the trans-nih rnai initiative: informatics

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The Trans‐NIH RNAi Ini0a0ve Informa(cs Rajarshi Guha

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Page 1: The Trans-NIH RNAi Initiative: Informatics

The Trans‐NIH RNAi Ini0a0ve Informa(cs 

Rajarshi Guha 

Page 2: The Trans-NIH RNAi Initiative: Informatics

Mission 

•  Gene func0on •  Pathway analysis •  Target ID •  Compound MoA •  Drug antagonist/agonist 

To establish a state of the art RNAi screening facility to perform genome-wide RNAi screens with investigators in the intramural NIH community.

Page 3: The Trans-NIH RNAi Initiative: Informatics

RNAi Informa0cs Infrastructure 

Page 4: The Trans-NIH RNAi Initiative: Informatics

• Summary sta0s0cs 

• Correc0ons 

QC 

• Median • Quar0le • Background 

Normaliza0on • Thresholding • Hypothesis tes0ng 

• Sum of ranks 

Hit Selec0on 

• GO seman0c similarity 

• Pathways • Interac0ons 

Hit Triage 

RNAi Analysis Workflow 

Raw and Processed 

Data 

GO annota0ons Pathways Interac0ons 

Hit List Follow‐up 

Page 5: The Trans-NIH RNAi Initiative: Informatics

RNAi Informa0cs Toolset 

• Local databases (screen data, pathways, interac0ons, etc). 

• Commercial pathway tools.  

• Custom soUware for loading, analysis and visualiza0on. 

Page 6: The Trans-NIH RNAi Initiative: Informatics

Back End Services 

•  Currently all computa0onal analysis performed on the backend 

•  R & Bioconductor code •  Custom R package (ncgcrnai) to support NCGC infrastructure –  Partly derived from cellHTS2 –  Supports QC metrics, normaliza0on, adjustments, selec0ons, triage, (sta0c) visualiza0on, reports 

•  Some Java tools for – Data loading –  Library and plate registra0on 

Page 7: The Trans-NIH RNAi Initiative: Informatics

User Accessible Tools 

Page 8: The Trans-NIH RNAi Initiative: Informatics

User Accessible Tools 

Page 9: The Trans-NIH RNAi Initiative: Informatics

Challenge – siRNA Design & Valida5on 

•  We mostly depend on quality controls implemented by vendor – siRNA design algorithms not a high priority 

•  Always interested in extra filters that help us get a reliable hit list 

•  Would like to have measures of  – Off‐target effects – Protein half lives 

Page 10: The Trans-NIH RNAi Initiative: Informatics

Challenge ‐ miRNA Target ID 

•  Screened a set of 885 human miRNA’s for CPT sensi0za0on 

•  Iden0fied 23 sensi0zing miRNA’s •  But, we don’t have target informa0on 

–  Predic0ons aren’t par0cularly helpful –  Poor overlap with siRNA hits  

•  Link pathogenic miRNA’s to human  targets 

miRAnda  TargetScan 

Page 11: The Trans-NIH RNAi Initiative: Informatics

Challenge ‐ RNAi & Small Molecule Screens 

Goal: Develop systems level view of small molecule activity

•  Reuse pre-existing MLI data •  Develop new annotated libraries

TACGGGAACTACCATAATTTA 

CAGCATGAGTACTACAGGCCA 

•  Run parallel RNAi screen

What targets mediate activity of siRNA and compound

Given a set of siRNA hits and their targets, is there a compound showing similar inhibition

Target ID and validation

Link RNAi generated pathway peturbations to small molecule activities. Could provide insight into polypharmacology

Page 12: The Trans-NIH RNAi Initiative: Informatics

Challenge – RNAi Meta Analyses 

•  Building up a collec0on of screens – Across cell lines, species, … – Not necessarily “designed” 

•  What do we do with this? –  Iden0fy consistent markers  – Characterize differences between cell lines  

– Extrapolate from gene knockdown to pathway and higher level differences 

– Merge with gene expression data 

Page 13: The Trans-NIH RNAi Initiative: Informatics

The People 

•  Scoh Mar0n •  Pinar Tuzmen 

•  Dac Trung Nguyen •  Yuhong Wang 

RNAi

Small Molecules