Large amounts of sequencing data have been generated by NGS technologies in the maize community. However, not all of them have been extensively studied. We believe that published data can be repurposed to answer different questions. Public data curated by domain experts (better to be the data generators) is critical for their re-usage. Past research experience has taught us that data tweaking and hammering is tedious. The smart maize researchers should spend their precious time on developing and testing hypothesis rather than processing, formatting, and reformatting theirs or others’ raw data.

With this platform, we are trying to bring published data, data producers, and version controlled pipelines together. But we are not intend to replace current database systems. Neither do we want to host or quality check the published data.

The major purposes of this platform are:

  1. Pointing the existing data sets.
  2. Providing peer curated and reproducible data processing pipelines.
  3. Learning, discussing, and improving data analyzing practices.

How does it work?

This platform, including the source codes of this website, can be open accessed via ZeaBigData hosted on github. To minimize the maintenance load, users from the community can directly access the site, write a post (using a very simple markdown language, see instruction) or make a comment. The posts or edits will appear on the website soon.

We are proudly supported by maize researchers from:

We have got computational support from XSEDE:

  • PI: Jinliang Yang, University of Nebraska, Lincoln
  • Request: Recount RNA-seq reads on AGPv4 genome to facilitate genetic studies for maize community
  • Request Number: BIR170001
  • End Date: 2018-02-05

What can you contribute to?

You can contribute by following ways:

  1. Serve as a volunteer for site maintenance.
  2. Send links to raw data or processed versions.
  3. Write technic posts to summarize data statistics.
  4. Write pipelines posts to discuss analyses pipelines.
  5. Edit or review posts.
  6. Correct grammars, typos, and errors.
  7. Check data and/or test pipelines.
  8. Use the data for your research.

How to contribute?

Follow this post.

ZeaBigData Hackathon 2017

We will have the 1st ZeaBigData Hackathon at UC Davis, hosted by Ross-Ibarra Lab. See Schedule.