.8449840 0.9222374 0.9418656
Ep.4.24h 0.8678853 0.8620130 0.8595948 0.8387362 0.8351311 0.9131622 0.9388200
Mi.4.24h 0.9248046 0.9142562 0.9157945 0.9052425 0.9031867 0.8842275 0.9013035
Tr.4.24h 0.9373094 0.9306386 0.9289520 0.9226275 0.9198345 0.8524954 0.8618636
Ve.4.24h 0.9307327 0.9198047 0.9203412 0.9151239 0.9131088 0.8510282 0.8595660
Da.5.3h 0.9650565 0.9723356 0.9717528 0.9559939 0.9479551 0.8912701 0.9002784
Do.5.3h 1.0000000 0.9693790 0.9661696 0.9585591 0.9520570 0.8925651 0.9068815
Ep.5.3h 0.9693790 1.0000000 0.9753951 0.9617784 0.9523541 0.8894645 0.9013976
Mi.5.3h 0.9661696 0.9753951 1.0000000 0.9596510 0.9507013 0.8871085 0.8977303
Tr.5.3h 0.9585591 0.9617784 0.9596510 1.0000000 0.9638562 0.8879325 0.8943097
Ve.5.3h 0.9520570 0.9523541 0.9507013 0.9638562 1.0000000 0.8946409 0.8859601
Da.5.24h 0.8925651 0.8894645 0.8871085 0.8879325 0.8946409 1.0000000 0.9580919
Do.5.24h 0.9068815 0.9013976 0.8977303 0.8943097 0.8859601 0.9580919 1.0000000
Ep.5.24h 0.9243419 0.9125783 0.9096514 0.8987945 0.8967355 0.9459767 0.9696449
Mi.5.24h 0.9496626 0.9407518 0.9392576 0.9301819 0.9256960 0.9116478 0.9312937
Tr.5.24h 0.9651886 0.9566272 0.9561181 0.9538274 0.9450849 0.8649983 0.8796835
Ve.5.24h 0.9647144 0.9506057 0.9518141 0.9501689 0.9464738 0.8715633 0.8820625
Da.6.3h 0.9373945 0.9390373 0.9407801 0.9293485 0.9207784 0.8604177 0.8733651
Do.6.3h 0.9378199 0.9326288 0.9343186 0.9297346 0.9206431 0.8512567 0.8659833
Ep.6.3h 0.9375098 0.9269979 0.9291656 0.9242408 0.9173349 0.8514789 0.8674289
Mi.6.3h 0.9360418 0.9358858 0.9405758 0.9285997 0.9203421 0.8562558 0.8692824
Tr.6.3h 0.9333678 0.9324236 0.9348023 0.9332263 0.9234733 0.8453685 0.8601925
Ve.6.3h 0.9347465 0.9327287 0.9341111 0.9320686 0.9244895 0.8509493 0.8613065
Da.6.24h 0.8855047 0.8792818 0.8778932 0.8650346 0.8604718 0.9333631 0.9525484
Do.6.24h 0.9065466 0.8963376 0.8969004 0.8886396 0.8823756 0.9084719 0.9363738
Ep.6.24h 0.9053143 0.9029686 0.9034979 0.8923638 0.8849985 0.9119691 0.9359261
Mi.6.24h 0.9225002 0.9203544 0.9238385 0.9188791 0.9095238 0.8829505 0.9020097
Tr.6.24h 0.9232730 0.9078939 0.9131331 0.9150592 0.9067405 0.8335405 0.8482378
Ve.6.24h 0.9299162 0.9290436 0.9312004 0.9337569 0.9259216 0.8534417 0.8635234
Ep.5.24h Mi.5.24h Tr.5.24h Ve.5.24h Da.6.3h Do.6.3h Ep.6.3h
Da.1.3h 0.8823364 0.9083892 0.9096053 0.9108663 0.9528214 0.9444414 0.9453039
Do.1.3h 0.8863643 0.9125159 0.9137166 0.9199656 0.9451679 0.9436710 0.9472987
Ep.1.3h 0.8860914 0.9143077 0.9135395 0.9152889 0.9509857 0.9439061 0.9470185
Mi.1.3h 0.8880706 0.9163623 0.9152429 0.9190236 0.9453242 0.9421237 0.9452692
Tr.1.3h 0.8810528 0.9113003 0.9142400 0.9193266 0.9380025 0.9395025 0.9414110
Ve.1.3h 0.8823772 0.9098228 0.9104863 0.9187054 0.9388753 0.9400808 0.9421992
Da.1.24h 0.9084563 0.8751595 0.8164823 0.8276510 0.8453272 0.8360335 0.8399094
Do.1.24h 0.8644601 0.8342728 0.7804022 0.7910340 0.8033875 0.7959925 0.8000445
Ep.1.24h 0.9180848 0.8796271 0.8180976 0.8281473 0.8398160 0.8314021 0.8357717
Mi.1.24h 0.9160977 0.9308282 0.8832136 0.8908573 0.9045948 0.9041340 0.9059984
Tr.1.24h 0.8829341 0.9125070 0.9191880 0.9239764 0.9332255 0.9371179 0.9360575
Ve.1.24h 0.8788683 0.9061909 0.9120229 0.9187413 0.9305668 0.9345140 0.9361974
Da.2.3h 0.8641728 0.8971613 0.9323852 0.9295813 0.9425640 0.9349955 0.9328630
Do.2.3h 0.8688877 0.9030860 0.9328277 0.9344744 0.9408797 0.9387362 0.9360773
Ep.2.3h 0.8738472 0.9084571 0.9361241 0.9340655 0.9448931 0.9374478 0.9360645
Mi.2.3h 0.8761809 0.9090897 0.9368132 0.9352518 0.9444501 0.9390938 0.9366685
Tr.2.3h 0.8628307 0.9015189 0.9315384 0.9300916 0.9373739 0.9337673 0.9297198
Ve.2.3h 0.8681258 0.9065428 0.9435850 0.9437356 0.9398553 0.9437370 0.9404717
Da.2.24h 0.9190544 0.8924338 0.8451503 0.8512957 0.8675045 0.8535812 0.8548138
