1. ArrayExpress and Gene Expression Atlas: Mining Functional Genomics data Gabriella Rustici, PhD Functional Genomics Team EBI-EMBL gabry@ebi.ac.uk

2. ArrayExpress2 Talk structure  Why do we need a database for functional genomics data?  ArrayExpress database Archive Gene Expression Atlas  ArrayExpress content  How to query the database  How to download data  How to submit data

3. What is functional genomics (FG)? The aim of FG is to understand the function of genes and other parts of the genome FG experiments typically utilize genome-wide assays to measure and track many genes (or proteins) in parallel under different conditions High-throughput technologies such as microarrays and high-throughput sequencing (HTS) are frequently used in this field to interrogate the transcriptome 3ArrayExpress

4. What biological questions is FG addressing? When and where are genes expressed? How do gene expression levels differ in various cell types and states? What are the functional roles of different genes and in what cellular processes do they participate? How are genes regulated? How do genes and gene products interact? How is gene expression changed in various diseases or following a treatment? 4ArrayExpress

5. Components of a FG experiment ArrayExpress5

6. ArrayExpress www.ebi.ac.uk/arrayexpress/  Is a public repository for FG data, which provides easy access to well annotated data in a structured and standardized format  Serves the scientific community as an archive for data supporting publications, together with GEO at NCBI and CIBEX at DDBJ  Facilitates the sharing of experimental information associated with the data such as microarray designs, experimental protocols,……  Based on community standards: MIAME guidelines & MAGE-TAB format for microarray, MINSEQE guidelines for HTS data (http://www.mged.org/minseqe/) ArrayExpress6

7. Reporting standards for sequencing MINSEQE checklist  Minimal Information about a high-throughput Nucleotide SEQuencing Experiment  The proposed guidelines for MINSEQE are (still work in progress): 1.General information about the experiment 2.Essential sample annotation including experimental factors and their values (e.g. compound and dose) 3.Experimental design including sample data relationships (e.g. which raw data file relates to which sample, ….) 4.Essential experimental and data processing protocols 5.Sequence read data with quality scores, raw intensities and processing parameters for the instrument 6.Final processed data for the set of assays in the experiment ArrayExpress7

8. MAGE-TAB is a simple spreadsheet format that uses a number of different files to capture information about a microarray experiment. We adapted it to handle HTS data: IDFInvestigation Description Format file, contains top-level information about the experiment including title, description, submitter contact details and protocols. SDRFSample and Data Relationship Format file contains the relationships between samples and arrays, as well as sample properties and experimental factors, as provided by the data submitter. Data filesRaw and processed data files. The ‘raw’ data files are the trace data files (.srf or.sff). Fastq format files are also accepted, but SRF format files are preferred. The trace data files that you submit to ArrayExpress will be stored in the European Nucleotide Archive (ENA).European Nucleotide Archive The processed data file is a ‘data matrix’ file containing processed values, e.g. files in which the expression values are linked to genome coordinates. 8 Standards for microarray & sequencing MAGE-TAB format HTS data in ArrayExpress and Atlas

9. ArrayExpress9 ArrayExpress – two databases

10. What is the difference between them? ArrayExpress10 ArrayExpress Archive Central object: experiment Query to retrieve experimental information and associated data Expression Atlas Central object: gene/condition Query for gene expression changes across experiments and across platforms

11. ArrayExpress – two databases ArrayExpress11

12. ArrayExpress Archive – when to use it? Find FG experiments that might be relevant to your research Download data and re-analyze it. Often data deposited in public repositories can be used to answer different biological questions from the one asked in the original experiments. Submit microarray or HTS data that you want to publish. Major journals will require data to be submitted to a public repository like ArrayExpress as part of the peer-review process. ArrayExpress 12

13. How much data in AE Archive? ArrayExpress13 GEO import

14. ArrayExpress14 Browsing the AE Archive

15. The direct link to raw and processed data. An icon indicates that this type of data is available. The total number of experiments and assay retrieved Species investigated Curated title of experiment The date when the data were loaded in the Archive AE unique experiment ID Number of assays The list of experiments retrieved can be printed, saved as Tab- delimited format or exported to Excel or as RSS feed loaded in Atlas flag Raw sequencing data available in ENA ArrayExpress15

16. ArrayExpress16 Browsing the AE Archive

17. Experimental factor ontology (EFO) http://www.ebi.ac.uk/efo  Application focused ontology modeling experimental factors (EFs) in AE – selected by default  Developed to: increase the richness of annotations that are currently made in AE Archive to promote consistency to facilitate automatic annotation and integrate external data  EFs are transformed into an ontological representation, forming classes and relationships between those classes  EFO terms map to multiple existing domain specific ontologies, such as the Disease Ontology and Cell Type Ontology ArrayExpress17

18. ArrayExpress18 Building EFO An example sarcoma cancer neoplasm disease Kaposi’s sarcoma Take all experimental factors sarcoma cancer neoplasm Kaposi’s sarcoma disease is the parent term is a type of disease is synonym of neoplasm is a type of cancer is a type of sarcoma Find the logical connection between them disease neoplasm cancer sarcoma Kaposi’s sarcoma [-] Organize them in an ontology

