Genome Browser The Plot Deepak Purushotham Hamid Reza Hassanzadeh Haozheng Tian Juliette Zerick Lavanya Rishishwar Piyush Ranjan Lu Wang

The Outline The Need & The Requirement The Options The Chosen One The New Age

THE NEED Why one should develop a Genome Browser

Why A Genome Browser? I want to analyze this organism

Why A Genome Browser? I want to analyze this organism Gene Functions Protein Domains Metabolic Pathways Comparative Analysis Synteny

THE REQUIREMENT What is expected out of a Genome Browser

A Genome Browser? I want something manageable

A Genome Browser!

The Genome Browser “Genome browsers facilitate genomic analysis by presenting alignment, experimental and annotation data in the context of genomic DNA sequences.” Melissa S Cline & James W Kent, 2009 Genome browsers aggregate data Taken From Andy Conley’s slides without permission

THE OPTIONS A Short Survey of the available Genome Browsers Modules

A Brief Time Travel FlyBase, SGD, MGD, and WormBase Setting up an MOD is expensive and time-consuming. The four MODs agreed in the fall of 2000 to pool their resources and to make reusable components available to the community free of charge under an open source license. The goal of this NIH-funded project, christened GMOD, is “…to generate a model organism database construction set that would allow a new model organism to be assembled by mixing and matching various components.”

GMOD

Who uses GMOD?

GMOD Components

Visualization - GBrowse

Visualization

JBrowse

GBrowse Synteny

CMAP

DATA MANAGEMENT

Chado

Tripal (

TableEdit

BioMart

InterMine

ANNOTATION

MAKER

DIYA

Galaxy

Ergatis

Apollo

REALLY EXCITING OPTION!

JBrowse Smooth, fast navigation (think Google Maps for genomes )

JBrowse Smooth, fast navigation (think Google Maps for genomes ) Supports BED, GFF, Bio::DB::*, Chado, WIG, BAM, UCSC (intron/exon structure, name lookups, quantitative plots) Relies on pre-indexing to minimize security exposure and runtime bandwidth/CPU load on the server (future versions more likely to do some server work at runtime) Has an API for customized track/glyph extensions Is stably funded by NHGRI, with many interesting innovations implemented & pending integration

Smoother UI

Most Genome browsers

How is JBrowse different?

First look: Live Demo A couple of JBrowses around the web

Types of Tracks

Pros Fast and smooth! User Friendly Works nicely on an iPad/iPhone too

Cons No user-uploaded data support Slow for big numbers of reference seqs (e.g. 5,000 annotated contigs) Few glyph options, feature tracks are limited by the facts of

What to pick?

? Tried and tested Fancy concept

THE CHOSEN ONE Gbrowse and its Features

GBrowse Most popular web based genome browser Visualize genome features along a reference sequence Open Source Highly customizable Excellent usability Rich set of “glyphs” – Genome features – Quantitative Data – Sequence Alignments

GBrowse Header Main Browser Window Track Menu

Under The Hood Client-Server Architecture GBrowse Architecture Installation Issues Input Data Configuration File Customization

Client Server Architecture 1. The user types in the URL: browser2012.biology.gatech.edu

Client Server Architecture 2. Browser interprets and sends the request to HTTP Server

Client Server Architecture 3. Web Server receives the request and “serves” the client i.e., starts Gbrowse

Client Server Architecture 4. In case of success, relevant hypertexts and multimedia is generated by accessing the database

Client Server Architecture 5. The output traverses the same path back

Client Server Architecture 5. The output traverses the same path back

Client Server Architecture 6. The whole process repeats again when the user interacts with the browser

How you see what you see Juxtaposed Images

How are so many images generated?

How you see what you see + Hyper Text files

How you see what you see Multimedia files + Hyper Text

©2002 by Cold Spring Harbor Laboratory Press Stein L D et al. Genome Res. 2002;12: GBrowse Architecture

The Bio::DB::SeqFeature database Schema

Attribute Attribute List Feature Name Type List Location List Parent2Child n n 1 1 n 1 n n n

Data file (.gff3) Reference Sequence (Chr/Clone /Contig) Source Eg: Prodigal/ Glimmer Type (sequence ontology (SO) terms) Start End Score Eg: E- value Strand Phase (0/1/2) Attributes Format: tag=value

Attributes (Data file) Different tags have predefined meanings: ID: Gives the feature a unique identifier. Useful when grouping features together (such as all the exons in a transcript). Name: Display name for the feature. This is the name to be displayed to the user. Alias: A secondary name for the feature. It is suggested that this tag be used whenever a secondary identifier for the feature is needed, such as locus names and accession numbers. Note: A descriptive note to be attached to the feature. This will be displayed as the feature's description. Alias and Note fields can have multiple values separated by commas. For example : Alias=M19211,gna-12,GAMMA-GLOBULIN Other good stuff can go into the attributes field.

Gbrowse Configuration File Global Website Settings Additional HTML Pages JavaScript Jquery Global Database Settings Data Source Definitions

Customizations

Configuration file (.conf)

Making a new Track ### TRACK CONFIGURATION ### [ExampleFeatures] feature = remark glyph = generic stranded = 1 bgcolor = orange height = 10 key = Example Features

Adding Multiple Tracks Data: Configuration: Result UI: Searchable Links Popup balloons with links

Searching for Features Gene symbols Gene IDs Sequence IDs Genetic markers Relative nucleotide coordinates Absolute nucleotide coordinates etc... click

Viewing Multiple Tracks Low Magnification

Viewing Multiple Tracks High Magnification

In short… Main features (Determination of protein coding and non-coding,…) Quantitative data (E-value, Identity percentage) Other evidences (Interpro, CoGs, etc.) GC content and other useful measurements Protein and DNA sequences

THE NEW AGE Value-Added Additions

RICHER ANNOTATION What’s New

INCREASED ANNOTATION INFO Richer Annotation

INTEGRATED QUALITY SCORE Richer Annotation

Origin of Database Matches

Quality Value Integration

Quality Scores Origin of Database Matches

Different E-values shown with different shades of colors

What’s New MORE LINK-OUTS

COGs KEGG ID

PATHWAYS What’s New

KEGG ID KEGG Genes KEGG Compound KEGG Pathway

ORGANISM SPECIFIC PAGES Synthesis!

Organism Summary Page At this point of the course, we have gathered a lot of information for the strains we are dealing with Not all of this information could be represented inside the genome browser We propose a separate section in the browser containing strain-wise summarized information

Organism Summary Page Conceptually, the page could contain: – Biological information – Assembly information: Genome Size, Number of contigs, N50, Sequencing platform – Gene Prediction information: Number of protein coding and non-protein coding genes, links to 16s rRNA gene – Annotation information: Percent annotation, function distribution pie – Comparative information: Unique protein clusters, etc.

Organism Summary Page

OPERONS Adding more values

Operons Operon “…is a functioning unit of genomic DNA containing a cluster of genes under the control of a single regulatory signal or promoter” ~70% of the genes have been assigned a unique OperonID OperonID will provide an additional browsing mechanism for biologist connecting co- transcribed and co-regulated genes.

Operons

Incorporating Operon Information

BRIG PATTERN More with Comparison

BRIG Patterns Concept: To either generate BRIG images at run time or load static images when the user requests for BRIG Pattern between two species

BRIG Patterns

That’s All Folks! Questions? Comments? Concerns? If you have any suggestions, we would love to hear from you! (There is a page on Wiki for it!)