Do.2.24h 0.9004744 0.8721566 0.8295416 0.8377178 0.8469662 0.8334325 0.8366993
Ep.2.24h 0.8360639 0.8404452 0.8357042 0.8386796 0.8671174 0.8442316 0.8465603
Mi.2.24h 0.9101047 0.9398966 0.9280635 0.9257563 0.9284145 0.9272572 0.9230838
Tr.2.24h 0.8679059 0.9070190 0.9452214 0.9400059 0.9358771 0.9374282 0.9327742
Ve.2.24h 0.8567502 0.8951939 0.9310607 0.9270453 0.9361519 0.9356307 0.9300138
Da.3.3h 0.8838980 0.9094269 0.9335422 0.9303001 0.9557381 0.9498276 0.9448233
Do.3.3h 0.8905454 0.9185063 0.9403740 0.9423690 0.9519342 0.9540471 0.9545895
Ep.3.3h 0.8837907 0.9136078 0.9377271 0.9330383 0.9590234 0.9550412 0.9514469
Mi.3.3h 0.8795592 0.9098337 0.9344148 0.9292742 0.9557557 0.9517904 0.9472243
Tr.3.3h 0.8893987 0.9219800 0.9430257 0.9437529 0.9513114 0.9539875 0.9552190
Ve.3.3h 0.8798044 0.9141484 0.9424556 0.9379176 0.9545141 0.9559460 0.9500723
Da.3.24h 0.9470549 0.9088599 0.8498121 0.8540418 0.8701109 0.8619189 0.8641699
Do.3.24h 0.9345525 0.8929341 0.8429081 0.8485911 0.8653734 0.8585999 0.8629421
Ep.3.24h 0.9358476 0.8943775 0.8399918 0.8455858 0.8558929 0.8470857 0.8508868
Mi.3.24h 0.9282627 0.9502110 0.9228753 0.9214518 0.9351703 0.9339508 0.9327204
Tr.3.24h 0.8812129 0.9165599 0.9445246 0.9440509 0.9505835 0.9553979 0.9550118
Ve.3.24h 0.8649322 0.9022243 0.9459633 0.9453635 0.9432901 0.9497187 0.9503082
Da.4.3h 0.8771429 0.9062831 0.9160605 0.9198813 0.9623014 0.9533293 0.9559766
Do.4.3h 0.8807072 0.9122567 0.9210579 0.9249312 0.9658456 0.9617866 0.9635270
Ep.4.3h 0.8805630 0.9108887 0.9202987 0.9236802 0.9663264 0.9604958 0.9610347
Mi.4.3h 0.8852534 0.9170427 0.9235001 0.9266499 0.9636879 0.9603695 0.9607597
Tr.4.3h 0.8792379 0.9145889 0.9267644 0.9308786 0.9616502 0.9620895 0.9630300
Ve.4.3h 0.8803820 0.9144789 0.9243517 0.9289531 0.9571330 0.9572930 0.9577612
Da.4.24h 0.9321779 0.9006656 0.8388379 0.8461141 0.8772361 0.8648026 0.8698920
Do.4.24h 0.9373198 0.9022655 0.8400540 0.8489318 0.8727698 0.8628884 0.8691907
Ep.4.24h 0.9267314 0.8966314 0.8349217 0.8404214 0.8764443 0.8636261 0.8694241
Mi.4.24h 0.9202275 0.9411567 0.9069010 0.9094360 0.9336844 0.9320511 0.9343270
Tr.4.24h 0.8819033 0.9167138 0.9355575 0.9356161 0.9563217 0.9583589 0.9571687
Ve.4.24h 0.8781345 0.9092061 0.9244891 0.9278172 0.9500770 0.9536874 0.9535413
Da.5.3h 0.9107682 0.9338877 0.9530954 0.9484859 0.9409377 0.9327901 0.9279505
Do.5.3h 0.9243419 0.9496626 0.9651886 0.9647144 0.9373945 0.9378199 0.9375098
Ep.5.3h 0.9125783 0.9407518 0.9566272 0.9506057 0.9390373 0.9326288 0.9269979
Mi.5.3h 0.9096514 0.9392576 0.9561181 0.9518141 0.9407801 0.9343186 0.9291656
Tr.5.3h 0.8987945 0.9301819 0.9538274 0.9501689 0.9293485 0.9297346 0.9242408
Ve.5.3h 0.8967355 0.9256960 0.9450849 0.9464738 0.9207784 0.9206431 0.9173349
Da.5.24h 0.9459767 0.9116478 0.8649983 0.8715633 0.8604177 0.8512567 0.8514789
Do.5.24h 0.9696449 0.9312937 0.8796835 0.8820625 0.8733651 0.8659833 0.8674289
Ep.5.24h 1.0000000 0.9517809 0.9006070 0.9061531 0.8798706 0.8764147 0.8790893
Mi.5.24h 0.9517809 1.0000000 0.9382894 0.9379439 0.9122563 0.9103209 0.9113306
Tr.5.24h 0.9006070 0.9382894 1.0000000 0.9761087 0.9280009 0.9355447 0.9329795
Ve.5.24h 0.9061531 0.9379439 0.9761087 1.0000000 0.9299330 0.9373599 0.9369506
Da.6.3h 0.8798706 0.9122563 0.9280009 0.9299330 1.0000000 0.9795964 0.9778300
Do.6.3h 0.8764147 0.9103209 0.9355447 0.9373599 0.9795964 1.0000000 0.9790934
Ep.6.3h 0.8790893 0.9113306 0.9329795 0.9369506 0.9778300 0.9790934 1.0000000
Mi.6.3h 0.8788719 0.9136739 0.9290321 0.9307787 0.9818846 0.9770801 0.9751692
Tr.6.3h 0.8703621 0.9092463 0.9343920 0.9350793 0.9811929 0.9821955 0.9786851
Ve.6.3h 0.8722588 0.9087970 0.9317121 0.9333820 0.9779134 0.9780371 0.9748008
Da.6.24h 0.9464180 0.9146991 0.8605729 0.8670814 0.9024818 0.8937170 0.8947411
Do.6.24h 0.9404887 0.9273363 0.8855386 0.8919874 0.9298106 0.9253061 0.9298993
