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diff --git a/02-Chapter2.Rmd b/02-Chapter2.Rmd
@@ -151,7 +151,7 @@ Data are stored in data structures. There are many different data structures in
 + **Data frames:** similar to a matrix but can contain different data types and additional attributes such as row names (and is one of the most common data structures in environmental health research). Tibbles are a stricter type of data frame implemented in the *tidyverse* package.
 + **Lists:** a special type of vector that acts as a container – other data structures can be stored within the list, and lists can contain other lists. Lists can contain elements that are different data structures. 
 
-```{r, echo=FALSE, fig.align = "center", fig.cap= "Created with *BioRender.com*"}
+```{r, echo=FALSE, fig.align = "center"}
 knitr::include_graphics("Module2_1_Input/Image5.png")
 ```
 

diff --git a/03-Chapter3.Rmd b/03-Chapter3.Rmd
@@ -1,4 +1,4 @@
-# (PART\*) Chapter 3 Basics of <br>Data Analysis and Visualizations {-}
+# (PART\*) Chapter 3 Basics of Data <br>Analysis and Visualizations {-}
 
 # 3.1 Data Visualizations
 

diff --git a/04-Chapter4.Rmd b/04-Chapter4.Rmd
@@ -1,4 +1,4 @@
-# (PART\*) Chapter 4 Converting Wet Lab Data into Dry Lab Analyses {-}
+# (PART\*) Chapter 4 Converting Wet <br>Lab Data into Dry Lab <br>Analyses {-}
 
 # 4.1 Overview of Experimental Design and Example Data 
 

diff --git a/05-Chapter5.Rmd b/05-Chapter5.Rmd
@@ -1,4 +1,4 @@
-# (PART\*) Chapter 5 Machine Learning & Artificial Intelligence {-}
+# (PART\*) Chapter 5 Machine Learning <br>& Artificial Intelligence {-}
 
 # 5.1 Introduction to Artificial Intelligence, Machine Learning, and Predictive Modeling for Environmental Health
 

diff --git a/06-Chapter6.Rmd b/06-Chapter6.Rmd
@@ -1,4 +1,4 @@
-# (PART\*) Chapter 6 Applications in Toxicology & Exposure Science {-}
+# (PART\*) Chapter 6 Applications in <br>Toxicology & Exposure <br>Science {-}
 
 # 6.1 Descriptive Cohort Analyses
 
@@ -525,7 +525,7 @@ Using a more expanded demographics file ("Module6_1_TYKInput.xlsx"), create a de
 + The two new variables (home location and home type) included
 + The table split by which site the participant visited
 + Variable names and values presented in a publication-quality format (first letters capitalized, spaces between words, no underscores) 
-::: 
+:::
 
 # 6.2 -Omics and System Biology: Transcriptomic Applications
 
@@ -1423,11 +1423,11 @@ Test Your Knowledge
 </label>
 
 :::tyk
-
 Using "Module6_2_TYKInput1.csv" (gene counts) and "Module6_2_TYKInput2.csv" (sample info) data sets, which have already been run through the QC process described in this module and are ready for analysis: 
 
 1. Conduct a differential expression analysis associated with "Season" using DESeq2. (Don't worry about including any covariates or using RUV).
