Presentation of the

CRG Bioinformatics Core facility

Jean-François Taly

People in the BioCore

Jean-Francois Luca Toni•@CRG 2009•@BioCore 2012•Acting head•Structur. bioinfo.•MSA•NGS analyst•Galaxy server•Training

•@BioCore 2010•NGS analyst•Small ncRNA prediction•Motif analysis•Training

•@Biocore 2009•Wikis•Web/DB dev.•DB Mirrors•Struct. bioinfo.•Training

•@Biocore 2014•Micro-arrays•NGS analyst•Galaxy•Training

Sarah

Our mission

• Expertise in bioinformatics• Service• Consultation

• Trainings • Internal and external

• Support in infrastructures• In collaboration with the SIT and TIC

• Part of the CRG bioinformaticians network• 83 @ bioinformatics retreat• Many more in PRBB/CNAG

Our services

Analysis Microarray Chip-seq RNA-seq DE and assembly Genome assembly Variant calling

Informatics support Wiki WEB Server API

Trainings Galaxy, Perl, Linux, advanced bioinformatics

Fee per service

Item PRBB fees Public fees without VAT

Manual data analysis 13.12 €/hour 39.36 €/hour

Automated data analysis (CPU time)

2.38 €/hour 7.16 €/hour

Our contribution to projects

Project conception

Bioinfo exp. design

Bioinfo exp. realization

Bioinfo output interpretation

Project conclusions

Our contribution to projects

Project conception

Bioinfo exp. design

Bioinfo exp. realization

Bioinfo output interpretation

Project conclusions

Apply a definedprocedures

Our contribution to projects

Project conception

Bioinfo exp. design

Bioinfo exp. realization

Bioinfo output interpretation

Project conclusions

CustomizedAnalysis

CRG bioinformatics community

Big Data WG• EGA initiative• Data Engineering• NoSQL• HPC

NGS Tech. Sem.• RNA-seq• G. assembly• Variant Annot.• Metagenomics

Other topics• Integrated -omics• Good practice in

code dev.• Galaxy dev.• …

source: Creative Commons, Wikipedia

Gene expression array data analysis:• Background correction and normalization• Differential expression analysis• Gene Ontology and pathway analysis• Various graphics / plots

Additional array-based technologies the Bioinformatics unit supports include:• qPCR arrays• Comparative Genomics Hybridization arrays

Main tools are based on the R / Bioconductor environment

Micro-arrays

RNA-seq

RNA-seq

DNA-seq

DNA-seq

Pevzner P A et al. PNAS 2001;98:9748-9753

Chip-seq

Chip-seq

Growing to the next level

From gene DE to transcripts DE Users have now access to longer reads and deeper coverage

Metagenomics 16S Ribosomal amplicon sequencing with MiSeq

Data integration framework Combining different data types into one single analysis

RNAseq DE Histone marks Metabolomics data Proteomics

Data analysis workflow on Galaxy Leave the basic processing to users and focus on advanced analysis

Databases mirroring

Biological file sources ENSEMBL UCSC NCBI Blast DBs UniProt PDB Igenomes (Illumina, only Human but the rest is upcoming)

All Indexed and formated for NCBI BLAST+ (makeblastdb for proteins and nucleic acids) Bowtie & Bowtie2 BWA Fastaindex (Exonerate) GEM faTo2bit

Where are they stored?

In CRG common storage: /db

More information: http://biocore.crg.cat/wiki/Category:Mirrors

IMPORTANT: /db/seq (former /seq) IS DEPRECATED

WEB and Database services

Applications Data and project management Platforms for big data analysis and complex information

querying Promotion and publication of scientific results

WEB and Database services Example

Superfly for Yogi Jaëger Visual catalogue of gene embryo development of different fly

species.

WEB and Database services Example

PRGDB with Walter Sanseverino Wiki-based Database of plant resistance genes.

Activity per category in 2014

Presentation of the Galaxy platform

Jean-François Taly Bioinformatics Core Facility

CRG (Barcelona, Catalonia, Spain)September 18th 2014

EMBO Global Exchange CoursePasteur Institute of Tunis, Tunisia

Biologists: Linux-free data analysis with a graphical

interface

Bioinformaticians: Insure reproducibility when sharing analysis

and workflows Teach their knowledge to a broad audience Get access to workflows for topics they are

not familiar of

Software Developers: Diffuse their tools on a standardized platform

Why Should I Use Galaxy?

The Galaxy Team

Galaxy is developed by :• The Nekrutenko lab in the center for

Comparative Genomics and Bioinformatics at Penn State University

• The Taylor lab at Johns Hopkins University• The community

https://wiki.galaxyproject.org/GalaxyTeam

Rationale behind GalaxyFrom Goeks et al. Genome Biol. 2010.