Ep.6.24h 0.9357481 0.9240327 0.8834784 0.8874901 0.9332824 0.9261162 0.9276542
Mi.6.24h 0.9110122 0.9336997 0.9118095 0.9139568 0.9552726 0.9537045 0.9497439
Tr.6.24h 0.8644808 0.9010077 0.9371893 0.9398606 0.9533016 0.9635534 0.9635290
Ve.6.24h 0.8719250 0.9073219 0.9322496 0.9333062 0.9698040 0.9714811 0.9687503
Mi.6.3h Tr.6.3h Ve.6.3h Da.6.24h Do.6.24h Ep.6.24h Mi.6.24h
Da.1.3h 0.9463978 0.9422835 0.9440705 0.8925134 0.9159101 0.9199926 0.9342154
Do.1.3h 0.9439405 0.9405363 0.9423336 0.8903097 0.9158751 0.9166706 0.9321716
Ep.1.3h 0.9450420 0.9414746 0.9424742 0.8933761 0.9178040 0.9184108 0.9322613
Mi.1.3h 0.9451257 0.9400737 0.9427719 0.8916997 0.9154038 0.9168236 0.9326039
Tr.1.3h 0.9388050 0.9391404 0.9417382 0.8841079 0.9086894 0.9097779 0.9304202
Ve.1.3h 0.9406922 0.9386595 0.9419609 0.8844630 0.9125617 0.9129955 0.9314719
Da.1.24h 0.8429570 0.8276872 0.8306427 0.9367602 0.8969984 0.9008743 0.8642544
Do.1.24h 0.8018434 0.7883463 0.7914024 0.8797782 0.8543680 0.8544273 0.8235460
Ep.1.24h 0.8367056 0.8229473 0.8248255 0.9368384 0.9004142 0.9003598 0.8608726
Mi.1.24h 0.9082505 0.9017494 0.9047126 0.9153958 0.9231196 0.9269639 0.9345829
Tr.1.24h 0.9346481 0.9370284 0.9389949 0.8807883 0.9024349 0.9050811 0.9283707
Ve.1.24h 0.9334633 0.9344558 0.9376692 0.8767962 0.9008391 0.9041244 0.9250366
Da.2.3h 0.9337609 0.9326991 0.9306937 0.8554048 0.8837143 0.8861732 0.9101360
Do.2.3h 0.9377295 0.9369869 0.9363276 0.8591245 0.8902252 0.8911879 0.9163904
Ep.2.3h 0.9395844 0.9366111 0.9361856 0.8637816 0.8919741 0.8938287 0.9156257
Mi.2.3h 0.9408465 0.9375374 0.9379729 0.8647905 0.8909499 0.8927932 0.9172329
Tr.2.3h 0.9343475 0.9344040 0.9342082 0.8559304 0.8871698 0.8879388 0.9153063
Ve.2.3h 0.9385464 0.9424575 0.9408513 0.8557232 0.8906804 0.8888703 0.9188890
Da.2.24h 0.8601540 0.8467084 0.8470566 0.9422365 0.9076868 0.9082624 0.8758025
Do.2.24h 0.8391274 0.8257305 0.8256720 0.9196746 0.8827186 0.8825277 0.8509642
Ep.2.24h 0.8519810 0.8371828 0.8345320 0.8500187 0.8412057 0.8452743 0.8353814
Mi.2.24h 0.9268302 0.9277930 0.9251535 0.8947999 0.9211467 0.9210295 0.9445596
Tr.2.24h 0.9336252 0.9393935 0.9346754 0.8545366 0.8879782 0.8880871 0.9189094
Ve.2.24h 0.9335234 0.9387152 0.9350717 0.8487196 0.8868250 0.8880177 0.9184895
Da.3.3h 0.9517162 0.9516417 0.9489812 0.8804099 0.9030382 0.9111267 0.9328823
Do.3.3h 0.9504321 0.9519361 0.9511736 0.8812579 0.9104198 0.9094608 0.9336674
Ep.3.3h 0.9540049 0.9573729 0.9533672 0.8812495 0.9094570 0.9139480 0.9366198
Mi.3.3h 0.9544246 0.9545789 0.9506932 0.8774172 0.9068410 0.9124990 0.9357577
Tr.3.3h 0.9508483 0.9570309 0.9558454 0.8787789 0.9145399 0.9113835 0.9383897
Ve.3.3h 0.9545701 0.9632214 0.9579041 0.8736104 0.9070158 0.9104108 0.9409337
Da.3.24h 0.8648663 0.8549520 0.8551449 0.9604804 0.9374232 0.9334199 0.8978898
Do.3.24h 0.8611292 0.8525929 0.8507649 0.9518485 0.9339138 0.9295633 0.8925991
Ep.3.24h 0.8506788 0.8412836 0.8404771 0.9520654 0.9222519 0.9169379 0.8769434
Mi.3.24h 0.9345278 0.9344653 0.9345760 0.9191496 0.9424562 0.9419878 0.9604872
Tr.3.24h 0.9507202 0.9580823 0.9556189 0.8724314 0.9108917 0.9091810 0.9410499
Ve.3.24h 0.9424001 0.9515675 0.9476778 0.8570419 0.8962989 0.8913668 0.9224016
Da.4.3h 0.9569386 0.9528389 0.9544795 0.8879780 0.9129494 0.9177314 0.9349239
Do.4.3h 0.9637693 0.9634865 0.9634370 0.8906466 0.9217208 0.9248859 0.9443170
Ep.4.3h 0.9629552 0.9605551 0.9610375 0.8925028 0.9190624 0.9236646 0.9417809
Mi.4.3h 0.9654311 0.9627351 0.9631553 0.8951565 0.9225841 0.9265042 0.9463184
Tr.4.3h 0.9634194 0.9672528 0.9667625 0.8866752 0.9193438 0.9205284 0.9450070
Ve.4.3h 0.9587618 0.9605149 0.9627477 0.8861563 0.9145806 0.9178257 0.9401703
Da.4.24h 0.8732082 0.8600761 0.8601592 0.9620683 0.9345763 0.9343298 0.8944419
Do.4.24h 0.8698553 0.8578694 0.8592926 0.9598673 0.9361657 0.9335314 0.8943044
