updates

docs/build/html/_sources/sections/Reference-Data.txt

@@ -27,7 +27,7 @@ Although additional details can be found at the Illumina_ webpage, we have uploa
 annotation information into the BigQuery table isb-cgc:platform_reference.methylation_annotation
 
 Each CpG locus is uniquely identified as described in this 
-`technical note <http://www.illumina.com/content/dam/illumina-marketing/documents/products/technotes/technote_cpg_loci_identification.pdf>_`
+`technical note <http://www.illumina.com/content/dam/illumina-marketing/documents/products/technotes/technote_cpg_loci_identification.pdf>`_
 and this unique identifier can be used to look up and cross-reference data between the TCGA DNA methylation data table
 and the platform annotation table.
 
@@ -49,7 +49,7 @@ Other Reference Data Sources
 ############################
 
 Google Genomics maintains a list of 
-`publicly available datasets <http://googlegenomics.readthedocs.org/en/latest/use_cases/discover_public_data/index.html>_`, 
+`publicly available datasets <http://googlegenomics.readthedocs.org/en/latest/use_cases/discover_public_data/index.html>`_, 
 including **Reference Genomes**, 
 the **Illumina Platinum Genomes**, information about the **Tute Genomics Annotation** table, *etc*.
 

docs/build/html/_sources/sections/TCGA-Data.txt

@@ -11,10 +11,11 @@ Storage (GCS_) and in BigQuery_.
 
 The data being hosted by the ISB-CGC was obtained from the two main TCGA data
 repositories:
-* **TCGA DCC**: this is the TCGA Data Coordinating Center which provides a `Data Portal <https://tcga-data.nci.nih.gov/tcga/>_` from which users may download open-access or controlled-access data.  This portal provides access to all TCGA data *except* for the low-level sequence data. 
+
+* **TCGA DCC**: this is the TCGA Data Coordinating Center which provides a `Data Portal <https://tcga-data.nci.nih.gov/tcga/>`_ from which users may download open-access or controlled-access data.  This portal provides access to all TCGA data *except* for the low-level sequence data. 
 * **CGHub**:  this is NCI's current secure data repository for all TCGA BAM and FASTQ sequence data files.
 
-The ISB-CGC platform is one of NCI's `Cancer Genomics Cloud Pilots <https://cbiit.nci.nih.gov/ncip/nci-cancer-genomics-cloud-pilots>_` 
+The ISB-CGC platform is one of NCI's `Cancer Genomics Cloud Pilots <https://cbiit.nci.nih.gov/ncip/nci-cancer-genomics-cloud-pilots>`_ 
 and our mission is to host the TCGA data in the cloud so that researchers around the world may work with the data without needing 
 to download and store the data at their own local institutions.
 
@@ -39,7 +40,7 @@ TCGA Data Levels
 Understanding Data Access
 #########################
 
-    * **Public Data**  Sometimes the word "public" is misinterpreted as meaning "open".  All of the TCGA data is *public* data, but some of it is *open*, meaning that it is accessible and available to *all* users; while some TCGA data is *controlled* and restricted to authorized users.
-    * **Open-Access Data**  Depending on how you categorize the data, *most* of the TCGA data is open-access data.  This includes all de-identified clinical and biospecimen data, as well as all Level-3 molecular data including gene expression data, DNA methylation data, DNA copy-number data, protein expression data, somatic mutation calls, etc. 
-    * **Controlled-Access Data**  All low-level sequence data (both DNA-seq and RNA-seq), the raw SNP array data (CEL files), germline mutation calls, and a small amount of other data are treated as *controlled* data and require that a user be properly authenticated and have dbGaP-authorization prior to access these data.
+* **Public Data**  Sometimes the word "public" is misinterpreted as meaning "open".  All of the TCGA data is *public* data, but some of it is *open*, meaning that it is accessible and available to *all* users; while some TCGA data is *controlled* and restricted to authorized users.
+* **Open-Access Data**  Depending on how you categorize the data, *most* of the TCGA data is open-access data.  This includes all de-identified clinical and biospecimen data, as well as all Level-3 molecular data including gene expression data, DNA methylation data, DNA copy-number data, protein expression data, somatic mutation calls, etc. 
+* **Controlled-Access Data**  All low-level sequence data (both DNA-seq and RNA-seq), the raw SNP array data (CEL files), germline mutation calls, and a small amount of other data are treated as *controlled* data and require that a user be properly authenticated and have dbGaP-authorization prior to access these data.
 

docs/build/html/_sources/sections/Web-UI.txt

@@ -6,6 +6,7 @@ Documentation for the ISB-CGC web app is available from within the web-app.  Aft
 click on the down-arrow next to your name in the upper-right corner and select "Help".
 
