Using Ensembl tools for browsing ENCODE data

Size: px

Start display at page:

Download "Using Ensembl tools for browsing ENCODE data"

Kelly Newton
10 years ago
Views:

1 Using Ensembl tools for browsing ENCODE data Bert Overduin, Ph.D. Vertebrate Genomics Team EMBL - European Bioinformatics Institute Wellcome Trust Genome Campus Hinxton, Cambridge CB10 1SD United Kingdom

2 Outline Presentation Introduction to Ensembl ENCODE data hub Ensembl Regulatory Build Regulatory segmentation Adding custom tracks BioMart Variant Effect Predictor Worked examples Browser / Regulation BioMart Variation Effect Predictor Hands-on exercises

tracks BioMart Variant Effect Predictor Worked examples Browser

3 Ensembl - Goal To provide automatic annotation of completely sequenced vertebrate genomes To integrate this annotation with other available biological data To make all this information available to the scientific community

this annotation with other available biological data To

4 Species v71 (Apr 2013): 70 genomes (61 fully supported, 9 on Pre!) Primates Rodents etc. Laurasiatheria Afrotheria Xenartha Other mammals Birds & reptiles Amphibians Fish Other chordates Other eukaryotes On Pre! Ensembl

5 Data Genomic sequence Gene / transcript / protein models External references Mapped cdnas, proteins, microarray probes, BAC clones, cytogenetic bands, repeats, markers etc. etc. Variation data Sequence / short variants Structural variants Comparative data Gene trees, orthologues, paralogues, protein families Pairwise and multiple whole genome alignments, syntenic regions Regulatory data ENCODE data Regulatory Build: best guess set of regulatory data

etc. Variation data Sequence / short variants Structural variants Comparative data Gene trees, orthologues,

6 Access to data Ensembl web site Pre! web site Archive! web site BioMart FTP site Amazon Web Services MySQL Perl API REST API ftp://ftp.ensembl.org

ensembl.org http://aws.amazon.com/publicdatasets http://www.ensembl.org/info/data/mysql.

7 Official (cloud-based) mirrors United States West Coast United States East Coast Asia Geo-IP-based redirection

org United States East Coast http://useast.

8 ENCODE data hub Data from ENCODE integrative analysis ( ) Can be attached as a TrackHub integration_data_jan2011/hub.txt > 2800 tracks

9 Ensembl Regulatory Build Provides a single best guess set of regulatory features For human and mouse Created by overlap analysis of annotations from genome-wide data sets in a two stage cell type aware manner

analysis of annotations from genome-wide data sets in a two

10 Regulatory Build data Focus features (define potential binding sites) 13 cell types Open chromatin (DNase1, FAIRE) ENCODE CTCF (insulator/enhancer) binding sites Roadmap Epigenomics Binding sites for 90 transcription factors Attribute features 42 Histone modifications (methylation, acetylation) RNA Pol II and III binding sites Meta data: Focus features (define potential binding sites) 5 cell types Open chromatin (DNase1) ENCODE CTCF (insulator/enhancer) binding sites Binding sites for 22 transcription factors Attribute features 8 Histone modifications (methylation, acetylation) RNA Pol II binding sites Meta data:

org/homo_sapiens/experiment/sources Focus features (define potential binding sites) 5 cell types Open chromatin (DNase1) ENCODE CTCF (insulator/enhancer) binding sites Binding sites

11 Regulatory Build procedure Regulatory feature construction: Identify core regions across all available cell types using focus features Extend core regions in a cell type specific manner using attribute features Regulatory feature annotation: Classify regulatory features Annotate the position of putative TFBSs using position weight matrices (PWMs) taken from the JASPAR database

using attribute features Regulatory feature annotation: Classify regulatory features Annotate

12 Regulatory feature construction Focus features DNase1 Cell type 1 CTCF Cell type 1 Taf1 Cell type 1 DNase1 Cell type 2 CTCF Cell type 2 Attribute features H3K4me1 Cell type 1 H3K4me1 Cell type 3 H3K4me3 Cell type 3 H3K27ac Cell type 3 MultiCell reg feature Cell type 1 reg feature Cell type 2 reg feature Cell type 3 reg feature

Cell type 1 H3K4me1 Cell type 3 H3K4me3 Cell type 3 H3K27ac Cell type 3 MultiCell

13 Regulatory feature annotation Promoter Associated Gene Associated Non-gene Associated Polymerase III Associated Unclassified Patterns over-represented in the region of the transcription start site plus or minus 2500 bp upstream of protein coding genes, but not in the downstream gene body. Likely to be a 5' proximal promoter. Patterns over-represented in gene bodies. Often represent gene's transcriptional activity (expressed/ repressed). Patterns over-represented in non-gene regions. Likely to correspond to a distal regulatory element such as an insulator or enhancer. Patterns over-represented in regions 2500 bp upstream of PolIII transcribed regions e.g. trnas. Likely to correspond to a proximal regulatory element specifically associated to Polymerase III transcription. Patterns which are currently unclassifiable.