Ep.4.24h 0.8725630 0.8595924 0.8588233 0.9559787 0.9346807 0.9357111 0.8936960
Mi.4.24h 0.9357304 0.9331753 0.9340499 0.9199268 0.9437077 0.9448748 0.9576235
Tr.4.24h 0.9572998 0.9622841 0.9624066 0.8846248 0.9126086 0.9154502 0.9427770
Ve.4.24h 0.9529996 0.9564594 0.9579247 0.8828708 0.9097703 0.9145750 0.9393327
Da.5.3h 0.9364268 0.9315271 0.9299057 0.8812780 0.8930055 0.9009265 0.9176514
Do.5.3h 0.9360418 0.9333678 0.9347465 0.8855047 0.9065466 0.9053143 0.9225002
Ep.5.3h 0.9358858 0.9324236 0.9327287 0.8792818 0.8963376 0.9029686 0.9203544
Mi.5.3h 0.9405758 0.9348023 0.9341111 0.8778932 0.8969004 0.9034979 0.9238385
Tr.5.3h 0.9285997 0.9332263 0.9320686 0.8650346 0.8886396 0.8923638 0.9188791
Ve.5.3h 0.9203421 0.9234733 0.9244895 0.8604718 0.8823756 0.8849985 0.9095238
Da.5.24h 0.8562558 0.8453685 0.8509493 0.9333631 0.9084719 0.9119691 0.8829505
Do.5.24h 0.8692824 0.8601925 0.8613065 0.9525484 0.9363738 0.9359261 0.9020097
Ep.5.24h 0.8788719 0.8703621 0.8722588 0.9464180 0.9404887 0.9357481 0.9110122
Mi.5.24h 0.9136739 0.9092463 0.9087970 0.9146991 0.9273363 0.9240327 0.9336997
Tr.5.24h 0.9290321 0.9343920 0.9317121 0.8605729 0.8855386 0.8834784 0.9118095
Ve.5.24h 0.9307787 0.9350793 0.9333820 0.8670814 0.8919874 0.8874901 0.9139568
Da.6.3h 0.9818846 0.9811929 0.9779134 0.9024818 0.9298106 0.9332824 0.9552726
Do.6.3h 0.9770801 0.9821955 0.9780371 0.8937170 0.9253061 0.9261162 0.9537045
Ep.6.3h 0.9751692 0.9786851 0.9748008 0.8947411 0.9298993 0.9276542 0.9497439
Mi.6.3h 1.0000000 0.9810168 0.9783297 0.8977936 0.9267236 0.9311988 0.9555738
Tr.6.3h 0.9810168 1.0000000 0.9848858 0.8891626 0.9245968 0.9266621 0.9577107
Ve.6.3h 0.9783297 0.9848858 1.0000000 0.8891417 0.9215080 0.9255599 0.9555680
Da.6.24h 0.8977936 0.8891626 0.8891417 1.0000000 0.9603130 0.9580687 0.9258288
Do.6.24h 0.9267236 0.9245968 0.9215080 0.9603130 1.0000000 0.9697828 0.9534004
Ep.6.24h 0.9311988 0.9266621 0.9255599 0.9580687 0.9697828 1.0000000 0.9575814
Mi.6.24h 0.9555738 0.9577107 0.9555680 0.9258288 0.9534004 0.9575814 1.0000000
Tr.6.24h 0.9526645 0.9652425 0.9588014 0.8747632 0.9124389 0.9063974 0.9395151
Ve.6.24h 0.9707782 0.9774814 0.9758510 0.8868778 0.9203909 0.9230490 0.9538796
Tr.6.24h Ve.6.24h
Da.1.3h 0.9252461 0.9402979
Do.1.3h 0.9320758 0.9375057
Ep.1.3h 0.9276547 0.9379633
Mi.1.3h 0.9277794 0.9366205
Tr.1.3h 0.9288798 0.9352638
Ve.1.3h 0.9279800 0.9364364
Da.1.24h 0.8218928 0.8276129
Do.1.24h 0.7843357 0.7902507
Ep.1.24h 0.8190736 0.8218320
Mi.1.24h 0.8940943 0.9011529
Tr.1.24h 0.9306204 0.9348534
Ve.1.24h 0.9282138 0.9343277
Da.2.3h 0.9245144 0.9334456
Do.2.3h 0.9266815 0.9365340
Ep.2.3h 0.9240755 0.9364668
Mi.2.3h 0.9242409 0.9390819
Tr.2.3h 0.9214547 0.9359471
Ve.2.3h 0.9349693 0.9391976
Da.2.24h 0.8352300 0.8452882
Do.2.24h 0.8190487 0.8259444
Ep.2.24h 0.8276731 0.8357285
Mi.2.24h 0.9175878 0.9259933
Tr.2.24h 0.9322201 0.9379377
Ve.2.24h 0.9268185 0.9397354
Da.3.3h 0.9379919 0.9496691
Do.3.3h 0.9440045 0.9476678
Ep.3.3h 0.9424418 0.9548709
Mi.3.3h 0.9391237 0.9506285
Tr.3.3h 0.9473078 0.9535113
Ve.3.3h 0.9476530 0.9580342
Da.3.24h 0.8467667 0.8546983
Do.3.24h 0.8496115 0.8535577
Ep.3.24h 0.8366218 0.8412829
Mi.3.24h 0.9248102 0.9338696
Tr.3.24h 0.9526619 0.9550625
Ve.3.24h 0.9557961 0.9509475
Da.4.3h 0.9338249 0.9482949
Do.4.3h 0.9429781 0.9572719
Ep.4.3h 0.9380089 0.9539978
Mi.4.3h 0.9403578 0.9562418
Tr.4.3h 0.9466275 0.9606959
Ve.4.3h 0.9404918 0.9545815
Da.4.24h 0.8441093 0.8578100
Do.4.24h 0.8462306 0.8570850
Ep.4.24h 0.8421687 0.8554175
Mi.4.24h 0.9208149 0.9314514
Tr.4.24h 0.9482093 0.9581444
Ve.4.24h 0.9415586 0.9536817
Da.5.3h 0.9108645 0.9271688
Do.5.3h 0.9232730 0.9299162
Ep.5.3h 0.9078939 0.9290436
Mi.5.3h 0.9131331 0.9312004
Tr.5.3h 0.9150592 0.9337569
Ve.5.3h 0.9067405 0.9259216
Da.5.24h 0.8335405 0.8534417