 .. toctree::
+
   webapp/releases
   webapp/User-Dashboard
   webapp/Cohorts

docs/build/html/_sources/sections/webapp/Cohorts.txt

@@ -36,7 +36,7 @@ Participant Filters List
 
     * Project
     * Study
-    * Vital Study
+    * Vital Status
     * Gender
     * Age At Diagnosis
     * Sample Type Code
@@ -118,29 +118,29 @@ Editing a Cohort
 
 **Details of cohort edit page**
 
-Menu
-* Add New Filters: Selecting this menu item make the filters panel appear. And filters selected will be additive to any
-filters that have already been selected. To return to the previous view, you much either save any selected filters, or
-choose to cancel adding any new filters.
-* Comments: Selecting “Comments” will cause the Comments panel to appear. Here anyone who can see this cohort can
-comment on it. Comments are shared with anyone who can view this cohort and ordered by newest on the bottom.
-* Make a Copy: Making a copy will create a copy of this cohort with the same list of samples and patients and make you
-the owner of the copy.
-* Share with Others: This behaves similarly to on the User Dashboard page. A dialogue box appears and the user is
-prompted to select users that are registered in the system to share the cohort with.
+Main Menu
+---------
+
+* Add New Filters: Selecting this menu item make the filters panel appear. And filters selected will be additive to any filters that have already been selected. To return to the previous view, you much either save any selected filters, or choose to cancel adding any new filters.
+* Comments: Selecting “Comments” will cause the Comments panel to appear. Here anyone who can see this cohort can comment on it. Comments are shared with anyone who can view this cohort and ordered by newest on the bottom.
+* Make a Copy: Making a copy will create a copy of this cohort with the same list of samples and patients and make you the owner of the copy.
+* Share with Others: This behaves similarly to on the User Dashboard page. A dialogue box appears and the user is prompted to select users that are registered in the system to share the cohort with.
 
 Selected Filters Panel
+----------------------
 
 This panel displays any filters that have been used on the cohort or any of its ancestors. These cannot be modified and
 any additional filters applied to this cohort will be appended to the list.
 
 Details Panel
+-------------
 
 This panel displays the number of samples and participant in this cohort. These vary because some participants may have
 provided multiple samples.
 This panel also displays “Your Permissions” which can be either owner or reader.
 
 Clinical Features Panel
+-----------------------
 
 This panel shows a list of treemaps that give a high level break of the samples for a handful of features:
 * Disease Code
@@ -153,7 +153,7 @@ This panel shows a list of treemaps that give a high level break of the samples
 By using the “Show More” button, you can see two more tree maps available.
 
 Data Availability Panel
-
+-----------------------
 This panel shows a parallel sets graph of available data for the selected samples in the cohort. The large headers over
 the vertical bars are data types. Each data type is broken up into their different platforms and “NA” for samples that
 do not have that data type. The bars that flow horizontally indicate the number of samples that have that data. By
@@ -177,6 +177,7 @@ contains the following information for each file:
 * File Path to the Cloud Storage Location
 
 Commenting
+----------
 Any user who owns or has had a cohort shared with them can comment on it. To open comments, use the menu button at the
 top right and select “Comments”. A sidebar will appear on the right side and any previously created comments will be
 shown.
@@ -185,7 +186,7 @@ On the bottom of the comments sidebar, you can create a new comment and save it.
 list of comments.
 
 Deleting a cohort
------------------
+=================
 
 From the dashboard:
 Select the cohorts that you wish to delete using the checkboxes next to the cohorts. When one or more are selected, the
@@ -194,8 +195,8 @@ delete button will be active and you can then proceed to deleting them.
 From within a cohort:
 If you are viewing a cohort you created, then you can delete the cohort from the top right menu option.
 