19. ArrayExpress19 Exploring EFO An example

20. Searching AE Archive Simple query ArrayExpress20

21. Searching AE Archive Simple query  Search across all fields: AE accession number e.g. E-MEXP-568 Secondary accession numbers e.g. GEO series accession GSE5389 Experiment name Submitter's experiment description Sample attributes, experimental factor and values, including species (e.g. GeneticModification, Mus musculus, DREB2C over-expression) Publication title, authors and journal name, PubMed ID  Synonyms for terms are always included in searches e.g. 'human' and 'Homo sapiens’ ArrayExpress21

22. AE Archive query output Matches to exact terms are highlighted in yellow Matches to synonyms are highlighted in green Matches to child terms in the EFO are highlighted in pink

23. 23 RNA-seq data in AE Archive HTS data in ArrayExpress and Atlas

24. 24 AE Archive – experiment view HTS data in ArrayExpress and Atlas

25. Master headline 19.09.2015 25 Link to raw data in ENA

26. 26 AE Archive – experiment view HTS data in ArrayExpress and Atlas

27. SDRF file – sample & data relationship ArrayExpress27

28. ArrayExpress – two databases ArrayExpress28

29. Expression Atlas – when to use it? Find out if the expression of a gene (or a group of genes with a common gene attribute, e.g. GO term) change(s) across all the experiments available in the Expression Atlas; Discover which genes are differentially expressed in a particular biological condition that you are interested in. ArrayExpress 29

30.  The criteria we use for selecting experiments for inclusion in the Atlas are as follows: Array designs relating to experiment must be provided to enable re-annotation using Ensembl or Uniprot (or have the potential for this to be done) High MIAME scores Experiment must have 6 or more hybridizations Sufficient replication and large sample size EF and EFV must be well annotated Adequate sample annotation must be provided Processed data must be provided or raw data which can be renormalized must be available Expression Atlas construction Experiment selection criteria ArrayExpress30

31. ArrayExpress31  New meta-analytical tool for searching gene expression profiles across experiments in AE  Data is taken as normalized by the submitter  Gene-wise linear models (limma) and t-statistics are applied to calculate the strength of genes’ differential expression across conditions across experiments  The result is a two-dimensional matrix where rows correspond to genes and columns correspond to conditions, rather than samples.  The matrix entries are p-values together with a sign, indicating the significance and direction of differential expression Expression Atlas construction Analysis pipeline

32. ArrayExpress32 Expression Atlas construction

33. ArrayExpress33 Expression Atlas construction

34. ArrayExpress34 Expression Atlas

35. ArrayExpress35 Atlas home page http://www.ebi.ac.uk/gxa/ Query for genes Query for conditions Restrict query by direction of differential expression The ‘advanced query’ option allows building more complex queries

36. Atlas home page The ‘Genes’ and ‘Conditions’ search boxes ArrayExpress36

37. Atlas home page A single gene query ArrayExpress37

38. Atlas gene summary page ArrayExpress38

39. Atlas experiment page ArrayExpress39

40. ArrayExpress40 Atlas experiment page – HTS data

41. ArrayExpress41 Atlas home page A ‘Conditions’ only query

42. ArrayExpress42 Atlas heatmap view

43. Atlas gene-condition query ArrayExpress43

44. Atlas advanced search ArrayExpress44

45. Atlas advanced search ArrayExpress45

46. Atlas advanced search ArrayExpress46

47. ArrayExpress47 Data submission to AE

48. ArrayExpress48 Data submission to AE www.ebi.ac.uk/microarray/submissions.html

49. Submission of HTS gene expression data Submit via MAGE-TAB submission route Submit: MAGE-TAB spreadsheet containing details of the samples and protocols used. Trace data files for each sample (in SRF, FASTQ or SFF format ) Processed data files For non-human species we will supply your SRF or FASTQ files to the European Nucleotide Archive (ENA). If you have human identifiable sequencing data you need to submit to the The European Genome-phenome Archive and not ArrayExpress. They will supply you with a suitable template for submission and store human identifiable data securely. ArrayExpress49

50. Types of data that can be submitted ArrayExpress50

51. What happens after submission? Email confirmation Curation The curation team will review your submission and will email you with any questions. Possible reopening for editing We will send you an accession number when all the required information has been provided. We will load your experiment into ArrayExpress and provide you with a reviewer login for viewing the data before it is made public. ArrayExpress51

52. Find out more Visit our eLearning portal, Train online, at http://www.ebi.ac.uk/training/online/ for courses on ArrayExpress and Atlas http://www.ebi.ac.uk/training/online/ Email us at: miamexpress@ebi.ac.ukmiamexpress@ebi.ac.uk Atlas mailing list: arrayexpress-atlas@ebi.ac.ukarrayexpress-atlas@ebi.ac.uk ArrayExpress52