Visualizing clusters with heatmaps

Objectives

Introduce the heatmap and dendrogram as tools for visualizing clusters in data.
Learn how to work with the package pheatmap.
Learn how to save a non-ggplot2 plot.
Introduce ggplotify to convert non-ggplots to ggplots

What is a heatmap?

A heatmap is a graphical representation of data where the individual values contained in a matrix are represented as colors. --- R Graph Gallery

Heatmaps are appropriate when we have lots of data because color is easier to interpret and distinguish than raw values. --- Dundas BI

Heatmap can be used to visualize the following

gene expression across samples (Figure 1)
correlation (Figure 2)
disease cases (Figure 3)
hot/cold zones
topograph

What is a dendrogram?

A dendrogram (or tree diagram) is a network structure and can be used to visualize hierarchy or clustering in data --- R Graph Gallery

https://youtu.be/h0e2HAPTGF4

Applications of heatmaps and dendrograms

Dendrograms are used in phylogenetics to help visualize relatedness of or dissimilarities between species.

In RNA sequencing, dendrogram can be combined with heatmap to show clustering of samples by gene expression or clustering of genes that are similarly expressed (Figure 1).

Figure 1: Heatmap and dendrogram showing clustering of samples with similar gene expression and clustering of genes with similar expression patterns.

Further heatmap and dendrogram can be as a diagnostic tool in high throughput sequencing experiments. As an example, we can look at the heatmap and dendrogram in Figure 2. In Figure 2, the heatmap shows correlation of RNA sequencing samples with the idea that biological replicates should be more highly correleated compared to samples between treatment groups. The dendrogram clusters similar samples together. Figure 2 tells us that heatmaps can also be used to visualize correlation.

Figure 2: Heatmap and dendrogram showing sample correlation in an RNA sequecing experimented. This heatmap and dendrogram is generated using DeepTools - https://deeptools.readthedocs.io/en/develop/content/tools/plotCorrelation.html

Figure 3: Maryland cancer cases - source: https://statecancerprofiles.cancer.gov

Methods available to produce a heatmap

One way of producing a heatmap is to use geom_tile in ggplot2. However, the process becomes cumbersome if we want to include a dendrogram to show clustering. To construct a heatmap and dendrogram using ggplot2 we would need to do the following

Calculate a distance matrix for the data using dist()
Calculate the clusters from the distance matrix using hclust()
Use an external package such as ggdendro to construct the dendrogram

After generating the dendrogram, we would need to combine it with the heatmap and then some resizing as well as adjustments are needed to ensure alignement.

Other options for creating heatmap in R include

built-in heatmap function
heatmap.2 from the gplots package (https://cran.r-project.org/web/packages/gplots/index.html)
Heatplus (https://bioconductor.org/packages/release/bioc/html/Heatplus.html)
ComplexHeatmap (https://www.bioconductor.org/packages/release/bioc/html/ComplexHeatmap.html)

Insert heatmap package comparison here http://compbio.ucsd.edu/making-heat-maps-r/#summary

pheatmap is a versatile package that draws clustered heatmaps so that the above steps taken using the ggplot2 approach would not have to be taken.

Load the libraries

library(ggplot2)
library(pheatmap)
library(tidyverse)
library(ggplotify)
library(heatmaply)

Import data

The data that we will be working with comes from the airway study that profiled the transcriptome of several airway smooth muscle cell lines under either control or dexamethasone treatment Himes et al 2014 and the dataset is available from Bioconductor (https://bioconductor.org/packages/release/data/experiment/html/airway.html).

Specifically, our dataset represents the normalized (log2 counts per million or log2 CPM) of count values from the top 20 differential expressed genes in this study. This data saved in the comma separated file RNAseq_mat_top20.csv and thus we will be using the read.csv command to import.

As a refresher, inside the read.csv command we have the following arguments

"./data/RNAseq_mat_top20.csv", which the path of the file name
header=TRUE indicates that we have column headings
we set the first column of our dataset, which contains gene names as the row names in the imported data using row.names=1, where 1 indicates the column number that we want to import as row names
check.names=FALSE so that R leaves the columen headings alone

The data is saved as R object mat.

mat<-read.csv("./data/RNAseq_mat_top20.csv",header=TRUE,row.names=1,check.names=FALSE)

We will now use head to look at the first 6 rows of mat. The column headings represent sample name and the row names are the genes.

head(mat)

##              508      509       512      513        516        517        520
## WNT2    4.694554 1.332858  5.983720 2.898648  2.1105784 -0.1655252  4.2828513
## DNM1    6.180735 4.441965  5.660024 3.981513  5.8002923  3.9603755  6.2853003
## ZBTB16 -1.863523 5.257967 -1.777152 4.902223 -2.9319722  4.2830866 -0.5150407
## DUSP1   4.936551 8.019074  5.607568 8.302196  5.0283417  7.7229898  5.1432459
## HIF3A   1.013991 3.374457  1.575250 4.154740  0.4928878  2.8335879  2.2501244
## MT2A    6.248514 8.276988  5.782855 8.070846  5.7583897  8.2015855  5.9163628
##             521
## WNT2   1.237000
## DNM1   4.488955
## ZBTB16 5.779173
## DUSP1  8.396709
## HIF3A  4.790581
## MT2A   7.933492

pheatmap of top 20 genes from differential expression analysis

Below we generate the basic heatmap using the pheatmap package. It is simple, just use the pheatmap command and include the data that we want to construct a heatmap of as the argument. In the heatmap below, we have the sample IDs plotted along the bottom horizontal axis, while the genes names are presented long the right vertical axis. Each tile in the heatmap corresponds to a sample-gene combination and as mentioned earlier, the expression level is indicated by the color scale. Note that later on in this lesson, we can add an additional legend that color codes the treatment group that each sample belongs to. The dendrogram that spans the columns indicates how samples are clustered together, while that which spans the rows tells us how the genes are clustered together.

pheatmap(mat)

distance and clustering

The idea behind cluster analysis is to calculate some sort of distance between objects in order to identify the ones that are closer together. When two objects have a small distance, we can conclude they are closer and should cluster together. On the other, two objects that are further apart will have a larger distance. There are various approaches to calculating distance in cluster analysis so considerations should be taken for choosing the appropriate one. Two of these are euclidean and Manhattan and the choice of distance calculation will affect the clustering outcome. To learn more about distance calculations, refer to https://medium.com/analytics-vidhya/role-of-distance-metrics-in-machine-learning-e43391a6bf2e. After the distance matrix has been calculated, it is time to perform the actual clustering and again, various approaches can be used to generate clusters. To learn more about each clustering approach see https://hlab.stanford.edu/brian/forming_clusters.htm.

Below, we use the head command to view the arguments that can be used with pheatmap. We can specify the clustering distance using either the clustering_distance_rows argument or clustering_distance_cols depending on whether we would like to cluster by row or column variables. As an example, if we would like to learn how samples in our data cluster by gene expression in the above heatmap, then we could use clustering_distance_cols to specify a distance calculation method. The clustering method in pheatmap is specified by the clustering_method argument.

To diverge a bit, other arguments from pheatmap that we will be using included

color (for setting color scheme)
annotation_col (for adding legend to show sample-treatment mapping),
annotation_colors (for customizing the color scheme for the sample-treatment mapping legend)

head(pheatmap,n=19)

##                                                                                      
## 1  function (mat, color = colorRampPalette(rev(brewer.pal(n = 7,                     
## 2      name = "RdYlBu")))(100), kmeans_k = NA, breaks = NA, border_color = "grey60", 
## 3      cellwidth = NA, cellheight = NA, scale = "none", cluster_rows = TRUE,         
## 4      cluster_cols = TRUE, clustering_distance_rows = "euclidean",                  
## 5      clustering_distance_cols = "euclidean", clustering_method = "complete",       
## 6      clustering_callback = identity2, cutree_rows = NA, cutree_cols = NA,          
## 7      treeheight_row = ifelse((class(cluster_rows) == "hclust") ||                  
## 8          cluster_rows, 50, 0), treeheight_col = ifelse((class(cluster_cols) ==     
## 9          "hclust") || cluster_cols, 50, 0), legend = TRUE, legend_breaks = NA,     
## 10     legend_labels = NA, annotation_row = NA, annotation_col = NA,                 
## 11     annotation = NA, annotation_colors = NA, annotation_legend = TRUE,            
## 12     annotation_names_row = TRUE, annotation_names_col = TRUE,                     
## 13     drop_levels = TRUE, show_rownames = T, show_colnames = T,                     
## 14     main = NA, fontsize = 10, fontsize_row = fontsize, fontsize_col = fontsize,   
## 15     angle_col = c("270", "0", "45", "90", "315"), display_numbers = F,            
## 16     number_format = "%.2f", number_color = "grey30", fontsize_number = 0.8 *      
## 17         fontsize, gaps_row = NULL, gaps_col = NULL, labels_row = NULL,            
## 18     labels_col = NULL, filename = NA, width = NA, height = NA,                    
## 19     silent = FALSE, na_col = "#DDDDDD", ...)

methods for calculating distance in pheatmap

In introduction of this lesson, we learned that R has a built-in function for generating distance matrices. The function is dist and it is options in dist that can be used for calculating distance in pheatmap.

clustering_distance_rows distance measure used in clustering rows. Possible values are "correlation" for Pearson correlation and all the distances supported by dist, such as "euclidean", etc. If the value is none of the above it is assumed that a distance matrix is provided. --- pheatmap documentation

distance calculation methods in dist the distance measure to be used. This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski". --- dist documentation

methods for hierarchical clustering in pheatmap

Also at the beginning of this lesson, we saw that hclust in base R can be used to generate cluster. The methods available in hclust can also be used for pheatmap.

clustering method clustering method used. Accepts the same values as hclust. --- pheatmap documentation

To learn more about clustering methods available, see the hclust documentation.

Figure 4: Comparison of distance calcuation methods - source: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0144059

To learn more about hierarchical clustering methods and advantages/disadvantages, refer to https://www.learndatasci.com/glossary/hierarchical-clustering/ and https://dataaspirant.com/hierarchical-clustering-algorithm/.

row-wise scaling

Scaling is important during cluster analysis because it reduces the influence that variables with high magnitude values will have on distance. (https://medium.com/analytics-vidhya/why-is-scaling-required-in-knn-and-k-means-8129e4d88ed7).

