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docs/no_toc/01-intro.md

@@ -3,7 +3,7 @@
 
 # Introduction
 
-<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_gd422c5de97_0_0.png" title="Title image: Choosing Genomics Tools Written by: Candace Savonen. Part of the ITN (ITCR training Network) and created through the Johns Hopkins Data Science Lab" alt="Title image: Choosing Genomics Tools Written by: Candace Savonen. Part of the ITN (ITCR training Network) and created through the Johns Hopkins Data Science Lab" width="100%" />
+<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_gd422c5de97_0_0.png" alt="Title image: Choosing Genomics Tools Written by: Candace Savonen. Part of the ITN (ITCR training Network) and created through the Johns Hopkins Data Science Lab" width="100%" />
 
 This is a *living* course meaning it is constantly changing and being updated. The goal for this course is to be a "wikipedia" of omic data.
 If you'd like to contribute, [you can file a pull request on GitHub](https://github.com/fhdsl/Choosing_Genomics_Tools) if you are comfortable with that sort of thing or email `[email protected]` to ask how to get started.
@@ -18,11 +18,11 @@ _This course is written for individuals who:_
 - Want a basic overview of genomic data types.
 - Want to find resources for processing and interpreting genomics data.
 
-<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g116525eff64_0_96.png" title="For individuals who: Have genomic data and don’t know what to do with it. Want a basic overview of their genomic data type. Want to find resources for processing and interpreting genomics data" alt="For individuals who: Have genomic data and don’t know what to do with it. Want a basic overview of their genomic data type. Want to find resources for processing and interpreting genomics data" width="100%" />
+<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g116525eff64_0_96.png" alt="For individuals who: Have genomic data and don’t know what to do with it. Want a basic overview of their genomic data type. Want to find resources for processing and interpreting genomics data" width="100%" />
 
 ## Topics covered:
 
-<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g11db7c97851_0_143.png" title=" " alt=" " width="100%" />
+<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g11db7c97851_0_143.png" alt=" " width="100%" />
 
 ## Motivation
 
@@ -33,17 +33,17 @@ Often students and researchers need to utilize genomic data to reach the next st
 
 Often researchers receive their genomic data processed from another lab or institution, and although they are excited to gain insights from it to inform the next steps of their research, they may not have a practical understanding of how the data they have received came to be or what needs to be done with it.
 
-<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g1221ea485b7_0_0.png" title="This researcher is very excited because they’ve received their genomic data and are ready to gain insights from it to inform the next steps of their research. An email sent to them says ‘your data are ready’" alt="This researcher is very excited because they’ve received their genomic data and are ready to gain insights from it to inform the next steps of their research. An email sent to them says ‘your data are ready’" width="100%" />
+<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g1221ea485b7_0_0.png" alt="This researcher is very excited because they’ve received their genomic data and are ready to gain insights from it to inform the next steps of their research. An email sent to them says ‘your data are ready’" width="100%" />
 
 As an example, data file formats may not have been covered in their training, and the data they received seems unintelligible and not as straightforward as they hoped.
 
-<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g1221ea485b7_0_13.png" title="The researcher may attempt to open their newly received genomic data and be completely perplexed by the file formats or what these data even represent. The researcher says ‘What is this and what do I do with it’" alt="The researcher may attempt to open their newly received genomic data and be completely perplexed by the file formats or what these data even represent. The researcher says ‘What is this and what do I do with it’" width="100%" />
+<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g1221ea485b7_0_13.png" alt="The researcher may attempt to open their newly received genomic data and be completely perplexed by the file formats or what these data even represent. The researcher says ‘What is this and what do I do with it’" width="100%" />
 
 This course attempts to give this researcher the basic bearings and resources regarding their data, in hopes that they will be equipped and informed about how to obtain the insights for their researcher they originally aimed to find.
 
 ## Curriculum  
 
-<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_gd422c5de97_0_10.png" title="Overall Course Learning Objectives. This course will demonstrate how too: Understand the overall workflow associated with processing their genomic data  Be aware of caveats based on their specific type of data. Find tutorials to help them process their genomic data. Choose tools for processing their genomic data. Choose tools for interpreting their genomic data " alt="Overall Course Learning Objectives. This course will demonstrate how too: Understand the overall workflow associated with processing their genomic data  Be aware of caveats based on their specific type of data. Find tutorials to help them process their genomic data. Choose tools for processing their genomic data. Choose tools for interpreting their genomic data " width="100%" />
+<img src="resources/images/01-intro_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_gd422c5de97_0_10.png" alt="Overall Course Learning Objectives. This course will demonstrate how too: Understand the overall workflow associated with processing their genomic data  Be aware of caveats based on their specific type of data. Find tutorials to help them process their genomic data. Choose tools for processing their genomic data. Choose tools for interpreting their genomic data " width="100%" />
 
