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About Pretzel

A Loopback/Ember/D3 framework to display and interactively navigate complex datasets.

Currently (2020-) funded and developed by Agriculture Victoria, Department of Jobs, Precincts and Regions (DJPR), Victoria, Australia.

Previously (2016-2020) funded by the Grains Research Development Corporation (GRDC) and co-developed by Agriculture Victoria and CSIRO, Canberra, Australia.

Table of Contents

Features

Axis re-ordering

Axis flipping

Zoom

Axis stacking

NOTE: References for the genetic maps shown in the alignments on this page are available at the bottom of this page.

Quick start (using docker)

For a quick start without installing any of the dependencies you will need docker engine running on your system.

Docker on linux

mkdir -p ~/mongodata \
 && docker run --name mongo --detach --volume ~/mongodata:/data/db --net=host mongo \
 && until $(curl --silent --output /dev/null localhost:27017 || \
    [ $(docker inspect -f '{{.State.Running}}' mongo) = "false" ]); do printf '.'; sleep 1; done \
 && docker run --name pretzel --detach --net=host plantinformaticscollaboration/pretzel:stable  \
 && until $(curl --silent --output /dev/null localhost:3000 || \
    [ $(docker inspect -f '{{.State.Running}}' pretzel) = "false" ] ); do printf '.'; sleep 1; done \
 && docker logs pretzel

Docker on windows

md mongodata
docker run --name mongo --detach --publish 27017:27017 --volume mongodata:/data/db mongo
docker run --name pretzel -e "DB_HOST=host.docker.internal" --publish 3000:3000 plantinformaticscollaboration/pretzel:stable

Checking things are running

If everything has worked so far, you should be able to open http://localhost:3000 in a browser and see a landing page. You can create a user by signing up, then logging in with these details (by default, the user is created immediately without any extra verification).

Loading data

Once your pretzel instance is running you may want to populate it with some data.

Using pretzel web interface

You can start by downloading and decompressing datasets (3 genetic maps) we have made available here. In your instance of Pretzel, navigate to the Upload tab on the left panel, select JSON and browse to the location where you extracted the content of the downloaded file. Select and submit each of the three JSON files in turn. Once submitted, the maps should be visible in the Explorer tab.

Using command line

To upload multiple genomes along with feature definitions and aliases defining syntenic relationships between the features, you can

  1. Download the pre-computed data,
wget https://github.com/plantinformatics/pretzel-input-generator/releases/download/v1.0/pretzel-genomes-features-aliases-JSON.tar.gz
  1. Unpack
tar xzvf pretzel-genomes-features-aliases-JSON.tar.gz
  1. Follow the upload instructions

Setting up your own instance (without docker)

Note for installation on MS Windows

The easiest way to set up a local instance on Windows is to first install the Windows Subsystem for Linux, as documented

Once the WSL is installed and you are within a Linux subsystem -powered command-line shell, all steps below may be followed as specified.

Dependencies

Database

Install MongoDB using your distribution's package manager; for example, in Ubuntu:

sudo apt-get install mongodb

Node.js, NPM and Bower

NPM is the package manager for Node.js and allows easy installation of the tools required by this project. You can install Node.js and NPM using your native distribution package manager; for example, in Ubuntu:

sudo apt-get install nodejs npm

Bower is a front-end package manager and depends on Node.js and NPM. Install it globally:

sudo npm install bower -g

Mac iOS install of Node and Mongodb

Prerequisites : XCode : https://itunes.apple.com/us/app/xcode/id497799835 Homebrew : https://brew.sh

brew install node
brew install mongodb
npm install bower -g

The default location of the mongo database is /data/db; to place the data in e.g. your home directory :

cd ~/Applications/
mkdir Pretzel
export MONGO_DATA_DB=$HOME/Applications/Pretzel/data_db
mkdir $MONGO_DATA_DB
mongod --dbpath $MONGO_DATA_DB

Cloning repository and set-up

Clone the Github repository:

git clone https://github.com/plantinformatics/pretzel.git

Default build

To setup and build the frontend and backend, and run the backend :

cd pretzel
npm run go

Step-by-step build procedure

This sections describes steps of default build individually, as an alternative to npm run go.

Install Ember dependencies

To install the various plug-ins and add-ons required by the project, use NPM and Bower (for the Ember-specific dependencies):

# cd into Ember directory
cd pretzel/frontend
# Install Ember dependencies
npm install
bower install
# cd into backend directory
cd ../backend
# Install dependencies
npm install

Note that npm install in backend/ and frontend/ will install the Express.js and Ember.js dependencies, including Express.js and Ember.js themselves, into those directories. For example, ember is in frontend/node_modules/ember-cli/bin/.

Compile Ember app

The app is served by the Loopback backend and needs to be pre-compiled:

cd ../frontend
node_modules/ember-cli/bin/ember build --environment production
cd ..

Set up soft links

The Loopback backend expects the compiled client in its client/ sub-directory. You can simply create a soft link:

ln -s ../frontend/dist backend/client
ln -s ../../../../backend/common/utilities/interval-overlap.js frontend/app/utils/draw/.

Running

Starting the app

You should now be able to start the Loopback backend:

cd backend
EMAIL_VERIFY=NONE AUTH=ALL node server/server.js

Note that this runs the app without any authentication or security and is only suitable for local installs or internal networks. See below for details on setting up user accounts and authentication.