Do.5.24h 0.8482378 0.8635234
Ep.5.24h 0.8644808 0.8719250
Mi.5.24h 0.9010077 0.9073219
Tr.5.24h 0.9371893 0.9322496
Ve.5.24h 0.9398606 0.9333062
Da.6.3h 0.9533016 0.9698040
Do.6.3h 0.9635534 0.9714811
Ep.6.3h 0.9635290 0.9687503
Mi.6.3h 0.9526645 0.9707782
Tr.6.3h 0.9652425 0.9774814
Ve.6.3h 0.9588014 0.9758510
Da.6.24h 0.8747632 0.8868778
Do.6.24h 0.9124389 0.9203909
Ep.6.24h 0.9063974 0.9230490
Mi.6.24h 0.9395151 0.9538796
Tr.6.24h 1.0000000 0.9611305
Ve.6.24h 0.9611305 1.0000000
Da.1.3h Do.1.3h E.1.3 M.1.3 T.1.3 V.1.3 Da.1.24h Do.1.24h E.1.2 M.1.2
Da.1.3h 1
Do.1.3h B 1
Ep.1.3h B B 1
Mi.1.3h B B B 1
Tr.1.3h B B B B 1
Ve.1.3h B B B B B 1
Da.1.24h + + + + + + 1
Do.1.24h + + + + + + * 1
Ep.1.24h + + + + + + B * 1
Mi.1.24h * B * B B B * + * 1
Tr.1.24h B B B B B B + + + B
Ve.1.24h B B B B B B + + + B
Da.2.3h * + * + + + , , , +
Do.2.3h * * + * + * , , , +
Ep.2.3h * * * * * * + , + +
Mi.2.3h * * * * * * + , + +
Tr.2.3h + + + + + + , , , +
Ve.2.3h * * * * * * , , , +
Da.2.24h + + + + + + * + * +
Do.2.24h + + + + + + * + * +
Ep.2.24h + + + + + + + , + +
Mi.2.24h * * * * + * + , + +
Tr.2.24h * + + + + + , , , +
Ve.2.24h + + + + + + , , , +
Da.3.3h * * * * * * + , + +
Do.3.3h * * * * * * + , + +
Ep.3.3h * * * * * * + , + +
Mi.3.3h * * * * * * + , + +
Tr.3.3h * * * * * * + , + +
Ve.3.3h * * * * * * + , + +
Da.3.24h + + + + + + * + * *
Do.3.24h + + + + + + * + * +
Ep.3.24h + + + + + + * + * +
Mi.3.24h * * * * * * + + + *
Tr.3.24h * * * * * * + , + +
Ve.3.24h * * * * * * , , , +
Da.4.3h B B B B B B + + + *
Do.4.3h B B B B B B + + + *
Ep.4.3h B B B B B B + + + *
Mi.4.3h B B B B B B + + + *
Tr.4.3h B B B B B B + + + *
Ve.4.3h B B B B B B + + + *
Da.4.24h + + + + + + B + B *
Do.4.24h + + + + + + B + B *
Ep.4.24h + + + + + + B + B *
Mi.4.24h * B B B B B + + + B
Tr.4.24h B B B B B B + + + *
Ve.4.24h B B B B B B + + + *
Da.5.3h * * * * * * + + + +
Do.5.3h * * * * * * + + + *
Ep.5.3h * * * * * * + , + +
Mi.5.3h * * * * * * + , + +
Tr.5.3h * * * * * * + , + +
Ve.5.3h * * * * * * + , + +
Da.5.24h + + + + + + * + * +
Do.5.24h + + + + + + * + * +
Ep.5.24h + + + + + + * + * *
Mi.5.24h * * * * * * + + + *
Tr.5.24h * * * * * * + , + +
Ve.5.24h * * * * * * + , + +
Da.6.3h B * B * * * + + + *
Do.6.3h * * * * * * + , + *
Ep.6.3h * * * * * * + + + *
Mi.6.3h * * * * * * + + + *
Tr.6.3h * * * * * * + , + *
Ve.6.3h * * * * * * + , + *
Da.6.24h + + + + + + * + * *
Do.6.24h * * * * * * + + * *
Ep.6.24h * * * * * * * + * *
Mi.6.24h * * * * * * + + + *
Tr.6.24h * * * * * * + , + +
Ve.6.24h * * * * * * + , + *
T.1.2 V.1.2 Da.2.3h Do.2.3h E.2.3 M.2.3 T.2.3 V.2.3 Da.2.24h Do.2.24h
Da.1.3h
Do.1.3h
Ep.1.3h
Mi.1.3h
Tr.1.3h
Ve.1.3h
Da.1.24h
Do.1.24h
Ep.1.24h
Mi.1.24h
Tr.1.24h 1
Ve.1.24h B 1
Da.2.3h + + 1
Do.2.3h + + B 1
Ep.2.3h + + B B 1
Mi.2.3h + + B B B 1
Tr.2.3h + + B B B B 1
Ve.2.3h + + B B B B B 1
Da.2.24h + + + + + + + + 1
Do.2.24h + + + + + + + + B 1
Ep.2.24h + + + + + + + + + +
Mi.2.24h + + * * * * * B + +
Tr.2.24h + + B B B B B B + +
Ve.2.24h + + B B B B B B + +
Da.3.3h * * * * B B * * + +
Do.3.3h * * * * * * * B + +
Ep.3.3h * * * * B B * * + +
Mi.3.3h * * * * B B * * + +
Tr.3.3h * * * * * B * B + +
Ve.3.3h * * * * * * * B + +
Da.3.24h + + + + + + + + * *
Do.3.24h + + + + + + + + * *
Ep.3.24h + + + + + + + + B *
Mi.3.24h * * * * * * * * + +
Tr.3.24h * * * * * * * B + +
Ve.3.24h * * * * * * * B + +
Da.4.3h B B * * * * * * + +
Do.4.3h B B * * * * * * + +
Ep.4.3h B B * * * * * * + +
Mi.4.3h B B * * * * * * + +
Tr.4.3h B B * * * * * * + +
Ve.4.3h B B * * * * * * + +
Da.4.24h + + + + + + + + * *
Do.4.24h + + + + + + + + * *
Ep.4.24h + + + + + + + + * *
Mi.4.24h B * + + + + + + + +
Tr.4.24h B B * * * * * * + +
Ve.4.24h B B * * * * * * + +
Da.5.3h * * * * * * * * + +
Do.5.3h * * * * * * * * + +
Ep.5.3h * * * * * * * * + +
Mi.5.3h * * * * * * * * + +
Tr.5.3h * * * * * * * * + +
