Collecting quantitative CNV information using
           aCGH in a Cytogenetic laboratory
                                ...
Overview
Copy  number  analysis  of  array  CGH  data
   Overview  of  an  array-­‐based  Cytogenetic  test
   Looking  fo...
Array-based copy number tests: data analysis
Data  pre-­‐processing
   Raw  measurements  extracted  from  a  slide
   Dat...
Looking for clinically relevant anomalies
Known  genes
  Look  for  genes  overlapping  with  detected  anomalies
  Find  ...
Building CNV tracks in copy number software
In-­‐house  CNV  track  
   Perform  copy  number  analysis  on  aCGH data  fr...
Using CNV tracks in Cytogenetic tests
Visualize  accumulated  CNV  information  during  routine  tests  
   Visualize  reg...
Cohorts of healthy individuals: the HapMap project
The  HapMap project
  The  International  HapMap Project  is  a  partne...
Building CNV frequencies across HapMap samples
A  large,  powerful  pool  of  data
  High-­‐density  information  provided...
Filtering HapMap CNV data
Control  group  may  produce  CNVs  that  are  clinically  relevant  
   HapMap sample  below  d...
CNV frequency profiles specific to sample attribute
Demographic  attributes  may  be  important  
  For  example:  11  dif...
Probe coverage issue
Different  array  platforms  may  produce  slightly  different  CNV  profiles  
                     ...
Other sources of high-quality CNV data
Other  studies
  CHOP:  High-­‐resolution  mapping  of  copy  number  variations  i...
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Large aCGH Datasets

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Transcript of "Large aCGH Datasets"

  1. 1. Collecting quantitative CNV information using aCGH in a Cytogenetic laboratory Anton Petrov, Ph.D. infoQuant December 2009
  2. 2. Overview Copy  number  analysis  of  array  CGH  data Overview  of  an  array-­‐based  Cytogenetic  test Looking  for  clinically  relevant  aberrations Samples  from  healthy  individuals  and  building  CNV  tracks Aberration  frequency  data HapMap project,  release  3:  Affymetrix SNP  6.0  data Population-­‐specific  CNV  profiles HapMap data:  11  populations Probe  coverage  issue CNV  profile  variation  from  one  array  platform  to  another
  3. 3. Array-based copy number tests: data analysis Data  pre-­‐processing Raw  measurements  extracted  from  a  slide Data  normalized  between  two  channels  (experiment/reference) Log-­‐ratio  measurements  built  and  arranged  along  genome Detection  of  copy  number  changes Detection  of  regions  where  log-­‐ratios  significantly  deviate  from  zero  (gains  and  losses) A  robust  binary  segmentation  approach  for  high-­‐res  data  in  infoQuant  software Reporting  of  detected  anomalies In  a  Cytogenetic  test  need  to  determine  clinical  relevance  of  detected  aberrations
  4. 4. Looking for clinically relevant anomalies Known  genes Look  for  genes  overlapping  with  detected  anomalies Find  genes,  associated  with  a  specific  class  of  disorders Known  CNVs Publicly  available  CNV  databases:  Database  of  Genomic  Variants  (Toronto) Lack  of  control  over  source Different  array  platforms  used In-­‐house  CNV  tracks  using  chosen  platform  
  5. 5. Building CNV tracks in copy number software In-­‐house  CNV  track   Perform  copy  number  analysis  on  aCGH data  from  individual  samples  (control  group) Collect  CNV  regions  for  a  cohort  of  control  samples  and  visualize  in  routine  Cyto tests Keep  updating  CNV  tracks  as  new  samples  get  analyzed   CNV  frequency  profile Compute  frequency  of  CNVs  along  genome  based  on  accumulated  samples Use  quantitative  information  that  CNV  frequencies  provide  to  interpret  relevance  of   detected  chromosomal  anomalies  in  newly  acquired  samples  
  6. 6. Using CNV tracks in Cytogenetic tests Visualize  accumulated  CNV  information  during  routine  tests   Visualize  regions  of  frequent  CNVs  when  reviewing  data  for  a  new  sample   to  determine  clinical  relevance  of  detected  anomalies Further  increase  insight  into  possible  clinical  relevance  of  a  detected   anomaly  using  quantitative  information  provided  by  CNV  frequencies
  7. 7. Cohorts of healthy individuals: the HapMap project The  HapMap project The  International  HapMap Project  is  a  partnership  of  scientists  and  funding  agencies     from  various  countries  www.hapmap.org The  goal  of  the  International  HapMap Project  is  to  compare  the  genetic  sequences  of   different  individuals  to  identify  chromosomal  regions  where  genetic  variants  are   shared Genetic  data  are  being  gathered  from  different  human  populations  >1000  samples  in   the  latest  release aCGH and  SNP  data  were  obtained  using  different  array  platforms  from  medium   resolution  to  high  resolution  to  ultra-­‐high  resolution  over  the  years
  8. 8. Building CNV frequencies across HapMap samples A  large,  powerful  pool  of  data High-­‐density  information  provided  by  Affymetrix SNP  6.0  arrays CNV  frequencies  across  HapMap samples  provide  a  useful  insight  into  how   frequently  a  certain  anomaly  may  be  observed  in  healthy  individuals Separate  gain  frequencies  and  loss  frequencies   Useful  addition  to  the  Database  of  Genomic  Variants  
  9. 9. Filtering HapMap CNV data Control  group  may  produce  CNVs  that  are  clinically  relevant   HapMap sample  below  demonstrates  a  large  copy  number  loss  confirmed  by   both  sets  of  measurements The  region  includes  cancer-­‐related  gene  NRAS Such  anomalies  need  to  be  isolated  using  copy  number  analysis  software Filter  CNVs  by  size When  computing  CNV  frequency  profiles  pre-­‐set  software  to  disregard  CNVs   larger  than  2Mbp,  for  instance    
  10. 10. CNV frequency profiles specific to sample attribute Demographic  attributes  may  be  important   For  example:  11  different  populations  in  HapMap Individual  CNV  frequency  plots  may  be  built  for  the  populations  by  aCGH software  and  used  in  Cytogenetic  tests  for  more  targeted  reference  
  11. 11. Probe coverage issue Different  array  platforms  may  produce  slightly  different  CNV  profiles   -­‐scale  and  complex  architecture  of  human  copy-­‐number   Affymetrix SNP  6.0  arrays  (HapMap release  3) Platforms  may  concentrate  their  probe  coverage  on  different  areas,  hence  different  CNV   profiles.  This  is  typical  for  performing  copy  number  analysis  across  array  platforms.
  12. 12. Other sources of high-quality CNV data Other  studies CHOP:  High-­‐resolution  mapping  of  copy  number  variations  in  2,026  healthy  individuals   http://cnv.chop.edu/ Wellcome Trust:  Ultra-­‐high  resolution  CNV  study.  42  M  probe  coverage,  custom  2.1  M   array  designs  based  on  Roche-­‐Nimblegen aCGH.   http://www.sanger.ac.uk/humgen/cnv/42mio/

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