Data management, curation, statistical analysis & display

Bob SinkovitsAfCS Bioinformatics Lab

San Diego Supercomputer CenterUC San Diego

The data management problem

• Collecting and archiving data• Tracking meta-data associated with

experiments (reagents, technicians, labs, dates, machine settings, protocols, etc.)

• Processing raw data• Curation• Organization and display• Data distribution

Data collection

Data acquisition for the AfCS involves the separate transfer of experimental data and the description of the experiment (meta–data)

SDSCExperimental Lab

GUIs

wgetdata (results)

meta-data

Data collectionExperimental data files transferred on a nightly basis using the UNIX wget utility under control of cron job

StanfordCaltech

SDSC

UTSW UCSFCa++, cAMP

phosphoproteincytokine

microarray

microscopysingle cell Ca++

Ca++

Vanderbilt

Lipid MS

Myriad

Y2H

Data collection•Meta-data inserted directly into the AfCS Oracle database through a set of GUIs

•Sample, experiment, cell line, etc. IDs are generated automatically based on date, laboratory code, etc.

•Error checking, the use of pull down menus, and database constraints ensure that valid data entered into GUIs

Data collection

Barcoding

• All experimental samples and materials (protein extracts, gels, cell preps, plasmids, solutions, reagents, etc.) are physically labeled using a 2-d barcode.

Zebra Z4M barcode printer Symbol Cyclone scanner

Data/information flow

Labs SDSC

parse.pl

SRB

Oracle 9i

Disk / Tape siloOff-site backup

(Caltech)

wwwpostprocess.pl

curationGUIs

data

meta-data

Storage of processed data

• Each type/category of experimental data is stored in a separate database schema• Easier to work with schemas containing

smaller numbers of tables• Minimizes possibility of data loss/corruption• Avoids confusion due to multiple developers

working in a single schema (overlap of namespaces)

• Easier recovery

• Privileges granted as needed between schemas

DataCenter organization

Data organized into several main sections

•Ligand screen•Two-ligand screen•Microscopy•Yeast two-hybrid

•Plasmid•Antibody•Lipid•FXM

Ligand screen

Measure response of cells due to stimulation by single ligands, using consistent conditions across all assays

Splenic B cell • Ca++• cAMP• phosphoprotein (11)• microarray (cDNA)

Raw 264.7• Ca++• cAMP• phosphoprotein (21)• cytokine (18)

Ligand screen

data archives

Results for ligand/assay combinationY/N used to provide quick overview

Assay details

Ligand details

Ligand screen

Results page contains explanation of assay, graphical display of data, and links to annotated tab-delimited files

CGS_30_uM_BC data

Ligand screen

Double ligand screen

Similar to single ligand screen, but involved stimulation by pairs of ligands, either sequentially or simultaneously

Splenic B cell • Ca++• cAMP

Raw 264.7• Ca++• cAMP• phosphoprotein (21)• cytokine (18)

Double ligand screen

Link to results found at intersection of ligand pair. Annotation based on additivity of ligand responses

Double ligand screen

Sample from phosphoprotein two-ligand display. Individual thumbnails linked to additional results

Double ligand screen

All results for phosphoprotein, ligand1, ligand2 combination

Phosphoprotein display in cell signaling context

•Quick overview of the signaling pathways activated

•User-friendly and attractive presentation of the data

•Easy way to navigate through the data•Highlight of the regulated proteins •http://biome.sdsc.edu:9080/

WesternDisplay

Goals

Phosphoprotein/signaling map

Phosphoprotein/signaling map

Phosphoprotein/signaling map

Phosphoprotein/signaling map

Phosphoprotein/signaling map

Data archivesArchives of data sets can be downloaded at

ftp://ftp.afcs.org/pub/datacenter

Data curation

• Need to provide convenient way for the AfCS labs to curate data• By ligand (don’t release until replicated)• By experiment (flag bad experiments)• By sample (flag bad samples w/o discarding

expt)

• Web interfaces for curation have been developed and are restricted by user

Data curation

• Ligand, experiments, and samples can be annotated in three ways

• Public – available for public• Internal – restricted to internal use. Validity of

data still being investigated or experimental conditions not yet replicated

• Invalid – experiment or sample flagged as being bad; not available to anyone

Data curation

Data curation by ligand

For curation by ligand, interface is based on the public display with additional features

Data curation by sample/expt

Curate by experiment

Curate by sample

Data curation by sample/expt

Curate by experiment

Curate by sample

Data curation by sample/expt

For some assays, such as cytokine and phosphoprotein, the large number of samples make curation by sampleid impractical. Curation limited to the experiment level

Data curation by sample/expt

Similar curation interfaces have been setup for FXM data

Lentivirally-Transduced RAW264.7 cells

Acknowledgements•Madhusudan, Ilango Vadivelu – LIMS•Stephen Lyon – web master•Brad Kroeger – systems administration•Chic Barna, Ray Bean – database administration•Sylvain Pradervand – phosphoprotein display•Shankar Subramaniam – “glue”

•Ron Taussig, Gil Sambrano, Richard Scheuermann - data center design

•Paul Sternweis – Ca++, cAMP display•Susie Mumby – phosphoprotein, cytokine display•Lonnie Sorrels, Keng-Mean Lin, Sangdun Choi,

Nick Wong, Robert Hsueh, Heping Han, Ruth Levitz