Checking things are running

If everything has worked so far, you should be able to open http://localhost:3000 in a browser and see a landing page. If you started the backend with the above command, you can create a user by signing up, then logging in with these details (with EMAIL_VERIFY=NONE, the user is created immediately without any extra verification).

Starting for development

To start the app for code development with live reloads on changes

  1. Ensure the Ember-CLI tool is installed globally
npm install -g ember-cli
  1. Run the backend independently, with an assigned port
EMAIL_VERIFY=NONE AUTH=ALL API_PORT_EXT=5000 npm run run:backend
  1. Run the frontend independently, using Ember CLI
cd frontend && ember serve

Adding user verification

To use with Postfix on Ubuntu 18.04, run apt install mailutils and follow the wizard defaults (for 'Internet Site').

Test postfix by sending yourself an email, e.g. echo "Test message" | mail [email protected] - the message may and up in your SPAM folder.

If it works, specify required environmental variables and run the app as per the dummy example below.

API_HOST=your_IP_or_FQDN EMAIL_VERIFY=ADMIN [email protected] [email protected] EMAIL_HOST=localhost EMAIL_PORT=25 AUTH=ALL node server/server.js

Make sure you modify:

  • API_HOST - should be set either to host IP number or its fully qualified domain name (FQDN)
  • EMAIL_ADMIN - email address of the person who will authorise the registration of new users

Alternatively, if you have access to your organisation's or hosting provider's SMTP server, then rather than using Postfix, update EMAIL_HOST and EMAIL_PORT to appropriate values. You may also have to supply your credential by specifying EMAIL_USER and EMAIL_PASS.

Inserting data

There are example datasets in the pretzel-data repository with simple dummy data. You can get the data with

git clone https://github.com/plantinformatics/pretzel-data

and upload these files by navigating to the Upload tab on the left panel, selecting JSON and browsing to pretzel-data/ to select a map. Once submitted, the maps should be visible in the Explorer tab. The file myDataset.json defines the reference myGenome, and hence should be uploaded before the files which refer to that reference : myAnnotation.json myMarkers.json myMarkers2.json mySample.json aliases.json

Loading data via the command line

An alternative to the Upload tab is to use the command-line, e.g. for larger files :

export APIHOST=http://localhost:3000
source ~/Applications/Pretzel/pretzel/resources/tools/functions_prod.bash

Logging in to the web application authorises a token, which is required by the API.

While logged into Pretzel via the browser, use the Web Inspector to get the authentication token :

From Ctrl-click : Inspect ...
>> Application : Storage : Cookies : http://localhost:3000 :  Name : ember_simple_auth-session

Copy/Paste the Value into a url decoder such as e.g. https://urldecode.org which will display the decoded parameters as e.g. :

{"authenticated":{"authenticator":"authenticator:pretzel-local","token":"0uOnWyy08OGcDJbC9eRx5Ki73z2OYkqvrZqQTJmoAklmysU5CxtrYmrXUpcX8MOe","clientId":"5ba9c0870612bf19a6afed01"}}

Copy/paste the token value and set it in the command-line environment using :

setToken  "authentication-token-goes-here"

Then in the same shell you can use the API to upload dataset files :

uploadData ~/Applications/Pretzel/pretzel-data/myMap.json
uploadDataList myDataset.json myAnnotation.json myMarkers.json myMarkers2.json mySample.json
URL=$URL_A uploadData aliases.json 

Database Indexes

Refer to 'Database configuration' in doc/notes/database-configuration.md for indexes added to the Feature and Alias database collections which are required for reasonable performance as datasets grown beyond 1k documents.

Public genetic map references

Wang, S., Wong, D., Forrest, K., Allen, A., Chao, S., Huang, B. E., Maccaferri, M., Salvi, S., Milner, S. G., Cattivelli, L., Mastrangelo, A. M., Whan, A., Stephen, S., Barker, G., Wieseke, R., Plieske, J., International Wheat Genome Sequencing Consortium, Lillemo, M., Mather, D., Appels, R., Dolferus, R., Brown-Guedira, G., Korol, A., Akhunova, A. R., Feuillet, C., Salse, J., Morgante, M., Pozniak, C., Luo, M.-C., Dvorak, J., Morell, M., Dubcovsky, J., Ganal, M., Tuberosa, R., Lawley, C., Mikoulitch, I., Cavanagh, C., Edwards, K. J., Hayden, M. and Akhunov, E. (2014), Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array. Plant Biotechnol J, 12: 787–796. doi:10.1111/pbi.12183

Gardner, K. A., Wittern, L. M. and Mackay, I. J. (2016), A highly recombined, high-density, eight-founder wheat MAGIC map reveals extensive segregation distortion and genomic locations of introgression segments. Plant Biotechnol J, 14: 1406–1417. doi:10.1111/pbi.12504

Wen, W., He, Z., Gao, F., Liu, J., Jin, H., Zhai, S., Xia, X. (2017). A High-Density Consensus Map of Common Wheat Integrating Four Mapping Populations Scanned by the 90K SNP Array. Frontiers in Plant Science, 8, 1389. http://doi.org/10.3389/fpls.2017.01389

Software / Tools Acknowledgments

Images / Media

bucketFill.png from : Icons made by Freepik from www.flaticon.com


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