 2. Find the number of significant differentially expressed genes associated with "Season", at the .05 level.
+:::
 
 # 6.3 Mixtures Analysis Methods Part 1: Overview and Example with Quantile G-Computation 
 

diff --git a/07-Chapter7.Rmd b/07-Chapter7.Rmd
@@ -1,4 +1,4 @@
-# (PART\*) Chapter 7 Environmental Health Database Mining {-}
+# (PART\*) Chapter 7 Environmental<br> Health Database Mining {-}
 
 # 7.1 Comparative Toxicogenomics Database
 

diff --git a/VennDiagram.2024-12-06_13-22-00.944893.log b/VennDiagram.2024-12-06_13-22-00.944893.log
@@ -0,0 +1,36 @@
+INFO [2024-12-06 13:22:00] $x
+INFO [2024-12-06 13:22:00] list(exp_filt$`Gene Symbol`, met_filt$`Gene Symbol`)
+INFO [2024-12-06 13:22:00] 
+INFO [2024-12-06 13:22:00] $category.names
+INFO [2024-12-06 13:22:00] c("Altered Expression", "Altered Methylation")
+INFO [2024-12-06 13:22:00] 
+INFO [2024-12-06 13:22:00] $filename
+INFO [2024-12-06 13:22:00] NULL
+INFO [2024-12-06 13:22:00] 
+INFO [2024-12-06 13:22:00] $output
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+INFO [2024-12-06 13:22:00] [1] "bold"
+INFO [2024-12-06 13:22:00] 
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+INFO [2024-12-06 13:22:00] [1] "outer"
+INFO [2024-12-06 13:22:00] 
+INFO [2024-12-06 13:22:00] $cat.pos
+INFO [2024-12-06 13:22:00] c(-27, 27)
+INFO [2024-12-06 13:22:00] 
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+INFO [2024-12-06 13:22:00] c(0.055, 0.055)
+INFO [2024-12-06 13:22:00] 
+INFO [2024-12-06 13:22:00] $col
+INFO [2024-12-06 13:22:00] c("#440154ff", "#21908dff")
+INFO [2024-12-06 13:22:00] 
+INFO [2024-12-06 13:22:00] $fill
+INFO [2024-12-06 13:22:00] c(alpha("#440154ff", 0.3), alpha("#21908dff", 0.3))
+INFO [2024-12-06 13:22:00] 
+INFO [2024-12-06 13:22:00] [[12]]
+INFO [2024-12-06 13:22:00] 
+INFO [2024-12-06 13:22:00] 
diff --git a/VennDiagram.2024-12-06_14-17-20.877928.log b/VennDiagram.2024-12-06_14-17-20.877928.log
@@ -0,0 +1,36 @@
+INFO [2024-12-06 14:17:20] $x
+INFO [2024-12-06 14:17:20] list(exp_filt$`Gene Symbol`, met_filt$`Gene Symbol`)
+INFO [2024-12-06 14:17:20] 
+INFO [2024-12-06 14:17:20] $category.names
+INFO [2024-12-06 14:17:20] c("Altered Expression", "Altered Methylation")
+INFO [2024-12-06 14:17:20] 
+INFO [2024-12-06 14:17:20] $filename
+INFO [2024-12-06 14:17:20] NULL
+INFO [2024-12-06 14:17:20] 
+INFO [2024-12-06 14:17:20] $output
+INFO [2024-12-06 14:17:20] F
+INFO [2024-12-06 14:17:20] 
+INFO [2024-12-06 14:17:20] $cat.cex
+INFO [2024-12-06 14:17:20] [1] 1.15
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+INFO [2024-12-06 14:17:20] [1] "bold"
+INFO [2024-12-06 14:17:20] 
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+INFO [2024-12-06 14:17:20] [1] "outer"
+INFO [2024-12-06 14:17:20] 
+INFO [2024-12-06 14:17:20] $cat.pos
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+INFO [2024-12-06 14:17:20] 
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+INFO [2024-12-06 14:17:20] c(0.055, 0.055)
+INFO [2024-12-06 14:17:20] 
+INFO [2024-12-06 14:17:20] $col
+INFO [2024-12-06 14:17:20] c("#440154ff", "#21908dff")
+INFO [2024-12-06 14:17:20] 
+INFO [2024-12-06 14:17:20] $fill
+INFO [2024-12-06 14:17:20] c(alpha("#440154ff", 0.3), alpha("#21908dff", 0.3))
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+INFO [2024-12-06 14:17:20] 
diff --git a/_main_files/figure-html/unnamed-chunk-186-1.png b/_main_files/figure-html/unnamed-chunk-186-1.png
diff --git a/_main_files/figure-html/unnamed-chunk-194-1.png b/_main_files/figure-html/unnamed-chunk-194-1.png
diff --git a/advanced-multi-group-comparisons.html b/advanced-multi-group-comparisons.html
diff --git a/chemical-read-across-for-toxicity-predictions.html b/chemical-read-across-for-toxicity-predictions.html
@@ -23,7 +23,7 @@
 <meta name="author" content="Rager Lab" />
 
 
-<meta name="date" content="2024-10-17" />
+<meta name="date" content="2024-12-06" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1" />
   <meta name="apple-mobile-web-app-capable" content="yes" />
@@ -254,7 +254,7 @@
 <li class="chapter" data-level="" data-path="improving-coding-efficiencies.html"><a href="improving-coding-efficiencies.html#concluding-remarks-7"><i class="fa fa-check"></i>Concluding Remarks</a></li>
 <li class="chapter" data-level="" data-path="improving-coding-efficiencies.html"><a href="improving-coding-efficiencies.html#additional-resources-2"><i class="fa fa-check"></i>Additional Resources</a></li>
