ENCODE Data Coordination at UCSC Kate Rosenbloom ENCODE DCC Technical Project Manager UCSC Genome Bioinformatics Group September 2010 Genome Browser SAB Review

ENCODE in a nutshell: Y3Q3 2 species (human, mouse) 3 years of production phase (2 years left) 17 grants, 27 labs 20 experiment types 27 browser tracks 140 cell & tissue types 1559 datasets

Topics: 1.DCC role in ENCODE 2.Progress since last SAB review 3.Challenges 4.Browser impact

DCC role in ENCODE Define data formats and submission process Load, display, curate, review & release data Collect metadata and documentation Provide public website, viz, tools User outreach & support Support consortium communications (wiki) Support analysis group

Data submission website: submissions as of September 2010

Lifecycle of a data submission sub.tar.gz lab uploads to submission website loaded uploaded pipeline validates and loads into database wrangler configures browser track data fails validation or loading validate failed, load failed displayed (on test browser) lab approves track on test browser Q/A reviews and releases approved, reviewing released (to public browser)

ENCODE track quality review Data format checks Description and metadata complete & correct Configurability Display at different zoom levels and visibilities Performance Does the data make biological sense ? Usability

Released Data: 27 tracks in hg18, representing 860 experiments as of September 2010

Features planned for Year 2: High-resolution wiggle (bigWig) DONE RNAseq display enhancements DONE NCBI accessioning of seq data IN PROGRESS Track search tool IN REVIEW Progress since last SAB review (Feb ‘09) Plus: Integrated regulatory track Hg19/GRCh37 migration BAM support (spec, validation, display, c-tracks) Mid-course review, 4 data freezes, 2 analysis workshops, DCC site review Mouse ENCODE

Integrated regulatory tracks UCSC-developed integrative ENCODE track – shows enrichment of histone modifications suggestive of enhancer and promoter activity, DNAse clusters indicating open chromatin, regions of transcription factor binding, and transcription levels, derived from ENCODE data collected in multiple cell lines.

ENCODE data at NCBI GEO: Caltech RNA-seq

Mouse ENCODE experiment matrix 4 grants funded by the ARRA, 3 are now submitting data more cell types more factors

Simple search looks at: Track names and labeling Tracl description Metadata terms (specifically ENCODE controlled vocabulary) Finding data in the browser: Simple free-text search

Advanced search allows selection by defined metadata terms. (Currently only for ENCODE tracks) This search finds histone modification H3K4me3 as seen in H1-hESC cells. Finding data in the browser: By metadata terms

The results of the search on the previous slide is a single track of histone modification H3K4me3 as seen in H1-hESC cells. Clicking ‘View in Browser’ will display this data. Results from track search

Challenges Number of labs, difficulty of some Metadata expansion, special handling beyond normal browser data Multiple customers: NHGRI, analysis group, labs, user community Production vs. research Mission expansion: GEO/SRA, standards, ARRA, year 5 Reporting overhead Engineering staff -> hire ‘wranglers’ Funding delays

DCC site visit recommendations 1.Data accessibility Track search, Feature supertracks, Tutorial 2.Data usability 3.Data quality Post standards on website, Flag non-conforming data 4.Long-term repository Deposit data to GEO 5.Metadata user review 6.Use cases Session gallery on website 7.Reproducibility in publications 8.Web site Data snapshot on website, Improve labeling 9.Analysis data sets Integrated regulatory track, Imports from AWG 10.Metrics for success Blue items are DCC-specific

Impact on browser Expanded data – mostly useful, some not so much Pushes development of viz, tools, formats for large datasets Competes for staff and mgmt resources

People at the DCC PI: Jim Kent Technical project manager: Kate Rosenbloom Engineering / Wrangling: Tim Dreszer, Venkat Malladi, Brian Raney, Cricket Sloan, Melissa Cline Outreach, usability: Melissa, OpenHelix (contractor) Submissions website: Galt Barber GEO tools: Krishna Roskin Quality assurance: Katrina Learned, Vanessa Swing Browser management: Donna Karolchik, Bob Kuhn, Ann Zweig

Reporting: Monthly Quarterly Annual

Additional slides

Plans ENCODE tutorial Portal upgrade Complete GEO submissions Analysis tracks ARRA grants (protegenomics, epitope-tag) Release Mouse data

Browser features developed for ENCODE High resolution wiggle (bigWig) HTS formats (BAM and bigBed) BIG custom tracks View-based tracks Data selection matrix Metadata links Coming soon: Track Search

Initial tracks of mouse data (test browser)

GEO Submission Pipeline

Portal

ENCODE Outreach Publication: NAR 2010 Database issue (2011 update in press) Presentations: CSHL Statistical Analysis course June 2010, Stanford Computational Systems Bioinformatics, Aug 2010 Posters: CSHL Biology of Genomes May 2009, CSB 2010

OpenHelix ENCODE tutorial

Key items from site visit recommendations Make a track search tool to make it easy to find all data on one cell line or one transcription factor Organize data by biochemical entities rather than by lab. Put effort into high level documentation on website –“Sessions gallery” to show use cases –Page that give overview of what data is available in ENCODE including cells, antibodies, and assays. –Put up data summaries, figures, and presentations generated by the AWG onto site

Some user comments from DCC survey Linking annotation across all cell types and linking all annotations across one cell type would be quite nice. As it is now, it takes a fair bit of manual manipulation to do this. Great job, awesome resource. Thanks to all! Need more cell types and conditions. Do data from non- ENCODE consortium groups get incorporated? Amazingly there isn't a useful Encode summary, let alone a detailed description of the project and results. There's a nice do-loop with links between UCSC & NHGRI that don't lead anywhere. Is there a publication or link that I'm missing somewhere that informs, educates & is a users' guide? Great project, just difficult to sift through in it's current form. Encode only covers 1% of the human genome. Not sufficient coverage