A common method for scaling is to use the z score (equation 1), which tells us how many standard deviations away from the mean is a given value in our data.

$$ z= \ {individual\ value - mean \over standard\ deviation\ } \ equation\ 1 $$

Briefly, let's look at how scaling of data influences the Euclidean distance between samples in a hypothetical RNA sequencing experiment. In this hypothetical data below, the counts expression for gene HPRT is 10 and 20 for sample1 and sample2, respectively. On the other, the magnitude for gene ADA is higher than that for HPRT for both of the samples.

unscaled_rna <- read.csv("./data/rna_unscaled.csv")
unscaled_rna

##    sample HPRT  ADA
## 1 sample1   10 6500
## 2 sample2   20 8000

Gene expression for sample1 and sample2 are plotted in Figure 5. The diagonal line that connects the samples represents the Euclidean distance between the samples. This diagonal can be viewed as the hypotenuse of a right triangle, which can be calculated from the coordinates of sample 1 and sample 2 on the plot using the Pythagorean theorem (Figure 6 and equation 2).

Figure 5: unscaled RNA

Figure 6: pythagorean theorem

$$ distance= \sqrt{(x2-x1)^2+(y2-y1)^2} \ equation\ 2 $$

To calculate the Euclidean distance between sample1 and sample2, we will need to substitute for the values in equation 2. Note the distance component given by x2-x1 accounts for the changes in HPRT expression (ie. x axis coordinates in Figure 5) and the distance component given by y2-y1 accounts for changes in ADA expression (ie. y axis coordinates in Figure 5). Thus, we will

substitute the sample2 HPRT expression for x2
substitute the sample1 HPRT expression for x1
subtract sample1 HPRT expression from sample 2 HPRT expression and then square the difference
substitute the sample2 ADA expression for y2
substitute the sample1 ADA expression for y1
subtract sample1 ADA expression from sample 2 ADA expression and then square the difference
add results from step 3 and step 6 and then take the square root

In sum, we will end up with equation 3 and our result is 1500.033. Note that ADA expression contributes for more weight to the Euclidean distance, which is attributed to the difference in ADA expression between both samples being 1500 and that for HPRT expression being 10.

$$ distance= \sqrt{(20-10)^2+(8000-6500)^2} \ equation\ 3 $$

However, we use z-score to scale the data, then the expression of ADA will contribute as much weight to the Euclidean distance between sample1 and sample2. As a matter of fact, both ADA and HPRT expression contributes equally to the Euclidean distance in the scaled data (in other words, their scale expression are the same). Following the steps for calculation, we get a Euclidean distance of approximately 2 between sample1 and sample2. In sum, a rationale for scaling is to minimize the contribution that variables with high magnitude values will have on distance.

scaled_rna <- read.csv("./data/rna_scaled.csv")
scaled_rna

##    sample       HPRT        ADA
## 1 sample1 -0.7071068 -0.7071068
## 2 sample2  0.7071068  0.7071068

Scaling also helps in the construction of heatmaps and this again has to do with variables that values with large magnitude versus those with low magnitude. On a color scale, it will be very hard to discern any differences in the the low magnitude value variables if scaling does not occur. We can see this using the built-in data mtcars.

data(mtcars)
cars <- mtcars
head(cars)

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

Note that variables like disp and hp has larger magnitudes. If we constructed a heatmap of the mtcars data without scaling, we will not be able to discern differences in variables like mpg, which have lower magnitude values.

pheatmap(cars)

However, if we scaled then it becomes easier to observe differences in values for each of the variables. Here, we scale by column because the sample names (ie. car brands) are the row names for the data. If the car brands were column headings, we would have scaled by row.

pheatmap(cars, scale="column")

Getting back to RNA seq and something more biologically relevant, we can scale by row in mat.

pheatmap(mat, scale="row")

Controlling column clustering

Working with colors customization

pheatmap(mat,scale="row",
         color=colorRampPalette(c("navy", "white", "red"))(50))

#pheatmap(mat,scale="row", color=brewer.pal(5, "Spectral"))

Adding treatment group information to samples (`annotation_col`, `annotation_colors`)

The code below generates a data frame, dfh, that contains information on the treatment group in which a sample was assigned. To create a data frame in R, we use the data.frame command. In the data.frame command, we set the sample to the column names of the data mat using colnames(mat) to extract the mat column headings. We then want to convert the column headings in mat to character using as.character. Next, also in the data.frame argument, we set the column dex to "Treatment".

Using %>%, we send the dfh data frame to the column_to_rownames command to set the rownames of the dfh data frame to the sample ids. Finally, we will change the values in the dex column to either untrt (untreated) or trt (treated) using ifelse to check if the row names of dfh (rownames(dfh)) are samples 508, 512, 516, or 520. If yes, then the value for these samples in the dex column becomes untrt. In other words, 508, 512, 516, and 520 are untreated samples. Else, we will assign the samples to the trt group, which indicates they are treated.

#create data frame for annotations
dfh<-data.frame(sample=as.character(colnames(mat)),dex="Treatment") %>% column_to_rownames("sample")
dfh$dex<-ifelse(rownames(dfh) %in% c("508","512","516","520"),"untrt","trt")
dfh

##       dex
## 508 untrt
## 509   trt
## 512 untrt
## 513   trt
## 516 untrt
## 517   trt
## 520 untrt
## 521   trt

Add the annotations column

We can add the sample treatment annotation by setting the annotation_col argument to dfh in pheatmap. We use annotation_col rather than annotation_col because the samples IDs are listed along the horizontal axis so essentially corresponding to the columns of the heatmap. The result is that the samples are now color coded by the treatment group in which they belong and this color coding is provided in the legend.

pheatmap(mat,scale="row", annotation_col = dfh,
         color=colorRampPalette(c("navy", "white", "red"))(50))

Modify the annotations colors

Using the annotation_colors argument, we can reassign the colors of the legend.

pheatmap(mat,scale="row", annotation_col = dfh,
         annotation_colors=list(dex=c(trt="orange",untrt="black")),
         color=colorRampPalette(c("navy", "white", "red"))(50))

Splitting heatmap into multiple columns using

It maybe helpful to split the heatmap into different portions to illustrate clusters more efficiently. Here, we can the heatmap into two columns using the argument cutree_col and setting this to 2. Doing so will split the heatmap into a column containing the dexamethasone (dex) treated column (trt) and an untreated column (untrt).

pheatmap(mat,scale="row", annotation_col = dfh,
         annotation_colors=list(dex=c(trt="orange",untrt="black")),
         color=colorRampPalette(c("navy", "white", "red"))(50),
         cutree_cols=2)

If we include cutree_rows=2, then the heatmap will be split into two rows. Note that it is split in a way that the top row represents genes that are down-regulated in the treated group while the but up-regulated in the up-regulated group. The bottom row represents those genes that are up-regulated by dexamethasone treatment but down-regulated when not treated.

pheatmap(mat,scale="row", annotation_col = dfh,
         annotation_colors =list(dex=c(trt="orange",untrt="black")),
         color=colorRampPalette(c("navy", "white", "red"))(50),
         cutree_cols=2, cutree_rows=2)

Add a title to heatmap

A title for our heatmap can be included using the main argument

pheatmap(mat,scale="row", annotation_col = dfh,
         annotation_colors =list(dex=c(trt="orange",untrt="black")),
         color=colorRampPalette(c("navy", "white", "red"))(50),
         cutree_cols=2, cutree_rows=2, 
         main="expression and clustering of DE genes")

The last few customization we will do with the heatmap is to adjust the fontsize using argument fontsize. We will adjust the cellwidth to move the treatment legend into the plot canvas. We also use cellheight to adjust the height of the heatmap to fill more of the plotting canvas.

pheatmap(mat,scale="row", annotation_col = dfh,
         annotation_colors=list(dex=c(trt="orange",untrt="black")),
         color=colorRampPalette(c("navy", "white", "red"))(50),
         cutree_cols=2, cutree_rows=2, 
         main="expression and clustering of DE genes",
         fontsize=11, cellwidth=35, cellheight=10.25)

Saving a non-ggplot

Recall that we can use the ggsave command to save a ggplot. However, heatmaps generated using the pheatmap package are not ggplots, there for we need to turn to either the image export feature (Figure 7) in R studio or use one of the several image saving commands.

Figure 7: Exporting images

The programmatic ways to save an image include the following commands

jpeg
bmp
tiff
png
pdf

All of these take the file name in which we would like to save the image, resolution (res), image width (width), image height (height), and units of image dimension (unit) as arguments. Below, we use png to save our heatmap as file pheatmap_1.png at 300 dpi as specified in res. The workflow is to first create the file using one of the image save commands, then generate the plot, and set dev.off() to turn off the current graphical device.

png("/Users/wuz8/Documents/pheatmap_1.png", res=300, width=7, height=4.5, unit="in")
pheatmap(mat,scale="row", annotation_col = dfh,
         annotation_colors=list(dex=c(trt="orange",untrt="black")),
         color=colorRampPalette(c("navy", "white", "red"))(50),
         cutree_cols=2, cutree_rows=2,
         main="expression and clustering of DE genes",
         fontsize=11, cellwidth=35, cellheight=10.25)
dev.off()

## quartz_off_screen 
##                 3

Make this plot compatible with ggplot2 using the package `ggplotify`.

hm_gg<-as.ggplot(pheatmap(mat,scale="row", annotation_col = dfh,annotation_colors =list(dex=c(trt="orange",untrt="black")),
         color=colorRampPalette(c("navy", "white", "red"))(50)))

Save as an R object

Below, we assign the heatmap to the R object hm_ph.

hm_ph <- pheatmap(mat,scale="row", annotation_col = dfh,annotation_colors =list(dex=c(trt="orange",untrt="black")),
         color=colorRampPalette(c("navy", "white", "red"))(50),
         cutree_cols=2, cutree_rows=2,
         main="expression and clustering of DE genes",
         fontsize=11, cellwidth=35, cellheight=10.25)

saveRDS(hm_ph, file="/Users/wuz8/Documents/airways_pheatmap.rds")

We will wrap up lesson 5 with an introduction to the package heatmaply, which can be used to generate interactive heatmaps. Below is a basic interactive heatmap generated using this package for the airway top 20 differentially expressed genes (mat).