 **Goal of this course:**  
 Equip learners with tutorials and resources so they can understand and interpret their genomic data in a way that helps them meet their goals and handle the data properly.

docs/no_toc/02-genomics_overview.md

@@ -4,7 +4,7 @@
 
 ## Learning Objectives
 
-<img src="resources/images/02-genomics_overview_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_gd422c5de97_0_16.png" title="Learning objectives This chapter will demonstrate how to: Understand what will be covered in this course. Find information about your particular file format" alt="Learning objectives This chapter will demonstrate how to: Understand what will be covered in this course. Find information about your particular file format" width="100%" />
+<img src="resources/images/02-genomics_overview_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_gd422c5de97_0_16.png" alt="Learning objectives This chapter will demonstrate how to: Understand what will be covered in this course. Find information about your particular file format" width="100%" />
 
 In this chapter we are going to cover sequencing and microarray workflows at a very general high level overview to give you a first orientation. As we dive into specific data types and experiments, we will get into more specifics.
 Here we will cover the most common file formats. If you have a file format you are dealing with that you don't see listed here, it may be specific to your data type and we will discuss that more in that data type's respective chapter. We still suggest you go through this chapter to give you a basic understanding of commonalities of all genomic data types and workflows
@@ -13,7 +13,7 @@ Here we will cover the most common file formats. If you have a file format you a
 
 In the most general sense, all genomics data when originally collected is raw, it needs to undergo processing to be normalized and ready to use. Then normalized data is generally summarized in a way that is ready for it to be further consumed. Lastly, this summarized data is what can be used to make inferences and create plots and results tables.
 
-<img src="resources/images/02-genomics_overview_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12890ae15d7_0_20.png" title="In the most general sense, all genomics data when originally collected is raw, it needs to undergo processing to be normalized and ready to use. Then normalized data is generally summarized in a way that is ready for it to be further consumed. Lastly this summarized data is what can be used to make inferences and create plots and results tables. " alt="In the most general sense, all genomics data when originally collected is raw, it needs to undergo processing to be normalized and ready to use. Then normalized data is generally summarized in a way that is ready for it to be further consumed. Lastly this summarized data is what can be used to make inferences and create plots and results tables. " width="100%" />
+<img src="resources/images/02-genomics_overview_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12890ae15d7_0_20.png" alt="In the most general sense, all genomics data when originally collected is raw, it needs to undergo processing to be normalized and ready to use. Then normalized data is generally summarized in a way that is ready for it to be further consumed. Lastly this summarized data is what can be used to make inferences and create plots and results tables. " width="100%" />
 
 ### Basic file formats
 

docs/no_toc/03-whats-metadata.md

@@ -5,7 +5,7 @@
 
 ## Learning Objectives
 
-<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12709027cba_1_70.png" title="Learning objectives This chapter will demonstrate how to: Understand what metadata are and why they are so critical. Learn the basics of creating crystal clear, readable metadata" alt="Learning objectives This chapter will demonstrate how to: Understand what metadata are and why they are so critical. Learn the basics of creating crystal clear, readable metadata" width="100%" />
+<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12709027cba_1_70.png" alt="Learning objectives This chapter will demonstrate how to: Understand what metadata are and why they are so critical. Learn the basics of creating crystal clear, readable metadata" width="100%" />
 
 ## What are metadata?
 
@@ -15,11 +15,11 @@ Metadata are critically important descriptive information about your data.
 
 Metadata describe how your data came to be, what organism or patient the data are from and include any and every relevant piece of information about the samples in your data set.
 
-<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12709027cba_1_12.png" title="Question: What are metadata? Answer: Anything and everything that should be known about your samples! Samples labeled A-H are in test tubes. A corresponding spreadsheet has metadata such as mouse id, processing date, treatment and etc. The researcher says ‘I know everything I need to know about these samples from their metadata!’" alt="Question: What are metadata? Answer: Anything and everything that should be known about your samples! Samples labeled A-H are in test tubes. A corresponding spreadsheet has metadata such as mouse id, processing date, treatment and etc. The researcher says ‘I know everything I need to know about these samples from their metadata!’" width="100%" />
+<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12709027cba_1_12.png" alt="Question: What are metadata? Answer: Anything and everything that should be known about your samples! Samples labeled A-H are in test tubes. A corresponding spreadsheet has metadata such as mouse id, processing date, treatment and etc. The researcher says ‘I know everything I need to know about these samples from their metadata!’" width="100%" />
 
 Metadata includes but isn't limited to, the following example categories:
 