-Creating a Cohort From a visualization
---------------------------------------
+Creating a Cohort from a Visualization
+======================================
 
 To create a cohort from a visualization, you must be in plot selection mode. If you are in plot selection mode, the
 crosshairs icon in the top right corner of the plot panel should be blue. If it is not, click on it and it should turn
@@ -210,10 +211,11 @@ on this when you are ready to create a new cohort.
 Put in a name for you newly selected cohort and click the “Save” button.
 
 Copying a cohort
-----------------
+================
 
 Copying a cohort can only be done from the cohort details page of the cohort you are want to copy.
 
 When you are looking at the cohort you wish to copy, select the “Make A Copy” item from the top right menu.
 
 This will take you to your copy of the cohort.
+

docs/build/html/_sources/sections/webapp/General-Permissions.txt

@@ -8,9 +8,9 @@ visualizations will, by default, be private to the user who created them.  Users
 also share these components of their interactive analyses.  There are two levels of permissions:
 Owner and Reader:
 
-    * **Owner**: As owner of a cohort or visualization, you are able to edit and share your cohort.
-    * **Reader**:  If a cohort or visualization is shared with you, you have view-only access:
-        - You may be able to make configuration changes to plots in a visualizations, but you will not be able to save those changes;
-        - You are able to comment on a cohort or plot, and your comments will be shared with all other Readers;
-        - You may make a copy ("clone") of the cohort or visualization, after which you will be the owner and you will be able to make changes.
+* **Owner**: As owner of a cohort or visualization, you are able to edit and share your cohort.
+* **Reader**:  If a cohort or visualization is shared with you, you have view-only access:
+    - You may be able to make configuration changes to plots in a visualizations, but you will not be able to save those changes;
+    - You are able to comment on a cohort or plot, and your comments will be shared with all other Readers;
+    - You may make a copy ("clone") of the cohort or visualization, after which you will be the owner and you will be able to make changes.
 

docs/build/html/_sources/sections/webapp/SeqPeek.txt

@@ -14,8 +14,9 @@ menu. This will automatically take you to a SeqPeek page with no pre-selected se
 the Settings panel.
 
 In the Settings panel, there will be options to select in order to make a new plot.
-    * Gene selection: this is an autocompleting dropdown for valid gene symbols
-    * Cohorts: here you can select one or more cohorts for the visualization
+
+* Gene selection: this is an autocompleting dropdown for valid gene symbols
+* Cohorts: here you can select one or more cohorts for the visualization
 
 To add a cohort, select the “+ Cohort” option underneath the currently selected list of cohorts. This will take you to
 the cohorts listing panel where you can select a cohort from the list, or use the autocomplete textbox to search in
@@ -32,7 +33,7 @@ visualization and save. You will be notified after it saves correctly.
 Deleting a SeqPeek Visualization
 ################################
 
-    * **From User Dashboard**  Select the SeqPeek visualizations that you wish to delete using the checkboxes next to the visualization. When one or more are selected, the delete button will be active and you can then proceed to deleting them.
+* **From User Dashboard**  Select the SeqPeek visualizations that you wish to delete using the checkboxes next to the visualization. When one or more are selected, the delete button will be active and you can then proceed to deleting them.
 
-    * **From SeqPeek Visualization**  When viewing a SeqPeek visualization that you created, you may delete it using the top right menu option.
+* **From SeqPeek Visualization**  When viewing a SeqPeek visualization that you created, you may delete it using the top right menu option.
 

docs/build/html/_sources/sections/webapp/User-Dashboard.txt

@@ -50,9 +50,10 @@ Set Operations on Cohorts
 To activate the set operations button, you must have at least one cohort selected. Upon clicking 
 the “Set Operations” button, a dialogue box will appear. From here you may choose one of the following
 operations:
-    * Enter a name for the resulting cohort you will create
-    * Select a set operation
-    * Edit cohorts to be operated upon
+
+* Enter a name for the resulting cohort you will create
+* Select a set operation
+* Edit cohorts to be operated upon
 
 The intersect and union operations can take any number of cohorts and in any order.
 