 </ul></li>
-<li class="part"><span><b>Chapter 3 Basics of <br>Data Analysis and Visualizations</b></span></li>
+<li class="part"><span><b>Chapter 3 Basics of Data <br>Analysis and Visualizations</b></span></li>
 <li class="chapter" data-level="" data-path="data-visualizations.html"><a href="data-visualizations.html"><i class="fa fa-check"></i>3.1 Data Visualizations</a>
 <ul>
 <li class="chapter" data-level="" data-path="data-visualizations.html"><a href="data-visualizations.html#introduction-to-data-visualizations"><i class="fa fa-check"></i>Introduction to Data Visualizations</a></li>
@@ -294,7 +294,7 @@
 <li class="chapter" data-level="" data-path="intoduction-to-statistical-tests.html"><a href="intoduction-to-statistical-tests.html#statistical-evaluations-of-categorical-data-using-the-chi-squared-test-and-fishers-exact-test"><i class="fa fa-check"></i>Statistical Evaluations of Categorical Data using the Chi-Squared Test and Fisher’s Exact Test</a></li>
 <li class="chapter" data-level="" data-path="intoduction-to-statistical-tests.html"><a href="intoduction-to-statistical-tests.html#concluding-remarks-11"><i class="fa fa-check"></i>Concluding Remarks</a></li>
 </ul></li>
-<li class="part"><span><b>Chapter 4 Converting Wet Lab Data into Dry Lab Analyses</b></span></li>
+<li class="part"><span><b>Chapter 4 Converting Wet <br>Lab Data into Dry Lab <br>Analyses</b></span></li>
 <li class="chapter" data-level="" data-path="overview-of-experimental-design-and-example-data.html"><a href="overview-of-experimental-design-and-example-data.html"><i class="fa fa-check"></i>4.1 Overview of Experimental Design and Example Data</a>
 <ul>
 <li class="chapter" data-level="" data-path="overview-of-experimental-design-and-example-data.html"><a href="overview-of-experimental-design-and-example-data.html#introduction-to-training-module-12"><i class="fa fa-check"></i>Introduction to Training Module</a></li>
@@ -345,7 +345,7 @@
 <li class="chapter" data-level="" data-path="advanced-multi-group-comparisons.html"><a href="advanced-multi-group-comparisons.html#ancova-example"><i class="fa fa-check"></i>ANCOVA Example</a></li>
 <li class="chapter" data-level="" data-path="advanced-multi-group-comparisons.html"><a href="advanced-multi-group-comparisons.html#concluding-remarks-17"><i class="fa fa-check"></i>Concluding Remarks</a></li>
 </ul></li>
-<li class="part"><span><b>Chapter 5 Machine Learning &amp; Artificial Intelligence</b></span></li>
+<li class="part"><span><b>Chapter 5 Machine Learning <br>&amp; Artificial Intelligence</b></span></li>
 <li class="chapter" data-level="" data-path="introduction-to-artificial-intelligence-machine-learning-and-predictive-modeling-for-environmental-health.html"><a href="introduction-to-artificial-intelligence-machine-learning-and-predictive-modeling-for-environmental-health.html"><i class="fa fa-check"></i>5.1 Introduction to Artificial Intelligence, Machine Learning, and Predictive Modeling for Environmental Health</a>
 <ul>
 <li class="chapter" data-level="" data-path="introduction-to-artificial-intelligence-machine-learning-and-predictive-modeling-for-environmental-health.html"><a href="introduction-to-artificial-intelligence-machine-learning-and-predictive-modeling-for-environmental-health.html#introduction-to-training-module-18"><i class="fa fa-check"></i>Introduction to Training Module</a></li>
@@ -400,7 +400,7 @@
 <li class="chapter" data-level="" data-path="unsupervised-machine-learning-part-2-additional-clustering-applications.html"><a href="unsupervised-machine-learning-part-2-additional-clustering-applications.html#variable-contributions"><i class="fa fa-check"></i>Variable Contributions</a></li>
 <li class="chapter" data-level="" data-path="unsupervised-machine-learning-part-2-additional-clustering-applications.html"><a href="unsupervised-machine-learning-part-2-additional-clustering-applications.html#concluding-remarks-22"><i class="fa fa-check"></i>Concluding Remarks</a></li>
 </ul></li>
-<li class="part"><span><b>Chapter 6 Applications in Toxicology &amp; Exposure Science</b></span></li>
+<li class="part"><span><b>Chapter 6 Applications in <br>Toxicology &amp; Exposure <br>Science</b></span></li>