“Computation has become an essential tool in life science research. This is exemplified in genomics, where first microarrays and now massively parallel DNA sequencing have enabled a variety of genome-wide functional assays, such as ChIP-seq and RNA-seq (and many others), that require increasingly complex analysis tools. However, sudden reliance on computation has created an 'informatics crisis' for life science researchers: computational resources can be difficult to use, and ensuring that computational experiments are communicated well and hence reproducible is challenging. Galaxy helps to address this crisis by providing an open, web-based platform for performing accessible, reproducible, and transparent genomic science. “

Biologists: Linux-free data analysis with a graphical

interface

Bioinformaticians: Insure reproducibility when sharing analysis

and workflows Teach their knowledge to a broad audience Get access to workflows for topics they are

not familiar of

Software Developers: Diffuse their tools on a standardized platform

Why Should I Use Galaxy?

Makes bioinformatics accessible

From a command line …

… to a graphical interface

One step

Multi-step protocol1

2

3

4

5

Workflow

Galaxy Tutorials https://usegalaxy.org/u/jeremy/p/galaxy-rna-seq-analysis-exercise

https://wiki.galaxyproject.org/Learn

NGS in a laptop• MinION brings NGS to your laptop

• http://youtu.be/UtXlr19xTh8

Biologists: Linux-free data analysis with a graphical

interface

Bioinformaticians: Insure reproducibility when sharing analysis

and workflows Teach their knowledge to a broad audience Get access to workflows for topics they are

not familiar of

Software Developers: Diffuse their tools on a standardized platform

Why Should I Use Galaxy?

Reproducibility

Bioinformaticians suffer that too!• Results can change in function of

• Libraries and software versions• Genome annotations

• Results published without the code

Want to share your findings with everybody?

• Froze an environment in a Virtual Machine• Use an application controller (Docker) • Prepare a Galaxy workflow

Improve the visibility of a paper

“A Galaxy workflow and the corresponding wrappers are available to download at https://mylab.com. A virtual machine containing a pre-set up server can be download at the same address “

Why not having as well?

Galaxy Workflows

Biologists: Linux-free data analysis with a graphical

interface

Bioinformaticians: Insure reproducibility when sharing analysis

and workflows Teach their knowledge to a broad audience Get access to workflows for topics they are

not familiar of

Software Developers: Diffuse their tools on a standardized platform

Why Should I Use Galaxy?

Wrapping software

Software

The wrapper prepare the command line

XML file

Simple wrapper example

venn_diagram.sh Wrapper can launch scripts

TopHat wrapper (1) XML file describing tophat parameters

TopHat wrapper (2) XML file describing tophat parameters

Community Tools/Wrappers

Galaxy Public servers Good points

Free No IT tasks Comes with reference genomes and

workflows

Bad points Offer Limited Resources (Disk/CPUs) Data transfer may be long Give access to the tools they want Data security may not be respected

Should I install Galaxy?

Galaxy Public Servers https://wiki.galaxyproject.org/PublicGalaxyServers

Galaxy Local Server Good points

Total control on data and tools Your own disk and CPU limitation Some companies sell a ready-to-use

infrastructure Tool shed helps to install wrappers and

software

Bad points Cost of installation and maintenance Need IT supports if you need a multi-users

advanced set up

Should I install Galaxy?

Get Galaxy https://wiki.galaxyproject.org/Admin/GetGalaxy

Can be installed only in Linux or Mac

NFS:/software

HPC

User

/scratch

Sequences Indexes

Files, Back-up, tmp

FTP

NFS

NFS:/db

Galaxy server

Tools

DATA Software

30 days max.

Files > 2Gb

Database engine Galaxy team recommend postgreSQL but can it be

MySQL Store users details and data information

Tools = wrappers File describing all possible parameters of a software Script preparing the correct command line

Apache server

Shared file system NFS (2Pb)

10 €/Tb/Group/Month Access to the shared biological resources

Ensembl, UCSC Genomes and indexes Uniprot, pfam, smart, PDB

Access to the shared software repository

High Performance Computing 7 cores 8 CPUS each (56 tot) 47 Gb memory

FTP server Proftpd for the server side I recommend Filezila for the client (multiplatform)

Upload from Galaxy Files are moved to the shared file system

Galaxy is an open, web-based platform for computational biomedical research.

Accessible: Users without programming experience can run tools and workflows

Reproducible: Galaxy captures analysis details Transparent: Users can share and publish

analyses

WIKI: https://wiki.galaxyproject.org/FrontPage

Summary

http://galaxy.crg.es/

Demo on Galaxy@CRG