Similar to pheatmap, we will start by providing heatmaply the data that we would like to plot. We can also scale by row like we did in pheatmap. Plot margins can also be set to ensure the entire plot fits on the canvas. Like in pheatmap, we assign the plot title using the argument main. Setting col_side_colors to the data frame dfh, which contains the sample to treatment mapping, creates a legend that spans the columns of the heatmap informing us of the treatment group to which the samples belong.

heatmaply(mat, scale="row", margins=c(0.5,1,50,1),
          main="interactively explore airway DE genes",
          col_side_colors=dfh)

<div id="htmlwidget-3e60935c51fce4dec7e1" style="width:672px;height:480px;" class="plotly html-widget"></div>
<script type="application/json" data-for="htmlwidget-3e60935c51fce4dec7e1">{"x":{"data":[{"x":[4.875,2.875,null,2.875,2.875,null,2.875,1.75,null,1.75,1.75,null,1.75,1,null,1,1,null,1.75,2.5,null,2.5,2.5,null,2.5,2,null,2,2,null,2.5,3,null,3,3,null,2.875,4,null,4,4,null,4.875,6.875,null,6.875,6.875,null,6.875,5.75,null,5.75,5.75,null,5.75,5,null,5,5,null,5.75,6.5,null,6.5,6.5,null,6.5,6,null,6,6,null,6.5,7,null,7,7,null,6.875,8,null,8,8],"y":[9.37052889139853,9.37052889139853,null,9.37052889139853,2.91402464312441,null,2.91402464312441,2.91402464312441,null,2.91402464312441,1.88368605593102,null,1.88368605593102,1.88368605593102,null,1.88368605593102,0,null,1.88368605593102,1.88368605593102,null,1.88368605593102,1.83603486074388,null,1.83603486074388,1.83603486074388,null,1.83603486074388,0,null,1.83603486074388,1.83603486074388,null,1.83603486074388,0,null,2.91402464312441,2.91402464312441,null,2.91402464312441,0,null,9.37052889139853,9.37052889139853,null,9.37052889139853,2.9658247301148,null,2.9658247301148,2.9658247301148,null,2.9658247301148,2.07606369660548,null,2.07606369660548,2.07606369660548,null,2.07606369660548,0,null,2.07606369660548,2.07606369660548,null,2.07606369660548,1.76546633232318,null,1.76546633232318,1.76546633232318,null,1.76546633232318,0,null,1.76546633232318,1.76546633232318,null,1.76546633232318,0,null,2.9658247301148,2.9658247301148,null,2.9658247301148,0],"text":["y: 9.370529","y: 9.370529",null,"y: 9.370529","y: 9.370529",null,"y: 2.914025","y: 2.914025",null,"y: 2.914025","y: 2.914025",null,"y: 1.883686","y: 1.883686",null,"y: 1.883686","y: 1.883686",null,"y: 1.883686","y: 1.883686",null,"y: 1.883686","y: 1.883686",null,"y: 1.836035","y: 1.836035",null,"y: 1.836035","y: 1.836035",null,"y: 1.836035","y: 1.836035",null,"y: 1.836035","y: 1.836035",null,"y: 2.914025","y: 2.914025",null,"y: 2.914025","y: 2.914025",null,"y: 9.370529","y: 9.370529",null,"y: 9.370529","y: 9.370529",null,"y: 2.965825","y: 2.965825",null,"y: 2.965825","y: 2.965825",null,"y: 2.076064","y: 2.076064",null,"y: 2.076064","y: 2.076064",null,"y: 2.076064","y: 2.076064",null,"y: 2.076064","y: 2.076064",null,"y: 1.765466","y: 1.765466",null,"y: 1.765466","y: 1.765466",null,"y: 1.765466","y: 1.765466",null,"y: 1.765466","y: 1.765466",null,"y: 2.965825","y: 2.965825",null,"y: 2.965825","y: 2.965825"],"type":"scatter","mode":"lines","line":{"width":2.26771653543307,"color":"rgba(0,0,0,1)","dash":"solid"},"hoveron":"points","showlegend":false,"xaxis":"x","yaxis":"y","hoverinfo":"text","frame":null},{"x":[4.875,2.875,1.75,1,2.5,2,3,4,6.875,5.75,5,6.5,6,7,8],"y":[9.37052889139853,2.91402464312441,1.88368605593102,0,1.83603486074388,0,0,0,2.9658247301148,2.07606369660548,0,1.76546633232318,0,0,0],"text":["y: 9.370529","y: 2.914025","y: 1.883686","y: 0.000000","y: 1.836035","y: 0.000000","y: 0.000000","y: 0.000000","y: 2.965825","y: 2.076064","y: 0.000000","y: 1.765466","y: 0.000000","y: 0.000000","y: 0.000000"],"type":"scatter","mode":"markers","marker":{"autocolorscale":false,"color":"transparent","opacity":1,"size":null,"symbol":null,"line":{"width":1.88976377952756,"color":"transparent"}},"hoveron":"points","showlegend":false,"xaxis":"x","yaxis":"y","hoverinfo":"text","frame":null},{"type":"scatter","mode":"markers","marker":{"color":"rgba(44,160,44,1)","line":{"color":"rgba(44,160,44,1)"}},"error_y":{"color":"rgba(44,160,44,1)"},"error_x":{"color":"rgba(44,160,44,1)"},"line":{"color":"rgba(44,160,44,1)"},"xaxis":"x2","yaxis":"y","frame":null},{"x":[2.5,2.5,3.5,3.5,2.5],"y":[0.5,1.5,1.5,0.5,0.5],"text":"value: trt<br />column: 509<br />variable: dex","type":"scatter","mode":"lines","line":{"width":0.377952755905512,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(166,206,227,1)","hoveron":"fills","name":"trt","legendgroup":"trt","showlegend":true,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[0.5,0.5,1.5,1.5,0.5],"y":[0.5,1.5,1.5,0.5,0.5],"text":"value: trt<br />column: 513<br />variable: dex","type":"scatter","mode":"lines","line":{"width":0.377952755905512,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(166,206,227,1)","hoveron":"fills","name":"trt","legendgroup":"trt","showlegend":false,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[3.5,3.5,4.5,4.5,3.5],"y":[0.5,1.5,1.5,0.5,0.5],"text":"value: trt<br />column: 517<br />variable: dex","type":"scatter","mode":"lines","line":{"width":0.377952755905512,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(166,206,227,1)","hoveron":"fills","name":"trt","legendgroup":"trt","showlegend":false,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[1.5,1.5,2.5,2.5,1.5],"y":[0.5,1.5,1.5,0.5,0.5],"text":"value: trt<br />column: 521<br />variable: dex","type":"scatter","mode":"lines","line":{"width":0.377952755905512,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(166,206,227,1)","hoveron":"fills","name":"trt","legendgroup":"trt","showlegend":false,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[6.5,6.5,7.5,7.5,6.5],"y":[0.5,1.5,1.5,0.5,0.5],"text":"value: untrt<br />column: 508<br />variable: dex","type":"scatter","mode":"lines","line":{"width":0.377952755905512,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(31,120,180,1)","hoveron":"fills","name":"untrt","legendgroup":"untrt","showlegend":true,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[5.5,5.5,6.5,6.5,5.5],"y":[0.5,1.5,1.5,0.5,0.5],"text":"value: untrt<br />column: 512<br />variable: dex","type":"scatter","mode":"lines","line":{"width":0.377952755905512,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(31,120,180,1)","hoveron":"fills","name":"untrt","legendgroup":"untrt","showlegend":false,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[7.5,7.5,8.5,8.5,7.5],"y":[0.5,1.5,1.5,0.5,0.5],"text":"value: untrt<br />column: 516<br />variable: dex","type":"scatter","mode":"lines","line":{"width":0.377952755905512,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(31,120,180,1)","hoveron":"fills","name":"untrt","legendgroup":"untrt","showlegend":false,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"x":[4.5,4.5,5.5,5.5,4.5],"y":[0.5,1.5,1.5,0.5,0.5],"text":"value: untrt<br />column: 520<br />variable: dex","type":"scatter","mode":"lines","line":{"width":0.377952755905512,"color":"transparent","dash":"solid"},"fill":"toself","fillcolor":"rgba(31,120,180,1)","hoveron":"fills","name":"untrt","legendgroup":"untrt","showlegend":false,"xaxis":"x","yaxis":"y2","hoverinfo":"text","frame":null},{"type":"scatter","mode":"markers","marker":{"color":"rgba(255,127,14,1)","line":{"color":"rgba(255,127,14,1)"}},"error_y":{"color":"rgba(255,127,14,1)"},"error_x":{"color":"rgba(255,127,14,1)"},"line":{"color":"rgba(255,127,14,1)"},"xaxis":"x2","yaxis":"y2","frame":null},{"x":[1,2,3,4,5,6,7,8],"y":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],"z":[[0.142081664008549,0.307407879503353,0.292098330424203,0.135195071215145,0.892662125230596,0.688945341338971,0.858594529955199,0.734645137798025],[0.255252554192431,0.0575204942506929,0.216672329995217,0.343148211812258,0.731700184973087,0.816191885443724,0.786981437405585,0.844162981401046],[0.295416843351229,0.0507353401865884,0.253070642541595,0.338465839318091,0.549635250807323,0.897582083952149,0.806166462370443,0.860557616946623],[0.386144555842134,0.173552310376893,0.0789763017944922,0.267532885530203,0.759871631818087,0.903924569446749,0.647189153195486,0.834438671469998],[0.52222128788573,0.264885253063706,0.279730582141476,0.0476790755636527,0.736589931093047,1,0.800349426886454,0.400174522839975],[0.773695907583577,0.702473345225393,0.999496539906,0.465829234711997,0.261259702106614,0.301861851690231,0.547013498250229,0],[0.952883169707135,0.757637018976691,0.822623418996111,0.5195337850014,0.183928287439045,0.451631376056891,0.312487860283121,0.0509051630136466],[0.844015395504366,0.900222634473088,0.776963663364038,0.58255211396413,0.394691652669243,0.290324256482295,0.245984983086429,0.0168753799304514],[0.843504244022128,0.977949258542405,0.67851761260496,0.564153889873065,0.440783751339449,0.298085344987014,0.179410215785305,0.0692257623197157],[0.904517781878235,0.839037313491813,0.778666556459275,0.646324946960845,0.258803544560584,0.289704863634681,0.249729477770289,0.0848455947183175],[0.887179966354019,0.845970775308771,0.781556946106582,0.664051052130891,0.26040851107287,0.308744118222008,0.189657425170605,0.114061285108295],[0.855532979668195,0.821772059784089,0.790028486103426,0.736014235098152,0.2780376247374,0.260961819223679,0.141924456412207,0.167358418446894],[0.839270419065252,0.858246978663921,0.782425072326302,0.722976951481028,0.205013635167113,0.29824068043619,0.163513267572279,0.181943074761958],[0.790439246287495,0.838927241163085,0.839040279289257,0.745483038526974,0.225762628980385,0.224154192580577,0.162917427381785,0.224906025264483],[0.792741026163404,0.93442740109682,0.723489306749428,0.740439207688491,0.288223274604346,0.189654539444934,0.167543259530804,0.215112064195813],[0.785813843636411,0.860953869090081,0.816295188431205,0.732764173214816,0.321644538510777,0.213502621015521,0.206102098579071,0.114553746996158],[0.788536625078949,0.751538336431344,0.844063868253471,0.823753235557389,0.208195704625901,0.17223355078034,0.297665388587226,0.165643370159422],[0.88666476508025,0.756006384227706,0.743199861358246,0.818333594207329,0.174814651441414,0.262740893835343,0.164070793400051,0.2457991359237],[0.82223151560205,0.764710012035609,0.792431660033311,0.819272510625704,0.0826131705249468,0.257562933344516,0.224669862098464,0.288138415209441],[0.71932310125997,0.772493552097587,0.798628419296348,0.896473436055879,0.203658749469612,0.155428264907225,0.159114811312276,0.346509745075145]],"text":[["row: DNM1<br>column: 513<br>value: -1.14033","row: DNM1<br>column: 521<br>value: -0.62293","row: DNM1<br>column: 509<br>value: -0.67084","row: DNM1<br>column: 517<br>value: -1.16188","row: DNM1<br>column: 520<br>value:  1.20867","row: DNM1<br>column: 512<br>value:  0.57112","row: DNM1<br>column: 508<br>value:  1.10205","row: DNM1<br>column: 516<br>value:  0.71414"],["row: VCAM1<br>column: 513<br>value: -0.78616","row: VCAM1<br>column: 521<br>value: -1.40497","row: VCAM1<br>column: 509<br>value: -0.90690","row: VCAM1<br>column: 517<br>value: -0.51108","row: VCAM1<br>column: 520<br>value:  0.70493","row: VCAM1<br>column: 512<br>value:  0.96935","row: VCAM1<br>column: 508<br>value:  0.87793","row: VCAM1<br>column: 516<br>value:  1.05689"],["row: ADAM12<br>column: 513<br>value: -0.66046","row: ADAM12<br>column: 521<br>value: -1.42621","row: ADAM12<br>column: 509<br>value: -0.79298","row: ADAM12<br>column: 517<br>value: -0.52573","row: ADAM12<br>column: 520<br>value:  0.13514","row: ADAM12<br>column: 512<br>value:  1.22407","row: ADAM12<br>column: 508<br>value:  0.93798","row: ADAM12<br>column: 516<br>value:  1.10820"],["row: PRSS35<br>column: 513<br>value: -0.37652","row: PRSS35<br>column: 521<br>value: -1.04184","row: PRSS35<br>column: 509<br>value: -1.33783","row: PRSS35<br>column: 517<br>value: -0.74772","row: PRSS35<br>column: 520<br>value:  0.79309","row: PRSS35<br>column: 512<br>value:  1.24392","row: PRSS35<br>column: 508<br>value:  0.44044","row: PRSS35<br>column: 516<br>value:  1.02646"],["row: WNT2<br>column: 513<br>value:  0.04935","row: WNT2<br>column: 521<br>value: -0.75601","row: WNT2<br>column: 509<br>value: -0.70955","row: WNT2<br>column: 517<br>value: -1.43577","row: WNT2<br>column: 520<br>value:  0.72023","row: WNT2<br>column: 512<br>value:  1.54459","row: WNT2<br>column: 508<br>value:  0.91977","row: WNT2<br>column: 516<br>value: -0.33261"],["row: PDPN<br>column: 513<br>value:  0.83636","row: PDPN<br>column: 521<br>value:  0.61346","row: PDPN<br>column: 509<br>value:  1.54302","row: PDPN<br>column: 517<br>value: -0.12714","row: PDPN<br>column: 520<br>value: -0.76736","row: PDPN<br>column: 512<br>value: -0.64029","row: PDPN<br>column: 508<br>value:  0.12694","row: PDPN<br>column: 516<br>value: -1.58499"],["row: FAM107A<br>column: 513<br>value:  1.39714","row: FAM107A<br>column: 521<br>value:  0.78610","row: FAM107A<br>column: 509<br>value:  0.98948","row: FAM107A<br>column: 517<br>value:  0.04094","row: FAM107A<br>column: 520<br>value: -1.00937","row: FAM107A<br>column: 512<br>value: -0.17157","row: FAM107A<br>column: 508<br>value: -0.60703","row: FAM107A<br>column: 516<br>value: -1.42568"],["row: ACSS1<br>column: 513<br>value:  1.05643","row: ACSS1<br>column: 521<br>value:  1.23233","row: ACSS1<br>column: 509<br>value:  0.84658","row: ACSS1<br>column: 517<br>value:  0.23816","row: ACSS1<br>column: 520<br>value: -0.34977","row: ACSS1<br>column: 512<br>value: -0.67640","row: ACSS1<br>column: 508<br>value: -0.81516","row: ACSS1<br>column: 516<br>value: -1.53218"],["row: HIF3A<br>column: 513<br>value:  1.05483","row: HIF3A<br>column: 521<br>value:  1.47558","row: HIF3A<br>column: 509<br>value:  0.53849","row: HIF3A<br>column: 517<br>value:  0.18058","row: HIF3A<br>column: 520<br>value: -0.20552","row: HIF3A<br>column: 512<br>value: -0.65211","row: HIF3A<br>column: 508<br>value: -1.02351","row: HIF3A<br>column: 516<br>value: -1.36834"],["row: STEAP2<br>column: 513<br>value:  1.24577","row: STEAP2<br>column: 521<br>value:  1.04085","row: STEAP2<br>column: 509<br>value:  0.85191","row: STEAP2<br>column: 517<br>value:  0.43774","row: STEAP2<br>column: 520<br>value: -0.77504","row: STEAP2<br>column: 512<br>value: -0.67833","row: STEAP2<br>column: 508<br>value: -0.80344","row: STEAP2<br>column: 516<br>value: -1.31946"],["row: CACNB2<br>column: 513<br>value:  1.19151","row: CACNB2<br>column: 521<br>value:  1.06255","row: CACNB2<br>column: 509<br>value:  0.86096","row: CACNB2<br>column: 517<br>value:  0.49321","row: CACNB2<br>column: 520<br>value: -0.77002","row: CACNB2<br>column: 512<br>value: -0.61875","row: CACNB2<br>column: 508<br>value: -0.99144","row: CACNB2<br>column: 516<br>value: -1.22802"],["row: NEXN<br>column: 513<br>value:  1.09247","row: NEXN<br>column: 521<br>value:  0.98681","row: NEXN<br>column: 509<br>value:  0.88747","row: NEXN<br>column: 517<br>value:  0.71843","row: NEXN<br>column: 520<br>value: -0.71485","row: NEXN<br>column: 512<br>value: -0.76829","row: NEXN<br>column: 508<br>value: -1.14082","row: NEXN<br>column: 516<br>value: -1.06123"],["row: DUSP1<br>column: 513<br>value:  1.04158","row: DUSP1<br>column: 521<br>value:  1.10097","row: DUSP1<br>column: 509<br>value:  0.86368","row: DUSP1<br>column: 517<br>value:  0.67763","row: DUSP1<br>column: 520<br>value: -0.94338","row: DUSP1<br>column: 512<br>value: -0.65162","row: DUSP1<br>column: 508<br>value: -1.07326","row: DUSP1<br>column: 516<br>value: -1.01558"],["row: SPARCL1<br>column: 513<br>value:  0.88876","row: SPARCL1<br>column: 521<br>value:  1.04050","row: SPARCL1<br>column: 509<br>value:  1.04086","row: SPARCL1<br>column: 517<br>value:  0.74806","row: SPARCL1<br>column: 520<br>value: -0.87845","row: SPARCL1<br>column: 