docs/build/html/_sources/sections/webapp/Visualizations.txt

@@ -76,55 +76,46 @@ When you click on the edit icon next to the feature you would like to change (i.
 you will be taken to the feature selection panel.
 Here you must first specify the datatype of the feature you would like to plot. Each datatype requires a different set
 of parameters to narrow down the feature that can be used in the plot.
+
 * Clinical
     * Single autocomplete textbox. This input searches through the names of the all the clinical features available.
 * Gene Expression
-    * Gene Filter: filters down the plot-able features by a specific gene. This is an autocomplete search field for a
-    gene name.
+    * Gene Filter: filters down the plot-able features by a specific gene. This is an autocomplete search field for a gene name.
     * Platform Filter: filters down the plot-able features by platforms.
     * Center Filter: filters down the plot-able features by processing center.
     * Select Feature: provides the filtered down list of plot-able features to select from based on selected filters.
 * miRNA
-    * miRNA Name Filter: filters down the plot-able features by a specific miRNA. This is an autocomplete search field
-    for a miRNA name.
+    * miRNA Name Filter: filters down the plot-able features by a specific miRNA. This is an autocomplete search field for a miRNA name.
     * Platform Filter: filters down the plot-able features by platforms.
     * Value Filter: filters down the plot-able features by value.
     * Select Feature: provides the filtered down list of plot-able features to select from based on selected filters.
 * Methylation
-    * Gene Filter: filters down the plot-able features by a specific gene. This is an autocomplete search field for a
-    gene name.
-    * CpG Probe Filter: filters down the plot-able features by a specific CpG Probe. This is an autocomplete search
-    field for a particular probe.
+    * Gene Filter: filters down the plot-able features by a specific gene. This is an autocomplete search field for a gene name.
+    * CpG Probe Filter: filters down the plot-able features by a specific CpG Probe. This is an autocomplete search field for a particular probe.
     * Platform Filter: filters down the plot-able features by platforms.
     * Gene Region Filter: filters down the plot-able features by specific gene regions.
     * CpG Island region Filter: filters down the plot-able features by CpG Island region.
     * Select Feature: provides the filtered down list of plot-able features to select from based on selected filters.
 * Copy Number
-    * Gene Filter: filters down the plot-able features by a specific gene. This is an autocomplete search field for a
-    gene name.
+    * Gene Filter: filters down the plot-able features by a specific gene. This is an autocomplete search field for a gene name.
     * Value Filter: filters down the plot-able features by value
     * Select Feature: provides the filtered down list of plot-able features to select from based on selected filters.
 * Protein
-    * Gene Filter: filters down the plot-able features by a specific gene. This is an autocomplete search field for a
-    gene name.
-    * Protein Filter: filters down the plot-able features by protein. This is an autocomplete search field for a
-    protein name.
+    * Gene Filter: filters down the plot-able features by a specific gene. This is an autocomplete search field for a gene name.
+    * Protein Filter: filters down the plot-able features by protein. This is an autocomplete search field for a protein name.
     * Select Feature: provides the filtered down list of plot-able features to select from based on selected filters.
 * Mutation
-    * Gene Filter: filters down the plot-able features by a specific gene. This is an autocomplete search field for a
-    gene name.
+    * Gene Filter: filters down the plot-able features by a specific gene. This is an autocomplete search field for a gene name.
     * Value Filter: filters down the plot-able features by mutation value.
-
-Select Feature: provides the filtered down list of plot-able features to select from based on selected filters.
-* Swap Values: This button allows you to instantly swap the features on the X and Y Axes without having to re-select
-each feature individually.
-* Color By Cohort: This checkbox will override any feature that is in the Color By Feature. It will use the cohorts
-provided as the legend and Color By Feature.
+* Select Feature: provides the filtered list of plot-able features to select from based on selected filters.
+* Swap Values: This button allows you to instantly swap the features on the X and Y Axes without having to re-select each feature individually.
+* Color By Cohort: This checkbox will override any feature that is in the Color By Feature. It will use the cohorts provided as the legend and Color By Feature.
 * Cohorts: This is where you can select one or more cohorts to plot at one time.
 
 To add a cohort, select the “+ Cohort” option underneath the currently selected list of cohorts. This will take you to
 the cohorts listing panel where you can select a cohort from the list, or use the autocomplete textbox to search in
 their list of cohorts.
+
 When all the settings have been set, you can click “Update Plot” to regenerate the plot with the new settings.
 
 Pairwise Statistical Test