 <li class="chapter" data-level="" data-path="descriptive-cohort-analyses.html"><a href="descriptive-cohort-analyses.html"><i class="fa fa-check"></i>6.1 Descriptive Cohort Analyses</a>
 <ul>
 <li class="chapter" data-level="" data-path="descriptive-cohort-analyses.html"><a href="descriptive-cohort-analyses.html#introduction-to-training-module-23"><i class="fa fa-check"></i>Introduction to Training Module</a></li>
@@ -463,7 +463,7 @@
 <li class="chapter" data-level="" data-path="toxicokinetic-modeling.html"><a href="toxicokinetic-modeling.html#reverse-tk-calculating-administered-equivalent-doses-for-toxcast-bioactive-concentrations"><i class="fa fa-check"></i>Reverse TK: Calculating Administered Equivalent Doses for ToxCast Bioactive Concentrations</a></li>
 <li class="chapter" data-level="" data-path="toxicokinetic-modeling.html"><a href="toxicokinetic-modeling.html#comparing-equivalent-doses-estimated-to-elicit-toxicity-hazard-to-external-exposure-estimates-exposure-for-chemical-prioritization-by-bioactivity-exposure-ratios-bers"><i class="fa fa-check"></i>Comparing Equivalent Doses Estimated to Elicit Toxicity (Hazard) to External Exposure Estimates (Exposure), for Chemical Prioritization by Bioactivity-Exposure Ratios (BERs)</a></li>
 </ul></li>
-<li class="part"><span><b>Chapter 7 Environmental Health Database Mining</b></span></li>
+<li class="part"><span><b>Chapter 7 Environmental<br> Health Database Mining</b></span></li>
 <li class="chapter" data-level="" data-path="comparative-toxicogenomics-database.html"><a href="comparative-toxicogenomics-database.html"><i class="fa fa-check"></i>7.1 Comparative Toxicogenomics Database</a>
 <ul>
 <li class="chapter" data-level="" data-path="comparative-toxicogenomics-database.html"><a href="comparative-toxicogenomics-database.html#introduction-to-training-module-30"><i class="fa fa-check"></i>Introduction to Training Module</a></li>

diff --git a/coding-best-practices.html b/coding-best-practices.html
@@ -23,7 +23,7 @@
 <meta name="author" content="Rager Lab" />
 
 
-<meta name="date" content="2024-10-17" />
+<meta name="date" content="2024-12-06" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1" />
   <meta name="apple-mobile-web-app-capable" content="yes" />
@@ -254,7 +254,7 @@
 <li class="chapter" data-level="" data-path="improving-coding-efficiencies.html"><a href="improving-coding-efficiencies.html#concluding-remarks-7"><i class="fa fa-check"></i>Concluding Remarks</a></li>
 <li class="chapter" data-level="" data-path="improving-coding-efficiencies.html"><a href="improving-coding-efficiencies.html#additional-resources-2"><i class="fa fa-check"></i>Additional Resources</a></li>
 </ul></li>
-<li class="part"><span><b>Chapter 3 Basics of <br>Data Analysis and Visualizations</b></span></li>
+<li class="part"><span><b>Chapter 3 Basics of Data <br>Analysis and Visualizations</b></span></li>
 <li class="chapter" data-level="" data-path="data-visualizations.html"><a href="data-visualizations.html"><i class="fa fa-check"></i>3.1 Data Visualizations</a>
 <ul>
 <li class="chapter" data-level="" data-path="data-visualizations.html"><a href="data-visualizations.html#introduction-to-data-visualizations"><i class="fa fa-check"></i>Introduction to Data Visualizations</a></li>
@@ -294,7 +294,7 @@
 <li class="chapter" data-level="" data-path="intoduction-to-statistical-tests.html"><a href="intoduction-to-statistical-tests.html#statistical-evaluations-of-categorical-data-using-the-chi-squared-test-and-fishers-exact-test"><i class="fa fa-check"></i>Statistical Evaluations of Categorical Data using the Chi-Squared Test and Fisher’s Exact Test</a></li>
 <li class="chapter" data-level="" data-path="intoduction-to-statistical-tests.html"><a href="intoduction-to-statistical-tests.html#concluding-remarks-11"><i class="fa fa-check"></i>Concluding Remarks</a></li>
 </ul></li>
-<li class="part"><span><b>Chapter 4 Converting Wet Lab Data into Dry Lab Analyses</b></span></li>
+<li class="part"><span><b>Chapter 4 Converting Wet <br>Lab Data into Dry Lab <br>Analyses</b></span></li>
 <li class="chapter" data-level="" data-path="overview-of-experimental-design-and-example-data.html"><a href="overview-of-experimental-design-and-example-data.html"><i class="fa fa-check"></i>4.1 Overview of Experimental Design and Example Data</a>
 <ul>