Often represent gene's transcriptional activity (expressed/ repressed). Patterns over-represented in non-gene regions.

14 Regulatory feature annotation signal peak ChiP-Seq signal for transcription factor MAX regulatory feature Position Weight Matrix for MAX from JASPAR database

15 Regulatory segmentation Provides a summary of the functional architecture (or state ) of the human genome 6 cell types 14 assays, constituting 3 classes of data: open chromatin, transcription factors, histone modifications Segmentations produced using 2 programs: ChromHMM and Segway Segments classified into 7 classes

data: open chromatin, transcription factors, histone modifications

16 Regulatory segmentation

17 Regulatory segmentation CTCF WE T E PF R TSS CTCF enriched Predicted Weak Enhancer/Cis-reg element Predicted Transcribed Region Predicted Enhancer Predicted Promoter Flank Predicted Repressed/Low Activity Predicted Promoter with TSS

Predicted Transcribed Region Predicted Enhancer Predicted

18 Adding custom tracks Upload data Data saved by Ensembl 5 MB limit (and therefore not possible for large file formats) Attach remote file No size limit URL-based (http or ftp) Uploaded / attached tracks can be saved (to account) Uploaded / attached tracks can be shared with other users Only trivial security, do not use for sensitive data

ftp) Uploaded / attached tracks can be saved (to account) Uploaded / attached tracks

19 Adding custom tracks Possible formats: BAM sequence alignments (no upload) BED genes / features BedGraph continuous-valued data BigBed genes / features (no upload) BigWig continuous-valued data (no upload) TrackHub collection of tracks (no upload) GBrowse genes / features GFF / GTF genes / features PSL sequence alignments VCF variants (no upload) WIG continuous-valued data

continuous-valued data (no upload) TrackHub collection of tracks (no upload) GBrowse genes /

20 BioMart Data retrieval tool Originally developed for Ensembl (EnsMart) Now used by many large data resources Integrated with several widely used software packages, e.g. Galaxy ( Central portal:

with several widely used software package

21 BioMart - Principle Step 1 - Dataset Choose your dataset and species Step 2 - Filters Limit your dataset Step 3 - Attributes Specify what information you want to output Step 4 - Results Preview and output your results

22 Variant Effect Predictor (VEP) Predicts functional consequences of variants on Ensembl genes Annotates SNPs, indels and structural variants Accessible through web interface, REST server or Perl script Accepts tab-delimited, VCF and pileup format, variant identifiers and HGVS notations (on genome and Ensembl and RefSeq transcripts) as input SIFT and PolyPhen predictions for missense variants included for human

23 Workshops Browser (0.5-2 days) and API (1-3 days) workshops Combination of lectures and hands-on exercises Advertised on You can host your own workshop! For academic institutions there is no fee, apart from the instructor s expenses You only need a computer room and participants You can get more info from [email protected] or me ([email protected])

24 Help & Keeping in touch Helpdesk Mailing lists YouTube and YouKu (优酷网) channels: Blog Facebook Twitter

25 Nucl. Acids Res. (2012) doi: /nar/gks1236. Ensembl Paul Flicek, Ikhlak Ahmed, M. Ridwan Amode, Daniel Barrell, Kathryn Beal, Simon Brent, Denise Carvalho-Silva, Peter Clapham, Guy Coates, Susan Fairley, Stephen Fitzgerald, Laurent Gil, Carlos García-Girón, Leo Gordon, Thibaut Hourlier, Sarah Hunt, Thomas Juettemann, Andreas K. Kähäri, Stephen Keenan, Monika Komorowska, Eugene Kulesha, Ian Longden, Thomas Maurel, William M. McLaren, Matthieu Muffato, Rishi Nag, Bert Overduin, Miguel Pignatelli, Bethan Pritchard, Emily Pritchard, Harpreet Singh Riat, Graham R. S. Ritchie, Magali Ruffier, Michael Schuster, Daniel Sheppard, Daniel Sobral, Kieron Taylor, Anja Thormann, Stephen Trevanion, Simon White, Steven P. Wilder, Bronwen L. Aken, Ewan Birney, Fiona Cunningham, Ian Dunham, Jennifer Harrow, Javier Herrero, Tim J. P. Hubbard, Nathan Johnson, Rhoda Kinsella, Anne Parker, Giulietta Spudich, Andy Yates, Amonida Zadissa and Stephen M. J. Searle

26 Funding European Commission Framework Programme 7

Genome Viewing. Module 2. Using Genome Browsers to View Annotation of the Human Genome

Genome Viewing. Module 2. Using Genome Browsers to View Annotation of the Human Genome Module 2 Genome Viewing Using Genome Browsers to View Annotation of the Human Genome Bert Overduin, Ph.D. PANDA Coordination & Outreach EMBL - European Bioinformatics Institute Wellcome Trust Genome Campus