You can access the databases and tables within the Base module using snowSQL command-line interface. This is useful for external collaborators who do not have access to ICA core functionalities. In this tutorial we will describe how to obtain the token and use it for accessing the Base module. This tutorial does not cover how to install and configure snowSQL.

Obtaining OAuth token and URL

Once the Base module has been enabled within a project, the following details are shown in Projects > your_project > Project Settings > Details.

After clicking the button Create OAuth access token, the pop-up authenticator is displayed.

After clicking the button Generate snowSQL command the pop-up authenticator presents the snowSQL command.

Copy the snowSQL command and run it in the console to log in.

You can also get the OAuth access token via API by providing <PROJECT ID> and <YOUR KEY>.

Example:

API Call:

Response

Template snowSQL:

Now you can perform a variety of tasks such as:

1. Querying Data: execute SQL queries against tables, views, and other database objects to retrieve data from the Snowflake data warehouse.

2. Creating and Managing Database Objects: create tables, views, stored procedures, functions, and other database objects in Snowflake. you can also modify and delete these objects as needed.

3. Loading Data: load data into Snowflake from various sources such as local files, AWS S3, Azure Blob Storage, or Google Cloud Storage.

Overall, snowSQL CLI provides a powerful and flexible interface to work with Snowflake, allowing external users to manage data warehouse and perform a variety of tasks efficiently and effectively without access to the ICA core.

Example Queries:

Show all tables in the database:

Create a new table:

List records in a table:

Load data from a file: To load data from a file, you can start by create a staging area in the internal storage using the following commend:

You can then upload the local file to the internal storage using the following command:

You can check if the file was uploaded properly using LIST command:

Finally, Load data by using COPY TO command. The command assumes the data.tsv is a tab delimited file. You can easily modify the following command to import JSON file setting TYPE=JSON.

Load data from a string: If you have data as JSON string, you can import the data into the tables using following commands.

Load data into specific columns: If you want to load sample_name into the table, you can remove the "count" from the column and the value list as below:

List the views of the database to which you are connected. As shared database and catalogue views are created within the project database, they will be listed. However, it does not show views which are granted via another database, role or from bundles.

Show grants, both directly on the tables and views and grants to roles which in turn have grants on tables and views.

You can access the databases and tables within the Base module using Python from your local machine. Once retrieved as e.g. pandas object, the data can be processed further. In this tutorial, we will describe how you could create a Python script which will retrieve the data and visualize it using Dash framework. The script will contain the following parts:

• Importing dependencies and variables.

• Function to fetch the data from Base table.

• Creating and running the Dash app.

Importing dependencies and variables

This part of the code imports the dependencies which have to be installed on your machine (possibly with pip). Furthermore, it imports the variables API_KEY and PROJECT_ID from the file named config.

Function to fetch the data from Base table

We will be creating a function called fetch_data to obtain the data from Base table. It can be broken into several logically separated parts:

• Retrieving the token to access the Base table together with other variables using API.

• Establishing the connection using the token.

• SQL query itself. In this particular example, we are extracting values from two tables Demo_Ingesting_Metrics and BB_PROJECT_PIPELINE_EXECUTIONS_DETAIL. The table Demo_Ingesting_Metrics contains various metrics from DRAGEN analyses (e.g. the number of bases with quality at least 30 Q30_BASES) and metadata in the column ica which needs to be flattened to access the value

Here is the corresponding snippet:

Creating and running the Dash app

Once the data is fetched, it is visualized in an app. In this particular example, a scatter plot is presented with END_DATE as x axis and the choice of the customer from the dropdown as y axis.

Now we can create a single Python script called dashboard.py by concatenating the snippets and running it. The dashboard will be accessible in the browser on your machine.

Base is a genomics data aggregation and knowledge management solution suite. It is a secure and scalable integrated genomics data analysis solution which provides information management and knowledge mining. Refer to the Base documentation for more details.

This tutorial provides an example for exercising the basic operations used with Base, including how to create a table, load the table with data, and query the table.

Prerequisites

• An ICA project with access to Base

  • If you don't already have a project, please follow the instructions in the to create a project.

• File to import

  • A tab delimited gene expression file (). Example format:

Create table

Tables are components of databases that store data in a 2-dimensional format of columns and rows. Each row represents a new data record in the table; each column represents a field in the record. On ICA, you can use Base to create custom tables to fit your data. A schema definition defines the fields in a table. On ICA you can create a schema definition from scratch, or from a template. In this activity, you will create a table for RNAseq count data, by creating a schema definition from scratch.

1. Go to the Projects > your_project > Base > Tables and enable Base by clicking on the Enable button.

1. Select Add Table > New Table.

2. Create your table

   1. To create your table from scratch, select Empty Table from the Create table from dropdown.

Upload data to load into your table

1. Upload sampleX.final.count.tsv file with the final count.

   1. Select Data tab (1) from the left menu.

   2. Click on the grey box (2) to choose the file to upload or drag and drop the sampleX.final.count.tsv into the grey box

Create a schedule to load data into your table

Data can be loaded into tables manually or automatically. To load data automatically, you can set up a schedule. The schedule specifies which files’ data should be automatically loaded into a table, when those files are uploaded to ICA or created by an analyses on ICA. Active schedules will check for new files every 24 hours.

In this exercise, you will create a schedule to automatically load RNA transcript counts from .final.count.tsv files into the table you created above.

1. Go to Projects > your_project > Base > Schedule and click the + Add New button.

1. Select the option to load the contents from files into a table.

1. Create your schedule.

   1. Name your schedule LoadFeatureCounts

   2. Choose Project as the source of data for your table.

1. Highlight your schedule. Click the Run button to run your schedule now.

• It will take a short time to prepare and load data into your table.

  1. Check the status of your job on your Projects > your_project > Activity page.

  2. Click the BASE JOBS tab to view the status of scheduled Base jobs.

1. Check the data in the table.

   1. Go back to your Projects > your_project > Base > Tables page.

   2. Double-click your table to view its details.

Query a table

To request data or information from a Base table, you can run an SQL query. You can create and run new queries or saved queries.

In this activity, we will create and run a new SQL query to find out how many records (RNA transcripts) in your table have counts greater than 100.

1. Go to your Projects > your_project > Base > Query page.

1. Paste the above query into the NEW QUERY text box

2. Click the Run Query button to run your query

3. View your query results.

Export table data

Find the table you want to export on the "Tables" page under BASE. Go to the table details page by clicking twice on the table you want to export.

Click on the Export As File icon and complete the required fields

1. Name: Name of the exported file

2. Data Format: A table can be exported in CSV and JSON format. The exported files can be compressed using GZIP, BZ2, DEFLATE or RAW_DEFLATE.

   • CSV Format: In addition to Comma, the file can be Tab, Pipe or Custom character delimited.

1. Export to single/multiple files: This option allows the export of a table as a single (large) file or multiple (smaller) files. If "Export to multiple files" is selected, a user can provide "Maximum file size (in bytes)" for exported files. The default value is 16,000,000 bytes but can be increased to accommodate larger files. The maximum file size supported is 5 GB.