-<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12709027cba_1_45.png" title="Examples of metadata categories: Patient/organism of origin, Patient/organism information including: Demographics, Disease state, Treatment state, Time point (if applicable). Metadata also includes: Processing information like: Batch information and Processing details (for example: Isolation methods: Poly-A vs Ribo-minus) Metadata is Anything that should be known about the samples and their handling!" alt="Examples of metadata categories: Patient/organism of origin, Patient/organism information including: Demographics, Disease state, Treatment state, Time point (if applicable). Metadata also includes: Processing information like: Batch information and Processing details (for example: Isolation methods: Poly-A vs Ribo-minus) Metadata is Anything that should be known about the samples and their handling!" width="100%" />
+<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12709027cba_1_45.png" alt="Examples of metadata categories: Patient/organism of origin, Patient/organism information including: Demographics, Disease state, Treatment state, Time point (if applicable). Metadata also includes: Processing information like: Batch information and Processing details (for example: Isolation methods: Poly-A vs Ribo-minus) Metadata is Anything that should be known about the samples and their handling!" width="100%" />
 
 <div class = "warning">
 At this time it's important to note that if you work with human data or samples, your metadata will likely contain personal identifiable information (PII) and protected health information (PHI). It's critical that you protect this information! For more details on this, we encourage you to see our [course about data management](https://jhudatascience.org/Ethical_Data_Handling_for_Cancer_Research/data-privacy.html).
@@ -74,13 +74,13 @@ Toward these two goals, [this excellent article](https://www.tandfonline.com/doi
 
 <div class = "warning">
 Note that it is very dangerous to open gene data with Excel. According to @Ziemann2016, approximately one-fifth of papers with Excel gene lists have errors. This happens because Excel wants to interpret everything as a date. We strongly caution against opening (and saving afterward) gene data in Excel.
-<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g13a7f78e577_0_0.png" title="‘Approximately one-fifth of papers with supplementary Excel gene lists contain erroneous gene name conversions’ Ziemann, Eren, El-Osta, 2016. On the left, a meme that shows Excel asking ‘is this a date?’ in response to seeing ‘any data at all’. " alt="‘Approximately one-fifth of papers with supplementary Excel gene lists contain erroneous gene name conversions’ Ziemann, Eren, El-Osta, 2016. On the left, a meme that shows Excel asking ‘is this a date?’ in response to seeing ‘any data at all’. " width="100%" />
+<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g13a7f78e577_0_0.png" alt="‘Approximately one-fifth of papers with supplementary Excel gene lists contain erroneous gene name conversions’ Ziemann, Eren, El-Osta, 2016. On the left, a meme that shows Excel asking ‘is this a date?’ in response to seeing ‘any data at all’. " width="100%" />
 </div>
 
 ### To recap:
 
-<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12709027cba_1_52.png" title="Rules for creating metadata (from Broman &amp; Woo, 2017) Be Consistent. Choose good names for things. Write Dates as YYYY-MM-DD.No Empty Cells. Put Just One Thing in a Cell. Make it a Rectangle" alt="Rules for creating metadata (from Broman &amp; Woo, 2017) Be Consistent. Choose good names for things. Write Dates as YYYY-MM-DD.No Empty Cells. Put Just One Thing in a Cell. Make it a Rectangle" width="100%" />
+<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12709027cba_1_52.png" alt="Rules for creating metadata (from Broman &amp; Woo, 2017) Be Consistent. Choose good names for things. Write Dates as YYYY-MM-DD.No Empty Cells. Put Just One Thing in a Cell. Make it a Rectangle" width="100%" />
 
-<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12890ae15d7_0_1.png" title="Rules for creating metadata continued  (from Broman &amp; Woo, 2017). Create a Data Dictionary. No Calculations in the Raw Data Files. Do Not Use Font Color or Highlighting as Data. Make Backups. Use Data Validation to Avoid Errors" alt="Rules for creating metadata continued  (from Broman &amp; Woo, 2017). Create a Data Dictionary. No Calculations in the Raw Data Files. Do Not Use Font Color or Highlighting as Data. Make Backups. Use Data Validation to Avoid Errors" width="100%" />
+<img src="resources/images/03-whats-metadata_files/figure-html//1YwxXy2rnUgbx_7B7ENH9wpDX-j6JpJz6lGVzOkjo0qY_g12890ae15d7_0_1.png" alt="Rules for creating metadata continued  (from Broman &amp; Woo, 2017). Create a Data Dictionary. No Calculations in the Raw Data Files. Do Not Use Font Color or Highlighting as Data. Make Backups. Use Data Validation to Avoid Errors" width="100%" />
 
 If you are not the person who has the information needed to create metadata, or you believe that another individual already has this information, make sure you get ahold of the metadata that correspond to your data. It will be critical for you to have to do any sort of meaningful analysis!