Ve.5.3h * * * * * * * * + +
Da.5.24h + + + + + + + + * *
Do.5.24h + + + + + + + + * *
Ep.5.24h + + + + + + + + * *
Mi.5.24h * * + * * * * * + +
Tr.5.24h * * * * * * * * + +
Ve.5.24h * * * * * * * * + +
Da.6.3h * * * * * * * * + +
Do.6.3h * * * * * * * * + +
Ep.6.3h * * * * * * * * + +
Mi.6.3h * * * * * * * * + +
Tr.6.3h * * * * * * * * + +
Ve.6.3h * * * * * * * * + +
Da.6.24h + + + + + + + + * *
Do.6.24h * * + + + + + + * +
Ep.6.24h * * + + + + + + * +
Mi.6.24h * * * * * * * * + +
Tr.6.24h * * * * * * * * + +
Ve.6.24h * * * * * * * * + +
E.2.2 M.2.2 T.2.2 V.2.2 Da.3.3h Do.3.3h E.3.3 M.3.3 T.3.3 V.3.3
Da.1.3h
Do.1.3h
Ep.1.3h
Mi.1.3h
Tr.1.3h
Ve.1.3h
Da.1.24h
Do.1.24h
Ep.1.24h
Mi.1.24h
Tr.1.24h
Ve.1.24h
Da.2.3h
Do.2.3h
Ep.2.3h
Mi.2.3h
Tr.2.3h
Ve.2.3h
Da.2.24h
Do.2.24h
Ep.2.24h 1
Mi.2.24h + 1
Tr.2.24h + B 1
Ve.2.24h + B B 1
Da.3.3h + * * * 1
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Ep.3.3h + * * * B B 1
Mi.3.3h + * * * B B B 1
Tr.3.3h + * * * B B B B 1
Ve.3.3h + * B * B B B B B 1
Da.3.24h + + + + + + + + + +
Do.3.24h + + + + + + + + + +
Ep.3.24h + + + + + + + + + +
Mi.3.24h + B * * * B * * B B
Tr.3.24h + * B * B B B B B B
Ve.3.24h + * B * B B B B B B
Da.4.3h + * * * * * * * * *
Do.4.3h + * * * * B * * B *
Ep.4.3h + * * * * * * * * *
Mi.4.3h + * * * * * * * B *
Tr.4.3h + * * * * * * * B *
Ve.4.3h + * * * * * * * B *
Da.4.24h + + + + + + + + + +
Do.4.24h + + + + + + + + + +
Ep.4.24h + + + + + + + + + +
Mi.4.24h + * + + * * * * * *
Tr.4.24h + * * * * * * * B *
Ve.4.24h + * * * * * * * * *
Da.5.3h + * * * * * * * * *
Do.5.3h + * * * * B * * B *
Ep.5.3h + * * * * * * * * *
Mi.5.3h + * * * * * * * * *
Tr.5.3h + * * * * * * * * *
Ve.5.3h + * * * * * * * * *
Da.5.24h + + + + + + + + + +
Do.5.24h + + + + + + + + + +
Ep.5.24h + * + + + + + + + +
Mi.5.24h + * * + * * * * * *
Tr.5.24h + * * * * * * * * *
Ve.5.24h + * * * * * * * * *
Da.6.3h + * * * B B B B B B
Do.6.3h + * * * * B B B B B
Ep.6.3h + * * * * B B * B B
Mi.6.3h + * * * B B B B B B
Tr.6.3h + * * * B B B B B B
Ve.6.3h + * * * * B B B B B
Da.6.24h + + + + + + + + + +
Do.6.24h + * + + * * * * * *
Ep.6.24h + * + + * * * * * *
Mi.6.24h + * * * * * * * * *
Tr.6.24h + * * * * * * * * *
Ve.6.24h + * * * * * B B B B
Da.3.24h Do.3.24h E.3.2 M.3.2 T.3.2 V.3.2 Da.4.3h Do.4.3h E.4.3 M.4.3
Da.1.3h
Do.1.3h
Ep.1.3h
Mi.1.3h
Tr.1.3h
Ve.1.3h
Da.1.24h
Do.1.24h
Ep.1.24h
Mi.1.24h
Tr.1.24h
Ve.1.24h
Da.2.3h
Do.2.3h
Ep.2.3h
Mi.2.3h
Tr.2.3h
Ve.2.3h
Da.2.24h
Do.2.24h
Ep.2.24h
Mi.2.24h
Tr.2.24h
Ve.2.24h
Da.3.3h
Do.3.3h
Ep.3.3h
Mi.3.3h
Tr.3.3h
Ve.3.3h
Da.3.24h 1
Do.3.24h B 1
Ep.3.24h B B 1
Mi.3.24h * * * 1
Tr.3.24h + + + B 1
Ve.3.24h + + + * B 1
Da.4.3h + + + * * * 1
Do.4.3h + + + * * * B 1
Ep.4.3h + + + * * * B B 1
Mi.4.3h + + + * * * B B B 1
Tr.4.3h + + + * B * B B B B
Ve.4.3h + + + * * * B B B B
Da.4.24h B * B + + + + + + +
Do.4.24h B * B + + + + + + +
Ep.4.24h * * * + + + + + + +
Mi.4.24h * + + B * * B B B B
Tr.4.24h + + + * B * B B B B
Ve.4.24h + + + * * * B B B B
Da.5.3h + + + * * * * * * *
Do.5.3h + + + * * * * * * *
Ep.5.3h + + + * * * * * * *
Mi.5.3h + + + * * * * * * *
Tr.5.3h + + + * * * * * * *
Ve.5.3h + + + * * * * * * *
Da.5.24h * * * + + + + + + +
Do.5.24h B * * * + + + + + +
Ep.5.24h * * * * + + + + + +
Mi.5.24h * + + B * * * * * *
Tr.5.24h + + + * * * * * * *
Ve.5.24h + + + * * * * * * *
Da.6.3h + + + * B * B B B B
Do.6.3h + + + * B * B B B B
Ep.6.3h + + + * B B B B B B
Mi.6.3h + + + * B * B B B B
Tr.6.3h + + + * B B B B B B
Ve.6.3h + + + * B * B B B B
Da.6.24h B B B * + + + + + +
Do.6.24h * * * * * + * * * *
Ep.6.24h * * * * * + * * * *
Mi.6.24h + + + B * * * * * *
Tr.6.24h + + + * B B * * * *
Ve.6.24h + + + * B B * B B B
T.4.3 V.4.3 Da.4.24h Do.4.24h E.4.2 M.4.2 T.4.2 V.4.2 Da.5.3h Do.5.3h
Da.1.3h
Do.1.3h
Ep.1.3h
Mi.1.3h
Tr.1.3h
Ve.1.3h
Da.1.24h
Do.1.24h
Ep.1.24h
Mi.1.24h
Tr.1.24h