512<br>value: -0.88348","row: SPARCL1<br>column: 508<br>value: -1.07513","row: SPARCL1<br>column: 516<br>value: -0.88113"],["row: FGD4<br>column: 513<br>value:  0.89596","row: FGD4<br>column: 521<br>value:  1.33938","row: FGD4<br>column: 509<br>value:  0.67923","row: FGD4<br>column: 517<br>value:  0.73228","row: FGD4<br>column: 520<br>value: -0.68297","row: FGD4<br>column: 512<br>value: -0.99145","row: FGD4<br>column: 508<br>value: -1.06065","row: FGD4<br>column: 516<br>value: -0.91178"],["row: ZBTB16<br>column: 513<br>value:  0.87428","row: ZBTB16<br>column: 521<br>value:  1.10944","row: ZBTB16<br>column: 509<br>value:  0.96967","row: ZBTB16<br>column: 517<br>value:  0.70826","row: ZBTB16<br>column: 520<br>value: -0.57838","row: ZBTB16<br>column: 512<br>value: -0.91681","row: ZBTB16<br>column: 508<br>value: -0.93998","row: ZBTB16<br>column: 516<br>value: -1.22648"],["row: MT2A<br>column: 513<br>value:  0.88280","row: MT2A<br>column: 521<br>value:  0.76701","row: MT2A<br>column: 509<br>value:  1.05658","row: MT2A<br>column: 517<br>value:  0.99302","row: MT2A<br>column: 520<br>value: -0.93342","row: MT2A<br>column: 512<br>value: -1.04597","row: MT2A<br>column: 508<br>value: -0.65342","row: MT2A<br>column: 516<br>value: -1.06659"],["row: DNAJB4<br>column: 513<br>value:  1.18990","row: DNAJB4<br>column: 521<br>value:  0.78100","row: DNAJB4<br>column: 509<br>value:  0.74092","row: DNAJB4<br>column: 517<br>value:  0.97605","row: DNAJB4<br>column: 520<br>value: -1.03789","row: DNAJB4<br>column: 512<br>value: -0.76272","row: DNAJB4<br>column: 508<br>value: -1.07152","row: DNAJB4<br>column: 516<br>value: -0.81574"],["row: MAOA<br>column: 513<br>value:  0.98825","row: MAOA<br>column: 521<br>value:  0.80823","row: MAOA<br>column: 509<br>value:  0.89499","row: MAOA<br>column: 517<br>value:  0.97899","row: MAOA<br>column: 520<br>value: -1.32644","row: MAOA<br>column: 512<br>value: -0.77892","row: MAOA<br>column: 508<br>value: -0.88187","row: MAOA<br>column: 516<br>value: -0.68324"],["row: TIMP4<br>column: 513<br>value:  0.66619","row: TIMP4<br>column: 521<br>value:  0.83259","row: TIMP4<br>column: 509<br>value:  0.91438","row: TIMP4<br>column: 517<br>value:  1.22060","row: TIMP4<br>column: 520<br>value: -0.94762","row: TIMP4<br>column: 512<br>value: -1.09856","row: TIMP4<br>column: 508<br>value: -1.08703","row: TIMP4<br>column: 516<br>value: -0.50056"]],"colorscale":[[0,"#440154"],[0.0168753799304514,"#46075B"],[0.0476790755636527,"#471365"],[0.0507353401865884,"#481467"],[0.0509051630136466,"#481467"],[0.0575204942506929,"#481769"],[0.0692257623197157,"#481B6D"],[0.0789763017944922,"#481D6F"],[0.0826131705249468,"#481F70"],[0.0848455947183175,"#482071"],[0.114061285108295,"#482979"],[0.114553746996158,"#482979"],[0.135195071215145,"#472F7D"],[0.141924456412207,"#46327E"],[0.142081664008549,"#46327E"],[0.155428264907225,"#453681"],[0.159114811312276,"#453882"],[0.162917427381785,"#443983"],[0.163513267572279,"#443983"],[0.164070793400051,"#443983"],[0.165643370159422,"#443983"],[0.167358418446894,"#443A83"],[0.167543259530804,"#443A83"],[0.17223355078034,"#443B84"],[0.173552310376893,"#443C84"],[0.174814651441414,"#433C84"],[0.179410215785305,"#433E85"],[0.181943074761958,"#433E85"],[0.183928287439045,"#423F85"],[0.189654539444934,"#424086"],[0.189657425170605,"#424086"],[0.203658749469612,"#404588"],[0.205013635167113,"#404588"],[0.206102098579071,"#404688"],[0.208195704625901,"#404688"],[0.213502621015521,"#3F4788"],[0.215112064195813,"#3F4889"],[0.216672329995217,"#3F4889"],[0.224154192580577,"#3E4A89"],[0.224669862098464,"#3E4B89"],[0.224906025264483,"#3E4B89"],[0.225762628980385,"#3E4B8A"],[0.2457991359237,"#3B518B"],[0.245984983086429,"#3B518B"],[0.249729477770289,"#3B528B"],[0.253070642541595,"#3A538B"],[0.255252554192431,"#3A538B"],[0.257562933344516,"#3A548C"],[0.258803544560584,"#3A548C"],[0.26040851107287,"#3A548C"],[0.260961819223679,"#39558C"],[0.261259702106614,"#39558C"],[0.262740893835343,"#39558C"],[0.264885253063706,"#39568C"],[0.267532885530203,"#39568C"],[0.2780376247374,"#375A8C"],[0.279730582141476,"#375A8C"],[0.288138415209441,"#365C8D"],[0.288223274604346,"#365C8D"],[0.289704863634681,"#365D8D"],[0.290324256482295,"#365D8D"],[0.292098330424203,"#365D8D"],[0.295416843351229,"#355E8D"],[0.297665388587226,"#355F8D"],[0.298085344987014,"#355F8D"],[0.29824068043619,"#355F8D"],[0.301861851690231,"#34608D"],[0.307407879503353,"#34618D"],[0.308744118222008,"#33628D"],[0.312487860283121,"#33638D"],[0.321644538510777,"#32658E"],[0.338465839318091,"#30698E"],[0.343148211812258,"#306B8E"],[0.346509745075145,"#2F6B8E"],[0.386144555842134,"#2B748E"],[0.394691652669243,"#2A778E"],[0.400174522839975,"#2A788E"],[0.440783751339449,"#26828E"],[0.451631376056891,"#25848E"],[0.465829234711997,"#23888E"],[0.5195337850014,"#1F948C"],[0.52222128788573,"#1F958B"],[0.547013498250229,"#1E9B8A"],[0.549635250807323,"#1E9C89"],[0.564153889873065,"#1FA088"],[0.58255211396413,"#20A486"],[0.646324946960845,"#2EB37C"],[0.647189153195486,"#2EB37C"],[0.664051052130891,"#34B679"],[0.67851761260496,"#3ABA76"],[0.688945341338971,"#3EBC73"],[0.702473345225393,"#44BF70"],[0.71932310125997,"#4DC26C"],[0.722976951481028,"#4FC36B"],[0.723489306749428,"#4FC36B"],[0.731700184973087,"#53C568"],[0.732764173214816,"#54C568"],[0.734645137798025,"#55C568"],[0.736014235098152,"#55C667"],[0.736589931093047,"#56C667"],[0.740439207688491,"#58C765"],[0.743199861358246,"#59C864"],[0.745483038526974,"#5AC864"],[0.751538336431344,"#5DC962"],[0.756006384227706,"#60CA60"],[0.757637018976691,"#61CA60"],[0.759871631818087,"#62CB5F"],[0.764710012035609,"#65CB5E"],[0.772493552097587,"#69CD5B"],[0.773695907583577,"#6ACD5B"],[0.776963663364038,"#6CCD5A"],[0.778666556459275,"#6DCE59"],[0.781556946106582,"#6FCE58"],[0.782425072326302,"#6FCF57"],[0.785813843636411,"#71CF57"],[0.786981437405585,"#72D056"],[0.788536625078949,"#73D056"],[0.790028486103426,"#74D055"],[0.790439246287495,"#74D055"],[0.792431660033311,"#75D054"],[0.792741026163404,"#75D054"],[0.798628419296348,"#79D152"],[0.800349426886454,"#7AD151"],[0.806166462370443,"#7ED34F"],[0.816191885443724,"#84D44B"],[0.816295188431205,"#84D44B"],[0.818333594207329,"#85D54A"],[0.819272510625704,"#86D549"],[0.821772059784089,"#88D548"],[0.82223151560205,"#88D548"],[0.822623418996111,"#88D548"],[0.823753235557389,"#89D548"],[0.834438671469998,"#90D743"],[0.838927241163085,"#93D741"],[0.839037313491813,"#93D741"],[0.839040279289257,"#93D741"],[0.839270419065252,"#93D741"],[0.843504244022128,"#95D840"],[0.844015395504366,"#96D840"],[0.844063868253471,"#96D840"],[0.844162981401046,"#96D83F"],[0.845970775308771,"#97D83F"],[0.855532979668195,"#9DD93B"],[0.858246978663921,"#A0DA39"],[0.858594529955199,"#A0DA39"],[0.860557616946623,"#A1DA38"],[0.860953869090081,"#A1DA38"],[0.88666476508025,"#B2DD2D"],[0.887179966354019,"#B3DD2D"],[0.892662125230596,"#B7DE2A"],[0.896473436055879,"#B9DE28"],[0.897582083952149,"#BADE28"],[0.900222634473088,"#BCDF27"],[0.903924569446749,"#BFDF26"],[0.904517781878235,"#BFDF25"],[0.93442740109682,"#D3E21B"],[0.952883169707135,"#DFE318"],[0.977949258542405,"#F0E51C"],[0.999496539906,"#FDE725"],[1,"#FDE725"]],"type":"heatmap","showscale":false,"autocolorscale":false,"showlegend":false,"xaxis":"x","yaxis":"y3","hoverinfo":"text","frame":null},{"x":[1],"y":[1],"name":"99_72e3decb1be589183df28a75206d2a47","type":"scatter","mode":"markers","opacity":0,"hoverinfo":"skip","showlegend":false,"marker":{"color":[0,1],"colorscale":[[0,"#440154"],[0.00334448160535118,"#440256"],[0.00668896321070235,"#450357"],[0.0100334448160535,"#450558"],[0.0133779264214047,"#450659"],[0.0167224080267559,"#46075B"],[0.0200668896321071,"#46085C"],[0.0234113712374582,"#460A5D"],[0.0267558528428093,"#460B5E"],[0.0301003344481605,"#470C5F"],[0.0334448160535117,"#470E61"],[0.0367892976