 <li class="chapter" data-level="" data-path="overview-of-experimental-design-and-example-data.html"><a href="overview-of-experimental-design-and-example-data.html#introduction-to-training-module-12"><i class="fa fa-check"></i>Introduction to Training Module</a></li>
@@ -345,7 +345,7 @@
 <li class="chapter" data-level="" data-path="advanced-multi-group-comparisons.html"><a href="advanced-multi-group-comparisons.html#ancova-example"><i class="fa fa-check"></i>ANCOVA Example</a></li>
 <li class="chapter" data-level="" data-path="advanced-multi-group-comparisons.html"><a href="advanced-multi-group-comparisons.html#concluding-remarks-17"><i class="fa fa-check"></i>Concluding Remarks</a></li>
 </ul></li>
-<li class="part"><span><b>Chapter 5 Machine Learning &amp; Artificial Intelligence</b></span></li>
+<li class="part"><span><b>Chapter 5 Machine Learning <br>&amp; Artificial Intelligence</b></span></li>
 <li class="chapter" data-level="" data-path="introduction-to-artificial-intelligence-machine-learning-and-predictive-modeling-for-environmental-health.html"><a href="introduction-to-artificial-intelligence-machine-learning-and-predictive-modeling-for-environmental-health.html"><i class="fa fa-check"></i>5.1 Introduction to Artificial Intelligence, Machine Learning, and Predictive Modeling for Environmental Health</a>
 <ul>
 <li class="chapter" data-level="" data-path="introduction-to-artificial-intelligence-machine-learning-and-predictive-modeling-for-environmental-health.html"><a href="introduction-to-artificial-intelligence-machine-learning-and-predictive-modeling-for-environmental-health.html#introduction-to-training-module-18"><i class="fa fa-check"></i>Introduction to Training Module</a></li>
@@ -400,7 +400,7 @@
 <li class="chapter" data-level="" data-path="unsupervised-machine-learning-part-2-additional-clustering-applications.html"><a href="unsupervised-machine-learning-part-2-additional-clustering-applications.html#variable-contributions"><i class="fa fa-check"></i>Variable Contributions</a></li>
 <li class="chapter" data-level="" data-path="unsupervised-machine-learning-part-2-additional-clustering-applications.html"><a href="unsupervised-machine-learning-part-2-additional-clustering-applications.html#concluding-remarks-22"><i class="fa fa-check"></i>Concluding Remarks</a></li>
 </ul></li>
-<li class="part"><span><b>Chapter 6 Applications in Toxicology &amp; Exposure Science</b></span></li>
+<li class="part"><span><b>Chapter 6 Applications in <br>Toxicology &amp; Exposure <br>Science</b></span></li>
 <li class="chapter" data-level="" data-path="descriptive-cohort-analyses.html"><a href="descriptive-cohort-analyses.html"><i class="fa fa-check"></i>6.1 Descriptive Cohort Analyses</a>
 <ul>
 <li class="chapter" data-level="" data-path="descriptive-cohort-analyses.html"><a href="descriptive-cohort-analyses.html#introduction-to-training-module-23"><i class="fa fa-check"></i>Introduction to Training Module</a></li>
@@ -463,7 +463,7 @@
 <li class="chapter" data-level="" data-path="toxicokinetic-modeling.html"><a href="toxicokinetic-modeling.html#reverse-tk-calculating-administered-equivalent-doses-for-toxcast-bioactive-concentrations"><i class="fa fa-check"></i>Reverse TK: Calculating Administered Equivalent Doses for ToxCast Bioactive Concentrations</a></li>
 <li class="chapter" data-level="" data-path="toxicokinetic-modeling.html"><a href="toxicokinetic-modeling.html#comparing-equivalent-doses-estimated-to-elicit-toxicity-hazard-to-external-exposure-estimates-exposure-for-chemical-prioritization-by-bioactivity-exposure-ratios-bers"><i class="fa fa-check"></i>Comparing Equivalent Doses Estimated to Elicit Toxicity (Hazard) to External Exposure Estimates (Exposure), for Chemical Prioritization by Bioactivity-Exposure Ratios (BERs)</a></li>
 </ul></li>
-<li class="part"><span><b>Chapter 7 Environmental Health Database Mining</b></span></li>
+<li class="part"><span><b>Chapter 7 Environmental<br> Health Database Mining</b></span></li>
 <li class="chapter" data-level="" data-path="comparative-toxicogenomics-database.html"><a href="comparative-toxicogenomics-database.html"><i class="fa fa-check"></i>7.1 Comparative Toxicogenomics Database</a>
 <ul>
 <li class="chapter" data-level="" data-path="comparative-toxicogenomics-database.html"><a href="comparative-toxicogenomics-database.html#introduction-to-training-module-30"><i class="fa fa-check"></i>Introduction to Training Module</a></li>