googlegenomics/bigquery-examples

Name: bigquery-examples

Owner: Google Genomics

Description: Advanced BigQuery examples on genomic data.

Created: 2014-04-11 16:23:01.0

Updated: 2017-11-18 15:49:41.0

Pushed: 2017-06-09 21:19:26.0

Homepage:

Size: 4696

Language: Python

GitHub Committers

UserMost Recent Commit# Commits
Mad Price Ball2014-06-17 18:02:05.04
Erich S. Huang2014-05-14 20:03:26.02
Craig Citro2014-09-14 08:26:51.01
Chris Roat2014-05-06 23:51:04.01
Nicole Deflaux2017-06-09 21:19:25.0206
Matt Bookman2015-02-14 00:25:29.01
Cassie Doll2014-09-25 17:01:07.012

Other Committers

UserEmailMost Recent Commit# Commits

README

bigquery-examples

The data stories and queries in this repository demonstrate working with genomic data via Google BigQuery. All examples are built upon public datasets.

Have other data stories you would like to see here? Have any data stories you would like to share? Have corrections to the biology covered in this material? Have query simplifications or speed improvements? Let us know by filing an issue or contacting us directly.

Getting Started

If you are new to BigQuery, start here instead: Analyze Variants Using BigQuery.

Otherwise, navigate through the tree of content in this repository. You will find queries, RMarkdown, rendered analyses, and provenance details.

Loading your own Variant Data into BigQuery

After trying these queries on public data, you can load your own variant data into BigQuery.

For other types of data, such as variant annotations, see Preparing Data for BigQuery and also BigQuery in Practice : Loading Data Sets That are Terabytes and Beyond for more detail.

The mailing list

The Google Genomics Discuss mailing list is a good way to sync up with other people who use googlegenomics including the core developers. You can subscribe by sending an email to google-genomics-discuss+subscribe@googlegroups.com or just post using the web forum page.


This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.