588629,"#470F62"],[0.040133779264214,"#471063"],[0.0434782608695652,"#471164"],[0.0468227424749164,"#471365"],[0.0501672240802676,"#481467"],[0.0535117056856187,"#481568"],[0.0568561872909699,"#481768"],[0.0602006688963211,"#481769"],[0.0635451505016723,"#48186A"],[0.0668896321070234,"#481A6C"],[0.0702341137123745,"#481B6D"],[0.0735785953177257,"#481C6E"],[0.0769230769230769,"#481D6F"],[0.0802675585284281,"#481E6F"],[0.0836120401337792,"#481F70"],[0.0869565217391304,"#482071"],[0.0903010033444816,"#482173"],[0.0936454849498328,"#482374"],[0.0969899665551839,"#482475"],[0.100334448160535,"#482576"],[0.103678929765886,"#482576"],[0.107023411371237,"#482777"],[0.110367892976589,"#482878"],[0.11371237458194,"#482979"],[0.117056856187291,"#472A7A"],[0.120401337792642,"#472B7A"],[0.123745819397993,"#472D7B"],[0.127090301003344,"#472D7B"],[0.130434782608696,"#472E7C"],[0.133779264214047,"#472F7D"],[0.137123745819398,"#46307E"],[0.140468227424749,"#46327E"],[0.1438127090301,"#46337F"],[0.147157190635451,"#463480"],[0.150501672240803,"#463480"],[0.153846153846154,"#453581"],[0.157190635451505,"#453781"],[0.160535117056856,"#453882"],[0.163879598662207,"#443983"],[0.167224080267558,"#443A83"],[0.17056856187291,"#443A83"],[0.173913043478261,"#443C84"],[0.177257525083612,"#433D84"],[0.180602006688963,"#433E85"],[0.183946488294314,"#423F85"],[0.187290969899666,"#424086"],[0.190635451505017,"#424186"],[0.193979933110368,"#424186"],[0.197324414715719,"#414387"],[0.20066889632107,"#414487"],[0.204013377926421,"#404588"],[0.207357859531773,"#404688"],[0.210702341137124,"#3F4788"],[0.214046822742475,"#3F4889"],[0.217391304347826,"#3F4889"],[0.220735785953177,"#3E4989"],[0.224080267558528,"#3E4A89"],[0.22742474916388,"#3E4C8A"],[0.230769230769231,"#3D4D8A"],[0.234113712374582,"#3D4E8A"],[0.237458193979933,"#3C4F8A"],[0.240802675585284,"#3C4F8A"],[0.244147157190635,"#3C508B"],[0.247491638795987,"#3B518B"],[0.250836120401338,"#3B528B"],[0.254180602006689,"#3A538B"],[0.25752508361204,"#3A548C"],[0.260869565217391,"#39558C"],[0.264214046822742,"#39558C"],[0.267558528428094,"#39568C"],[0.270903010033445,"#38588C"],[0.274247491638796,"#38598C"],[0.277591973244147,"#375A8C"],[0.280936454849498,"#375B8D"],[0.284280936454849,"#375B8D"],[0.287625418060201,"#365C8D"],[0.290969899665552,"#365D8D"],[0.294314381270903,"#355E8D"],[0.297658862876254,"#355F8D"],[0.301003344481605,"#34608D"],[0.304347826086956,"#34618D"],[0.307692307692308,"#34618D"],[0.311036789297659,"#33628D"],[0.31438127090301,"#33638D"],[0.317725752508361,"#32648E"],[0.321070234113712,"#32658E"],[0.324414715719063,"#31668E"],[0.327759197324415,"#31678E"],[0.331103678929766,"#31678E"],[0.334448160535117,"#31688E"],[0.337792642140468,"#30698E"],[0.341137123745819,"#306A8E"],[0.344481605351171,"#2F6B8E"],[0.347826086956522,"#2F6C8E"],[0.351170568561873,"#2E6D8E"],[0.354515050167224,"#2E6D8E"],[0.357859531772575,"#2E6E8E"],[0.361204013377926,"#2E6F8E"],[0.364548494983278,"#2D708E"],[0.367892976588629,"#2D718E"],[0.37123745819398,"#2C718E"],[0.374581939799331,"#2C728E"],[0.377926421404682,"#2C728E"],[0.381270903010033,"#2C738E"],[0.384615384615385,"#2B748E"],[0.387959866220736,"#2B758E"],[0.391304347826087,"#2A768E"],[0.394648829431438,"#2A778E"],[0.397993311036789,"#2A778E"],[0.40133779264214,"#2A788E"],[0.404682274247492,"#29798E"],[0.408026755852843,"#297A8E"],[0.411371237458194,"#297B8E"],[0.414715719063545,"#287C8E"],[0.418060200668896,"#287D8E"],[0.421404682274247,"#287D8E"],[0.424749163879599,"#277E8E"],[0.42809364548495,"#277F8E"],[0.431438127090301,"#27808E"],[0.434782608695652,"#26818E"],[0.438127090301003,"#26828E"],[0.441471571906354,"#26828E"],[0.444816053511706,"#26828E"],[0.448160535117057,"#25838E"],[0.451505016722408,"#25848E"],[0.454849498327759,"#25858E"],[0.45819397993311,"#24868E"],[0.461538461538462,"#24878E"],[0.464882943143813,"#23888E"],[0.468227424749164,"#23888E"],[0.471571906354515,"#23898E"],[0.474916387959866,"#238A8D"],[0.478260869565217,"#228B8D"],[0.481605351170569,"#228C8D"],[0.48494983277592,"#228D8D"],[0.488294314381271,"#218E8D"],[0.491638795986622,"#218E8D"],[0.494983277591973,"#218F8D"],[0.498327759197324,"#21908D"],[0.501672240802675,"#21918C"],[0.505016722408027,"#20928C"],[0.508361204013378,"#20928C"],[0.511705685618729,"#20928C"],[0.51505016722408,"#20938C"],[0.518394648829431,"#1F948C"],[0.521739130434783,"#1F958B"],[0.525083612040134,"#1F968B"],[0.528428093645485,"#1F978B"],[0.531772575250836,"#1F988B"],[0.535117056856187,"#1F988B"],[0.538461538461538,"#1F998A"],[0.54180602006689,"#1F9A8A"],[0.545150501672241,"#1E9B8A"],[0.548494983277592,"#1E9C89"],[0.551839464882943,"#1E9D89"],[0.555183946488294,"#1F9E89"],[0.558528428093645,"#1F9E89"],[0.561872909698997,"#1F9F88"],[0.565217391304348,"#1FA088"],[0.568561872909699,"#1FA188"],[0.57190635451505,"#1FA187"],[0.575250836120401,"#1FA287"],[0.578595317725752,"#20A386"],[0.581939799331104,"#20A386"],[0.585284280936455,"#20A486"],[0.588628762541806,"#21A585"],[0.591973244147157,"#21A685"],[0.595317725752508,"#22A785"],[0.598662207357859,"#22A884"],[0.602006688963211,"#23A983"],[0.605351170568562,"#23A983"],[0.608695652173913,"#24AA83"],[0.612040133779264,"#25AB82"],[0.615384615384615,"#25AC82"],[0.618729096989966,"#26AD81"],[0.622073578595318,"#27AD81"],[0.625418060200669,"#27AD81"],[0.62876254180602,"#28AE80"],[0.632107023411371,"#29AF7F"],[0.635451505016722,"#2AB07F"],[0.638795986622074,"#2CB17E"],[0.642140468227425,"#2DB27D"],[0.645484949832776,"#2EB37C"],[0.648829431438127,"#2EB37C"],[0.652173913043478,"#30B47C"],[0.655518394648829,"#31B57B"],[0.65886287625418,"#32B67A"],[0.662207357859532,"#34B679"],[0.665551839464883,"#35B779"],[0.668896321070234,"#36B878"],[0.672240802675585,"#37B878"],[0.675585284280936,"#39B977"],[0.678929765886288,"#3ABA76"],[0.682274247491639,"#3BBB75"],[0.68561872909699,"#3DBC74"],[0.688963210702341,"#3EBC73"],[0.692307692307692,"#40BD72"],[0.695652173913043,"#41BD72"],[0.698996655518395,"#42BE71"],[0.702341137123746,"#44BF70"],[0.705685618729097,"#46C06F"],[0.709030100334448,"#48C16E"],[0.712374581939799,"#49C16D"],[0.71571906354515,"#4BC26C"],[0.719063545150502,"#4DC26C"],[0.722408026755853,"#4EC36B"],[0.725752508361204,"#50C46A"],[0.729096989966555,"#52C569"],[0.732441471571906,"#54C568"],[0.735785953177257,"#55C667"],[0.739130434782609,"#57C666"],[0.74247491638796,"#59C765"],[0.745819397993311,"#5AC864"],[0.749163879598662,"#5CC863"],[0.752508361204013,"#5EC962"],[0.755852842809364,"#5FCA61"],[0.759197324414716,"#62CB5F"],[0.762541806020067,"#64CB5F"],[0.765886287625418,"#66CB5D"],[0.769230769230769,"#67CC5C"],[0.77257525083612,"#69CD5B"],[0.775919732441471,"#6CCD5A"],[0.779264214046823,"#6DCE59"],[0.782608695652174,"#6FCF57"],[0.785953177257525,"#71CF57"],[0.789297658862876,"#74D055"],[0.792642140468227,"#75D054"],[0.795986622073579,"#77D153"],[0.79933110367893,"#79D151"],[0.802675585284281,"#7BD250"],[0.806020066889632,"#7ED34F"],[0.809364548494983,"#80D34E"],[0.812709030100334,"#82D34D"],[0.816053511705686,"#84D44B"],[0.819397993311037,"#86D549"],[0.822742474916388,"#88D548"],[0.826086956521739,"#8AD647"],[0.82943143812709,"#8DD645"],[0.832775919732441,"#8FD644"],[0.836120401337793,"#91D743"],[0.839464882943144,"#93D741"],[0.842809364548495,"#95D840"],[0.846153846153846,"#97D83E"],[0.849498327759197,"#9AD93D"],[0.852842809364548,"#9CD93C"],[0.8561872909699,"#9ED93A"],[0.859531772575251,"#A0DA39"],[0.862876254180602,"#A2DA37"],[0.866220735785953,"#A5DB36"],[0.869565217391304,"#A7DB35"],[0.872909698996655,"#A9DC33"],[0.876254180602007,"#ABDC31"],[0.879598662207358,"#AEDC30"],[0.882943143812709,"#B0DD2F"],[0.88628762541806,"#B2DD2D"],[0.889632107023411,"#B5DE2B"],[0.892976588628763,"#B7DE2A"],[0.896321070234114,"#B9DE28"],[0.899665551839465,"#BBDE27"],[0.903010033444816,"#BEDF26"],[0.906354515050167,"#C0DF25"],[0.909698996655