Ve.1.24h
Da.2.3h
Do.2.3h
Ep.2.3h
Mi.2.3h
Tr.2.3h
Ve.2.3h
Da.2.24h
Do.2.24h
Ep.2.24h
Mi.2.24h
Tr.2.24h
Ve.2.24h
Da.3.3h
Do.3.3h
Ep.3.3h
Mi.3.3h
Tr.3.3h
Ve.3.3h
Da.3.24h
Do.3.24h
Ep.3.24h
Mi.3.24h
Tr.3.24h
Ve.3.24h
Da.4.3h
Do.4.3h
Ep.4.3h
Mi.4.3h
Tr.4.3h 1
Ve.4.3h B 1
Da.4.24h + + 1
Do.4.24h + + B 1
Ep.4.24h + + B B 1
Mi.4.24h B B * * * 1
Tr.4.24h B B + + + B 1
Ve.4.24h B B + + + B B 1
Da.5.3h * * + + + * * * 1
Do.5.3h * * + + + * * * B 1
Ep.5.3h * * + + + * * * B B
Mi.5.3h * * + + + * * * B B
Tr.5.3h * * + + + * * * B B
Ve.5.3h * * + + + * * * * B
Da.5.24h + + * * * + + + + +
Do.5.24h + + * * * * + + * *
Ep.5.24h + + * * * * + + * *
Mi.5.24h * * * * + * * * * *
Tr.5.24h * * + + + * * * B B
Ve.5.24h * * + + + * * * * B
Da.6.3h B B + + + * B B * *
Do.6.3h B B + + + * B B * *
Ep.6.3h B B + + + * B B * *
Mi.6.3h B B + + + * B B * *
Tr.6.3h B B + + + * B B * *
Ve.6.3h B B + + + * B B * *
Da.6.24h + + B B B * + + + +
Do.6.24h * * * * * * * * + *
Ep.6.24h * * * * * * * * * *
Mi.6.24h * * + + + B * * * *
Tr.6.24h * * + + + * * * * *
Ve.6.24h B B + + + * B B * *
E.5.3 M.5.3 T.5.3 V.5.3 Da.5.24h Do.5.24h E.5.2 M.5.2 T.5.2 V.5.2
Da.1.3h
Do.1.3h
Ep.1.3h
Mi.1.3h
Tr.1.3h
Ve.1.3h
Da.1.24h
Do.1.24h
Ep.1.24h
Mi.1.24h
Tr.1.24h
Ve.1.24h
Da.2.3h
Do.2.3h
Ep.2.3h
Mi.2.3h
Tr.2.3h
Ve.2.3h
Da.2.24h
Do.2.24h
Ep.2.24h
Mi.2.24h
Tr.2.24h
Ve.2.24h
Da.3.3h
Do.3.3h
Ep.3.3h
Mi.3.3h
Tr.3.3h
Ve.3.3h
Da.3.24h
Do.3.24h
Ep.3.24h
Mi.3.24h
Tr.3.24h
Ve.3.24h
Da.4.3h
Do.4.3h
Ep.4.3h
Mi.4.3h
Tr.4.3h
Ve.4.3h
Da.4.24h
Do.4.24h
Ep.4.24h
Mi.4.24h
Tr.4.24h
Ve.4.24h
Da.5.3h
Do.5.3h
Ep.5.3h 1
Mi.5.3h B 1
Tr.5.3h B B 1
Ve.5.3h B B B 1
Da.5.24h + + + + 1
Do.5.24h * + + + B 1
Ep.5.24h * * + + * B 1
Mi.5.24h * * * * * * B 1
Tr.5.24h B B B * + + * * 1
Ve.5.24h B B B * + + * * B 1
Da.6.3h * * * * + + + * * *
Do.6.3h * * * * + + + * * *
Ep.6.3h * * * * + + + * * *
Mi.6.3h * * * * + + + * * *
Tr.6.3h * * * * + + + * * *
Ve.6.3h * * * * + + + * * *
Da.6.24h + + + + * B * * + +
Do.6.24h + + + + * * * * + +
Ep.6.24h * * + + * * * * + +
Mi.6.24h * * * * + * * * * *
Tr.6.24h * * * * + + + * * *
Ve.6.24h * * * * + + + * * *
Da.6.3h Do.6.3h E.6.3 M.6.3 T.6.3 V.6.3 Da.6.24h Do.6.24h E.6.2 M.6.2
Da.1.3h
Do.1.3h
Ep.1.3h
Mi.1.3h
Tr.1.3h
Ve.1.3h
Da.1.24h
Do.1.24h
Ep.1.24h
Mi.1.24h
Tr.1.24h
Ve.1.24h
Da.2.3h
Do.2.3h
Ep.2.3h
Mi.2.3h
Tr.2.3h
Ve.2.3h
Da.2.24h
Do.2.24h
Ep.2.24h
Mi.2.24h
Tr.2.24h
Ve.2.24h
Da.3.3h
Do.3.3h
Ep.3.3h
Mi.3.3h
Tr.3.3h
Ve.3.3h
Da.3.24h
Do.3.24h
Ep.3.24h
Mi.3.24h
Tr.3.24h
Ve.3.24h
Da.4.3h
Do.4.3h
Ep.4.3h
Mi.4.3h
Tr.4.3h
Ve.4.3h
Da.4.24h
Do.4.24h
Ep.4.24h
Mi.4.24h
Tr.4.24h
Ve.4.24h
Da.5.3h
Do.5.3h
Ep.5.3h
Mi.5.3h
Tr.5.3h
Ve.5.3h
Da.5.24h
Do.5.24h
Ep.5.24h
Mi.5.24h
Tr.5.24h
Ve.5.24h
Da.6.3h 1
Do.6.3h B 1
Ep.6.3h B B 1
Mi.6.3h B B B 1
Tr.6.3h B B B B 1
Ve.6.3h B B B B B 1
Da.6.24h * + + + + + 1
Do.6.24h * * * * * * B 1
Ep.6.24h * * * * * * B B 1
Mi.6.24h B B * B B B * B B 1
Tr.6.24h B B B B B B + * * *
Ve.6.24h B B B B B B + * * B
T.6.2 V.6.2
Da.1.3h
Do.1.3h
Ep.1.3h
Mi.1.3h
Tr.1.3h
Ve.1.3h
Da.1.24h
Do.1.24h
Ep.1.24h
Mi.1.24h
Tr.1.24h
Ve.1.24h
Da.2.3h
Do.2.3h
Ep.2.3h
Mi.2.3h
Tr.2.3h
Ve.2.3h
Da.2.24h
Do.2.24h
Ep.2.24h
Mi.2.24h
Tr.2.24h
Ve.2.24h
Da.3.3h
Do.3.3h
Ep.3.3h
Mi.3.3h
Tr.3.3h
Ve.3.3h
Da.3.24h
Do.3.24h
Ep.3.24h
Mi.3.24h
Tr.3.24h
Ve.3.24h
Da.4.3h
Do.4.3h
Ep.4.3h
Mi.4.3h
Tr.4.3h
Ve.4.3h
Da.4.24h
Do.4.24h
Ep.4.24h
Mi.4.24h
Tr.4.24h
Ve.4.24h
Da.5.3h
Do.5.3h
Ep.5.3h
Mi.5.3h
Tr.5.3h
Ve.5.3h
Da.5.24h
Do.5.24h
Ep.5.24h
Mi.5.24h
Tr.5.24h
Ve.5.24h
Da.6.3h
Do.6.3h
Ep.6.3h
Mi.6.3h
Tr.6.3h
Ve.6.3h
Da.6.24h
Do.6.24h
Ep.6.24h
Mi.6.24h
Tr.6.24h 1
Ve.6.24h B 1
attr(,"legend")
[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1[1] 0.7484706 1.0000000
GO analysis
sessionInfo()R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8
[2] LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
attached base packages:
