Your SlideShare is downloading. ×
0
The Trans‐NIH RNAi Ini0a0ve 
        Informa(cs 
         Rajarshi Guha 
Mission 
To establish a state of the art RNAi screening facility to perform
genome-wide RNAi screens with investigators in...
RNAi Informa0cs Infrastructure 
RNAi Analysis Workflow 
                                  Raw and              GO 
                                 Process...
RNAi Informa0cs Toolset 

• Local databases (screen data, pathways, 
  interac0ons, etc). 
• Commercial pathway tools.  
•...
Back End Services
                                

•  Currently all computa0onal analysis performed 
   on the backend 
•...
User Accessible Tools 
User Accessible Tools 
Challenge – siRNA Design & 
                             Valida5on 
•  We mostly depend on quality controls 
   implemente...
Challenge ‐ miRNA Target ID 

•  Screened a set of 885 human miRNA’s 
   for CPT sensi0za0on 
•  Iden0fied 23 sensi0zing mi...
Challenge ‐ RNAi & Small 
                                             Molecule Screens 
                                 ...
Challenge – RNAi Meta Analyses
                                    
•  Building up a collec0on of screens 
  –  Across cel...
The People 
•  Scoh Mar0n 
                       RNAi
•  Pinar Tuzmen 


•  Dac Trung Nguyen 
                          S...
Upcoming SlideShare
Loading in...5
×

The Trans-NIH RNAi Initiative : Informatics

1,040

Published on

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
1,040
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
6
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Transcript of "The Trans-NIH RNAi Initiative : Informatics"

  1. 1. The Trans‐NIH RNAi Ini0a0ve  Informa(cs  Rajarshi Guha 
  2. 2. Mission  To establish a state of the art RNAi screening facility to perform genome-wide RNAi screens with investigators in the intramural NIH community. •  Gene func0on  •  Pathway analysis  •  Target ID  •  Compound MoA  •  Drug antagonist/ agonist 
  3. 3. RNAi Informa0cs Infrastructure 
  4. 4. RNAi Analysis Workflow  Raw and  GO  Processed  annota0ons  Pathways  Data  Interac0ons  • Summary  Normaliza0on  • Thresholding  Hit Triage  sta0s0cs  • Median  • Hypothesis  • GO seman0c  • Correc0ons  • Quar0le  tes0ng  similarity  • Background  • Sum of ranks  • Pathways  • Interac0ons  QC  Hit Selec0on  Follow‐up  Hit List 
  5. 5. RNAi Informa0cs Toolset  • Local databases (screen data, pathways,  interac0ons, etc).  • Commercial pathway tools.   • Custom soUware for loading, analysis and  visualiza0on. 
  6. 6. 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 
  7. 7. User Accessible Tools 
  8. 8. User Accessible Tools 
  9. 9. 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 
  10. 10. 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   miRAnda  TargetScan  •  Link pathogenic  miRNA’s to human   targets 
  11. 11. Challenge ‐ RNAi & Small  Molecule Screens  What targets mediate activity of siRNA and compound Given a set of siRNA hits and their targets, is there a •  Reuse pre-existing MLI data compound showing similar •  Develop new annotated libraries inhibition CAGCATGAGTACTACAGGCCA  TACGGGAACTACCATAATTTA  Target ID and validation Link RNAi generated pathway peturbations to small molecule activities. Could provide insight into polypharmacology •  Run parallel RNAi screen Goal: Develop systems level view of small molecule activity
  12. 12. 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 
  13. 13. The People  •  Scoh Mar0n  RNAi •  Pinar Tuzmen  •  Dac Trung Nguyen  Small Molecules •  Yuhong Wang 
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×