518,"#C2DF23"],[0.913043478260869,"#C4E021"],[0.916387959866221,"#C7E020"],[0.919732441471572,"#C9E11F"],[0.923076923076923,"#CBE11E"],[0.926421404682274,"#CEE11D"],[0.929765886287625,"#D0E11C"],[0.933110367892977,"#D2E21B"],[0.936454849498328,"#D4E21A"],[0.939799331103679,"#D7E219"],[0.94314381270903,"#D9E319"],[0.946488294314381,"#DBE319"],[0.949832775919732,"#DDE318"],[0.953177257525084,"#DFE318"],[0.956521739130435,"#E2E418"],[0.959866220735786,"#E4E419"],[0.963210702341137,"#E6E419"],[0.966555183946488,"#E8E419"],[0.969899665551839,"#EBE51A"],[0.973244147157191,"#EDE51B"],[0.976588628762542,"#EFE51C"],[0.979933110367893,"#F1E51D"],[0.983277591973244,"#F3E61E"],[0.986622073578595,"#F5E61F"],[0.989966555183946,"#F7E620"],[0.993311036789298,"#F9E622"],[0.996655518394649,"#FBE723"],[1,"#FDE725"]],"colorbar":{"bgcolor":"rgba(255,255,255,1)","bordercolor":"transparent","borderwidth":1.88976377952756,"thickness":23.04,"title":null,"titlefont":{"color":"rgba(0,0,0,1)","family":"","size":14.6118721461187},"tickmode":"array","ticktext":["-1.5","-1.0","-0.5","0.0","0.5","1.0","1.5"],"tickvals":[0.0271567111147637,0.186922394054594,0.346688076994425,0.506453759934255,0.666219442874086,0.825985125813916,0.985750808753747],"tickfont":{"color":"rgba(0,0,0,1)","family":"","size":11.689497716895},"ticklen":2,"len":0.5}},"xaxis":"x","yaxis":"y3","frame":null},{"x":[5.27787699113601,5.27787699113601,null,5.27787699113601,2.07592133544238,null,2.07592133544238,2.07592133544238,null,2.07592133544238,1.74818534439332,null,1.74818534439332,1.74818534439332,null,1.74818534439332,0,null,1.74818534439332,1.74818534439332,null,1.74818534439332,1.12339133351962,null,1.12339133351962,1.12339133351962,null,1.12339133351962,0.652086977447083,null,0.652086977447083,0.652086977447083,null,0.652086977447083,0,null,0.652086977447083,0.652086977447083,null,0.652086977447083,0,null,1.12339133351962,1.12339133351962,null,1.12339133351962,0,null,2.07592133544238,2.07592133544238,null,2.07592133544238,0,null,5.27787699113601,5.27787699113601,null,5.27787699113601,2.27612743813117,null,2.27612743813117,2.27612743813117,null,2.27612743813117,1.23340544919341,null,1.23340544919341,1.23340544919341,null,1.23340544919341,0,null,1.23340544919341,1.23340544919341,null,1.23340544919341,0,null,2.27612743813117,2.27612743813117,null,2.27612743813117,1.81508679598828,null,1.81508679598828,1.81508679598828,null,1.81508679598828,1.24003809032464,null,1.24003809032464,1.24003809032464,null,1.24003809032464,0.499060959410415,null,0.499060959410415,0.499060959410415,null,0.499060959410415,0,null,0.499060959410415,0.499060959410415,null,0.499060959410415,0,null,1.24003809032464,1.24003809032464,null,1.24003809032464,0.81666442757416,null,0.81666442757416,0.81666442757416,null,0.81666442757416,0.232064854588764,null,0.232064854588764,0.232064854588764,null,0.232064854588764,0,null,0.232064854588764,0.232064854588764,null,0.232064854588764,0,null,0.81666442757416,0.81666442757416,null,0.81666442757416,0.556133302726053,null,0.556133302726053,0.556133302726053,null,0.556133302726053,0.381542492299851,null,0.381542492299851,0.381542492299851,null,0.381542492299851,0.30056512594899,null,0.30056512594899,0.30056512594899,null,0.30056512594899,0,null,0.30056512594899,0.30056512594899,null,0.30056512594899,0,null,0.381542492299851,0.381542492299851,null,0.381542492299851,0,null,0.556133302726053,0.556133302726053,null,0.556133302726053,0.518063294728804,null,0.518063294728804,0.518063294728804,null,0.518063294728804,0,null,0.518063294728804,0.518063294728804,null,0.518063294728804,0,null,1.81508679598828,1.81508679598828,null,1.81508679598828,0.796625865178289,null,0.796625865178289,0.796625865178289,null,0.796625865178289,0.723403361813129,null,0.723403361813129,0.723403361813129,null,0.723403361813129,0,null,0.723403361813129,0.723403361813129,null,0.723403361813129,0.449668231087046,null,0.449668231087046,0.449668231087046,null,0.449668231087046,0,null,0.449668231087046,0.449668231087046,null,0.449668231087046,0,null,0.796625865178289,0.796625865178289,null,0.796625865178289,0],"y":[7.07421875,3.5625,null,3.5625,3.5625,null,3.5625,2.125,null,2.125,2.125,null,2.125,1,null,1,1,null,2.125,3.25,null,3.25,3.25,null,3.25,2.5,null,2.5,2.5,null,2.5,2,null,2,2,null,2.5,3,null,3,3,null,3.25,4,null,4,4,null,3.5625,5,null,5,5,null,7.07421875,10.5859375,null,10.5859375,10.5859375,null,10.5859375,6.5,null,6.5,6.5,null,6.5,6,null,6,6,null,6.5,7,null,7,7,null,10.5859375,14.671875,null,14.671875,14.671875,null,14.671875,10.46875,null,10.46875,10.46875,null,10.46875,8.5,null,8.5,8.5,null,8.5,8,null,8,8,null,8.5,9,null,9,9,null,10.46875,12.4375,null,12.4375,12.4375,null,12.4375,10.5,null,10.5,10.5,null,10.5,10,null,10,10,null,10.5,11,null,11,11,null,12.4375,14.375,null,14.375,14.375,null,14.375,13.25,null,13.25,13.25,null,13.25,12.5,null,12.5,12.5,null,12.5,12,null,12,12,null,12.5,13,null,13,13,null,13.25,14,null,14,14,null,14.375,15.5,null,15.5,15.5,null,15.5,15,null,15,15,null,15.5,16,null,16,16,null,14.671875,18.875,null,18.875,18.875,null,18.875,17.75,null,17.75,17.75,null,17.75,17,null,17,17,null,17.75,18.5,null,18.5,18.5,null,18.5,18,null,18,18,null,18.5,19,null,19,19,null,18.875,20,null,20,20],"text":["y: 5.2778770","y: 5.2778770",null,"y: 5.2778770","y: 5.2778770",null,"y: 2.0759213","y: 2.0759213",null,"y: 2.0759213","y: 2.0759213",null,"y: 1.7481853","y: 1.7481853",null,"y: 1.7481853","y: 1.7481853",null,"y: 1.7481853","y: 1.7481853",null,"y: 1.7481853","y: 1.7481853",null,"y: 1.1233913","y: 1.1233913",null,"y: 1.1233913","y: 1.1233913",null,"y: 0.6520870","y: 0.6520870",null,"y: 0.6520870","y: 0.6520870",null,"y: 0.6520870","y: 0.6520870",null,"y: 0.6520870","y: 0.6520870",null,"y: 1.1233913","y: 1.1233913",null,"y: 1.1233913","y: 1.1233913",null,"y: 2.0759213","y: 2.0759213",null,"y: 2.0759213","y: 2.0759213",null,"y: 5.2778770","y: 5.2778770",null,"y: 5.2778770","y: 5.2778770",null,"y: 2.2761274","y: 2.2761274",null,"y: 2.2761274","y: 2.2761274",null,"y: 1.2334054","y: 1.2334054",null,"y: 1.2334054","y: 1.2334054",null,"y: 1.2334054","y: 1.2334054",null,"y: 1.2334054","y: 1.2334054",null,"y: 2.2761274","y: 2.2761274",null,"y: 2.2761274","y: 2.2761274",null,"y: 1.8150868","y: 1.8150868",null,"y: 1.8150868","y: 1.8150868",null,"y: 1.2400381","y: 1.2400381",null,"y: 1.2400381","y: 1.2400381",null,"y: 0.4990610","y: 0.4990610",null,"y: 0.4990610","y: 0.4990610",null,"y: 0.4990610","y: 0.4990610",null,"y: 0.4990610","y: 0.4990610",null,"y: 1.2400381","y: 1.2400381",null,"y: 1.2400381","y: 1.2400381",null,"y: 0.8166644","y: 0.8166644",null,"y: 0.8166644","y: 0.8166644",null,"y: 0.2320649","y: 0.2320649",null,"y: 0.2320649","y: 0.2320649",null,"y: 0.2320649","y: 0.2320649",null,"y: 0.2320649","y: 0.2320649",null,"y: 0.8166644","y: 0.8166644",null,"y: 0.8166644","y: 0.8166644",null,"y: 0.5561333","y: 0.5561333",null,"y: 0.5561333","y: 0.5561333",null,"y: 0.3815425","y: 0.3815425",null,"y: 0.3815425","y: 0.3815425",null,"y: 0.3005651","y: 0.3005651",null,"y: 0.3005651","y: 0.3005651",null,"y: 0.3005651","y: 0.3005651",null,"y: 0.3005651","y: 0.3005651",null,"y: 0.3815425","y: 0.3815425",null,"y: 0.3815425","y: 0.3815425",null,"y: 0.5561333","y: 0.5561333",null,"y: 0.5561333","y: 0.5561333",null,"y: 0.5180633","y: 0.5180633",null,"y: 0.5180633","y: 0.5180633",null,"y: 0.5180633","y: 0.5180633",null,"y: 0.5180633","y: 0.5180633",null,"y: 1.8150868","y: 1.8150868",null,"y: 1.8150868","y: 1.8150868",null,"y: 0.7966259","y: 0.7966259",null,"y: 0.7966259","y: 0.7966259",null,"y: 0.7234034","y: 0.7234034",null,"y: 0.7234034","y: 0.7234034",null,"y: 0.7234034","y: 0.7234034",null,"y: 0.7234034","y: 0.7234034",null,"y: 0.4496682","y: 0.4496682",null,"y: 0.4496682","y: 0.4496682",null,"y: 0.4496682","y: 0.4496682",null,"y: 0.4496682","y: 0.4496682",null,"y: 