[1] stats4 grid stats graphics grDevices utils datasets
[8] methods base
other attached packages:
[1] pheatmap_1.0.12
[2] Cormotif_1.42.0
[3] affy_1.74.0
[4] Hmisc_4.7-2
[5] Formula_1.2-4
[6] survival_3.5-0
[7] corrplot_0.92
[8] ggrepel_0.9.3
[9] cowplot_1.1.1
[10] Homo.sapiens_1.3.1
[11] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[12] org.Hs.eg.db_3.15.0
[13] GO.db_3.15.0
[14] OrganismDbi_1.38.1
[15] GenomicFeatures_1.48.4
[16] GenomicRanges_1.48.0
[17] GenomeInfoDb_1.32.4
[18] AnnotationDbi_1.58.0
[19] IRanges_2.30.1
[20] S4Vectors_0.34.0
[21] biomaRt_2.52.0
[22] scales_1.2.1
[23] forcats_1.0.0
[24] stringr_1.5.0
[25] dplyr_1.1.0
[26] purrr_1.0.1
[27] readr_2.1.3
[28] tidyr_1.3.0
[29] tibble_3.1.8
[30] tidyverse_1.3.2
[31] AnnotationHub_3.4.0
[32] BiocFileCache_2.4.0
[33] dbplyr_2.3.0
[34] devtools_2.4.5
[35] usethis_2.1.6
[36] reshape2_1.4.4
[37] gridExtra_2.3
[38] HTSFilter_1.36.0
[39] VennDiagram_1.7.3
[40] futile.logger_1.4.3
[41] mixOmics_6.20.0
[42] ggplot2_3.4.0
[43] lattice_0.20-45
[44] MASS_7.3-58.2
[45] RColorBrewer_1.1-3
[46] edgeR_3.38.4
[47] limma_3.52.4
[48] Biobase_2.56.0
[49] BiocGenerics_0.42.0
[50] workflowr_1.7.0
loaded via a namespace (and not attached):
[1] rappdirs_0.3.3 rtracklayer_1.56.1
[3] bit64_4.0.5 knitr_1.42
[5] DelayedArray_0.22.0 data.table_1.14.6
[7] rpart_4.1.19 KEGGREST_1.36.3
[9] RCurl_1.98-1.10 generics_0.1.3
[11] preprocessCore_1.58.0 callr_3.7.3
[13] lambda.r_1.2.4 RSQLite_2.2.20
[15] bit_4.0.5 tzdb_0.3.0
[17] xml2_1.3.3 lubridate_1.9.1
[19] httpuv_1.6.8 SummarizedExperiment_1.26.1
[21] assertthat_0.2.1 gargle_1.3.0
[23] xfun_0.37 hms_1.1.2
[25] jquerylib_0.1.4 evaluate_0.20
[27] promises_1.2.0.1 fansi_1.0.4
[29] restfulr_0.0.15 progress_1.2.2
[31] readxl_1.4.1 igraph_1.3.5
[33] DBI_1.1.3 geneplotter_1.74.0
[35] htmlwidgets_1.6.1 rARPACK_0.11-0
[37] googledrive_2.0.0 ellipsis_0.3.2
[39] RSpectra_0.16-1 backports_1.4.1
[41] annotate_1.74.0 deldir_1.0-6
[43] MatrixGenerics_1.8.1 vctrs_0.5.2
[45] remotes_2.4.2 cachem_1.0.6
[47] withr_2.5.0 checkmate_2.1.0
[49] GenomicAlignments_1.32.1 prettyunits_1.1.1
[51] cluster_2.1.4 crayon_1.5.2
[53] ellipse_0.4.3 genefilter_1.78.0
[55] pkgconfig_2.0.3 labeling_0.4.2
[57] pkgload_1.3.2 nnet_7.3-18
[59] rlang_1.0.6 lifecycle_1.0.3
[61] miniUI_0.1.1.1 filelock_1.0.2
[63] affyio_1.66.0 modelr_0.1.10
[65] cellranger_1.1.0 rprojroot_2.0.3
[67] matrixStats_0.63.0 graph_1.74.0
[69] Matrix_1.5-3 reprex_2.0.2
[71] base64enc_0.1-3 whisker_0.4.1
[73] processx_3.8.0 googlesheets4_1.0.1
[75] png_0.1-8 viridisLite_0.4.1
[77] rjson_0.2.21 bitops_1.0-7
[79] getPass_0.2-2 Biostrings_2.64.1
[81] blob_1.2.3 jpeg_0.1-10
[83] memoise_2.0.1 magrittr_2.0.3
[85] plyr_1.8.8 zlibbioc_1.42.0
[87] compiler_4.2.2 BiocIO_1.6.0
[89] DESeq2_1.36.0 Rsamtools_2.12.0
[91] cli_3.6.0 XVector_0.36.0
[93] urlchecker_1.0.1 ps_1.7.2
[95] htmlTable_2.4.1 formatR_1.14
[97] tidyselect_1.2.0 stringi_1.7.12
[99] highr_0.10 yaml_2.3.7
[101] locfit_1.5-9.7 latticeExtra_0.6-30
[103] sass_0.4.5 tools_4.2.2
[105] timechange_0.2.0 parallel_4.2.2
[107] rstudioapi_0.14 foreign_0.8-84
[109] git2r_0.31.0 farver_2.1.1
[111] digest_0.6.31 BiocManager_1.30.19
[113] shiny_1.7.4 Rcpp_1.0.10
[115] broom_1.0.3 BiocVersion_3.15.2
[117] later_1.3.0 httr_1.4.4
[119] colorspace_2.1-0 rvest_1.0.3
[121] XML_3.99-0.13 fs_1.6.1
[123] splines_4.2.2 RBGL_1.72.0
[125] statmod_1.5.0 sessioninfo_1.2.2
[127] xtable_1.8-4 jsonlite_1.8.4
[129] futile.options_1.0.1 corpcor_1.6.10
[131] R6_2.5.1 profvis_0.3.7
[133] pillar_1.8.1 htmltools_0.5.4
[135] mime_0.12 glue_1.6.2
[137] fastmap_1.1.0 BiocParallel_1.30.4
[139] interactiveDisplayBase_1.34.0 codetools_0.2-19
[141] pkgbuild_1.4.0 utf8_1.2.3
[143] bslib_0.4.2 curl_5.0.0
[145] interp_1.1-3 rmarkdown_2.20
[147] munsell_0.5.0 GenomeInfoDbData_1.2.8
[149] haven_2.5.1 gtable_0.3.1