0.7966259","y: 0.7966259",null,"y: 0.7966259","y: 0.7966259"],"type":"scatter","mode":"lines","line":{"width":2.26771653543307,"color":"rgba(0,0,0,1)","dash":"solid"},"hoveron":"points","showlegend":false,"xaxis":"x2","yaxis":"y3","hoverinfo":"text","frame":null},{"x":[5.27787699113601,2.07592133544238,1.74818534439332,0,1.12339133351962,0.652086977447083,0,0,0,0,2.27612743813117,1.23340544919341,0,0,1.81508679598828,1.24003809032464,0.499060959410415,0,0,0.81666442757416,0.232064854588764,0,0,0.556133302726053,0.381542492299851,0.30056512594899,0,0,0,0.518063294728804,0,0,0.796625865178289,0.723403361813129,0,0.449668231087046,0,0,0],"y":[7.07421875,3.5625,2.125,1,3.25,2.5,2,3,4,5,10.5859375,6.5,6,7,14.671875,10.46875,8.5,8,9,12.4375,10.5,10,11,14.375,13.25,12.5,12,13,14,15.5,15,16,18.875,17.75,17,18.5,18,19,20],"text":["y: 5.2778770","y: 2.0759213","y: 1.7481853","y: 0.0000000","y: 1.1233913","y: 0.6520870","y: 0.0000000","y: 0.0000000","y: 0.0000000","y: 0.0000000","y: 2.2761274","y: 1.2334054","y: 0.0000000","y: 0.0000000","y: 1.8150868","y: 1.2400381","y: 0.4990610","y: 0.0000000","y: 0.0000000","y: 0.8166644","y: 0.2320649","y: 0.0000000","y: 0.0000000","y: 0.5561333","y: 0.3815425","y: 0.3005651","y: 0.0000000","y: 0.0000000","y: 0.0000000","y: 0.5180633","y: 0.0000000","y: 0.0000000","y: 0.7966259","y: 0.7234034","y: 0.0000000","y: 0.4496682","y: 0.0000000","y: 0.0000000","y: 0.0000000"],"type":"scatter","mode":"markers","marker":{"autocolorscale":false,"color":"transparent","opacity":1,"size":null,"symbol":null,"line":{"width":1.88976377952756,"color":"transparent"}},"hoveron":"points","showlegend":false,"xaxis":"x2","yaxis":"y3","hoverinfo":"text","frame":null}],"layout":{"xaxis":{"domain":[0,0.8],"automargin":true,"type":"linear","autorange":false,"range":[0.5,8.5],"tickmode":"array","ticktext":["513","521","509","517","520","512","508","516"],"tickvals":[1,2,3,4,5,6,7,8],"categoryorder":"array","categoryarray":["513","521","509","517","520","512","508","516"],"nticks":null,"ticks":"outside","tickcolor":"rgba(51,51,51,1)","ticklen":3.65296803652968,"tickwidth":0.66417600664176,"showticklabels":true,"tickfont":{"color":"rgba(77,77,77,1)","family":"","size":13.2835201328352},"tickangle":-45,"showline":true,"linecolor":"rgba(0,0,0,1)","linewidth":0.66417600664176,"showgrid":false,"gridcolor":null,"gridwidth":0,"zeroline":false,"anchor":"y3","title":"","hoverformat":".2f"},"xaxis2":{"domain":[0.8,1],"automargin":true,"showticklabels":false,"showgrid":false,"zeroline":false,"anchor":"y3","type":"linear","autorange":false,"range":[0,5.27787699113601],"tickmode":"array","ticktext":["0","1","2","3","4","5"],"tickvals":[0,1,2,3,4,5],"categoryorder":"array","categoryarray":["0","1","2","3","4","5"],"nticks":null,"ticks":"","tickcolor":null,"ticklen":3.65296803652968,"tickwidth":0,"tickfont":{"color":null,"family":null,"size":0},"tickangle":-0,"showline":false,"linecolor":null,"linewidth":0,"gridcolor":null,"gridwidth":0,"title":{"text":"","font":{"color":null,"family":null,"size":0}},"hoverformat":".2f"},"yaxis3":{"domain":[0,0.7],"automargin":true,"type":"linear","autorange":false,"range":[0.5,20.5],"tickmode":"array","ticktext":["DNM1","VCAM1","ADAM12","PRSS35","WNT2","PDPN","FAM107A","ACSS1","HIF3A","STEAP2","CACNB2","NEXN","DUSP1","SPARCL1","FGD4","ZBTB16","MT2A","DNAJB4","MAOA","TIMP4"],"tickvals":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20],"categoryorder":"array","categoryarray":["DNM1","VCAM1","ADAM12","PRSS35","WNT2","PDPN","FAM107A","ACSS1","HIF3A","STEAP2","CACNB2","NEXN","DUSP1","SPARCL1","FGD4","ZBTB16","MT2A","DNAJB4","MAOA","TIMP4"],"nticks":null,"ticks":"outside","tickcolor":"rgba(51,51,51,1)","ticklen":3.65296803652968,"tickwidth":0.66417600664176,"showticklabels":true,"tickfont":{"color":"rgba(77,77,77,1)","family":"","size":13.2835201328352},"tickangle":-0,"showline":true,"linecolor":"rgba(0,0,0,1)","linewidth":0.66417600664176,"showgrid":false,"gridcolor":null,"gridwidth":0,"zeroline":false,"anchor":"x","title":"","hoverformat":".2f"},"yaxis2":{"domain":[0.7,0.8],"automargin":true,"showticklabels":true,"showgrid":true,"zeroline":false,"anchor":"x","type":"linear","autorange":false,"range":[0.4,1.6],"tickmode":"array","ticktext":["dex"],"tickvals":[1],"categoryorder":"array","categoryarray":["dex"],"nticks":null,"ticks":"","tickcolor":null,"ticklen":3.65296803652968,"tickwidth":0,"tickfont":{"color":"rgba(77,77,77,1)","family":"","size":13.2835201328352},"tickangle":-0,"showline":false,"linecolor":null,"linewidth":0,"gridcolor":"rgba(255,255,255,1)","gridwidth":0.66417600664176,"title":{"text":"","font":{"color":"rgba(0,0,0,1)","family":"","size":14.6118721461187}},"hoverformat":".2f"},"yaxis":{"domain":[0.8,1],"automargin":true,"showticklabels":false,"showgrid":false,"zeroline":false,"anchor":"x","type":"linear","autorange":false,"range":[0,9.37052889139853],"tickmode":"array","ticktext":["0.0","2.5","5.0","7.5"],"tickvals":[0,2.5,5,7.5],"categoryorder":"array","categoryarray":["0.0","2.5","5.0","7.5"],"nticks":null,"ticks":"","tickcolor":null,"ticklen":3.65296803652968,"tickwidth":0,"tickfont":{"color":null,"family":null,"size":0},"tickangle":-0,"showline":false,"linecolor":null,"linewidth":0,"gridcolor":null,"gridwidth":0,"title":{"text":"","font":{"color":null,"family":null,"size":0}},"hoverformat":".2f"},"annotations":[],"shapes":[{"type":"rect","fillcolor":null,"line":{"color":null,"width":0,"linetype":[]},"yref":"paper","xref":"paper","x0":0,"x1":0.8,"y0":0.8,"y1":1},{"type":"rect","fillcolor":null,"line":{"color":null,"width":0,"linetype":[]},"yref":"paper","xref":"paper","x0":0,"x1":0.8,"y0":0.7,"y1":0.8},{"type":"rect","fillcolor":null,"line":{"color":null,"width":0,"linetype":[]},"yref":"paper","xref":"paper","x0":0,"x1":0.8,"y0":0,"y1":0.7},{"type":"rect","fillcolor":null,"line":{"color":null,"width":0,"linetype":[]},"yref":"paper","xref":"paper","x0":0.8,"x1":1,"y0":0,"y1":0.7}],"images":[],"margin":{"t":50,"r":1,"b":0.5,"l":1},"font":{"color":"rgba(0,0,0,1)","family":"","size":14.6118721461187},"showlegend":false,"legend":{"bgcolor":"rgba(255,255,255,1)","bordercolor":"transparent","borderwidth":1.88976377952756,"font":{"color":"rgba(0,0,0,1)","family":"","size":11.689497716895},"title":{"text":"","font":{"color":"rgba(0,0,0,1)","family":"","size":14.6118721461187}},"y":1,"yanchor":"top"},"hovermode":"closest","barmode":"relative","paper_bgcolor":"rgba(255,255,255,1)","title":"interactively explore airway DE genes"},"attrs":{"fd0e7e05b089":{"xend":{},"yend":{},"colour":{},"linetype":{},"size":{},"x":{},"y":{},"type":"scatter"},"fd0e27893302":{"colour":{},"shape":{},"size":{},"x":{},"y":{}},"fd0e1696cad8":{"alpha_stroke":1,"sizes":[10,100],"spans":[1,20]},"fd0e2925ba20":{"fill":{},"x":{},"y":{},"type":"scatter"},"fd0e1728d35":{"alpha_stroke":1,"sizes":[10,100],"spans":[1,20]},"fd0e65ff9c38":{"x":{},"y":{},"fill":{},"text":{},"type":"heatmap"},"fd0e9a2591e":{"xend":{},"yend":{},"colour":{},"linetype":{},"size":{},"x":{},"y":{},"type":"scatter"},"fd0e188c583":{"colour":{},"shape":{},"size":{},"x":{},"y":{}}},"source":"A","config":{"doubleClick":"reset","modeBarButtonsToAdd":["hoverclosest","hovercompare"],"showSendToCloud":false,"displaylogo":false,"modeBarButtonsToRemove":["sendDataToCloud","select2d","lasso2d","autoScale2d","hoverClosestCartesian","hoverCompareCartesian","sendDataToCloud"]},"highlight":{"on":"plotly_click","persistent":false,"dynamic":false,"selectize":false,"opacityDim":0.2,"selected":{"opacity":1},"debounce":0},"subplot":true,"shinyEvents":["plotly_hover","plotly_click","plotly_selected","plotly_relayout","plotly_brushed","plotly_brushing","plotly_clickannotation","plotly_doubleclick","plotly_deselect","plotly_afterplot","plotly_sunburstclick"],"base_url":"https://plot.ly"},"evals":[],"jsHooks":[]}</script>