This document summarizes a study analyzing copy number variation (CNV) from a bioinformatics approach to identify genes associated with familial pancreatic cancer (FPC). The study identified CNVs in FPC cases and controls to find regions of inactivation or overexpression. The researcher assisted with data mining and analysis tools. Regions were compared between FPC cases and databases/controls to find overlapping and non-overlapping regions. Genes coinciding with FPC CNV regions were identified. Ongoing work involves annotating interesting genes and prioritizing them based on relevance to FPC.

1. Analyzing Copy Number
Variation from a
Bioinformatics Approach
July 24th, 2009
by Gagandeep Singh Anand
ganand@uwaterloo.ca

2. General Overview - Study
The Study:
• Identify and Annotate germline genomic alterations that
predispose to familial pancreatic cancer (FPC)
• Determine: functionally inactivated / over-expressed genes in pancreatic
adenocarcinoma tumours
• Considered as candidate tumour suppressor or oncogenic genes in FPC
• By finding copy number variation (variability in copy [>2
or <2] of DNA regions) in FPC Case vs. Controls to find
“interesting” regions of inactivation / over expression
My Contributions:
• Assist with data mining and pipelining – a technique to
find “interesting” genes
• Make data analysis a more efficient process with the aid
of numerous programming languages and bioinformatics
tools

3. General Overview - Bioinformatics
• Compare the Database of Genomic Variants (+ our
Controls) with our FPC CNV regions – find overlaps/non-
overlaps.
• Compare all regions (i.e. Somatic CNVs, miRNAs,
Hypo/Methylated regions) from other papers – also
based on pancreatic adenocarcinoma – with our FPC
Cases.
• Determine all the Genes coinciding with our FPC CNV
regions

4. DGV + our Controls vs. FPC Cases...
Overlap of FPC CNVs vs. All Controls:
565 FPC gain CNVs /
235 FPC deleted CNVs coinciding with any control
Non-overlap of FPC CNVs vs. All Controls:
240 FPC gain CNVs /
55 FPC deleted CNVs not overlapping with controls
FPC
Amplifications
(631)
FPC Deletions
(266)
DGV + Controls
(25700)

5. ...DGV + our Controls vs. FPC Cases
Database of Genomic Variants (DGV) Tracks:
• Using the DGV - Genomic Browser, we can view tracks
(list of sequence annotations) on the same page:
• FPC Case CNVs as well as all (DGV + our controls)
control regions
• CNV Non-Overlaps with all (DGV + our controls)
control regions
• This gives us the ability to visualize a multitude of
different annotations on the same page
• For example…

6. Somatic CNVs, miRNA's &
Methylated regions vs. FPC CNVs
• Analyzed 12 different papers containing 1265 (27
hypo/methylated, 12 miRNA’s, 1233 somatic PC CNVs)
interesting regions (regions that had high affinity in
pancreatic adenocarcinoma cases)
• Observed 63 FPC deleted CNVs overlapping with other
regions (somatic CNVs, miRNA's or Methylated regions)
• Observed 240 FPC gain CNVs overlapping with other
regions (somatic CNVs, miRNA's or Methylated regions)
• Ongoing, as we search for more papers

7. Annotate FPC Regions with Standard
Gene IDs
• Get a list of genes that coincide with a set of CNVs /
Controls
• Get a list of CNVs / Controls that coincide with a set
of genes
Ensembl ID Entrez
ID
Chr. Gene
Start
Gene End Known Gene
Aliases
# of
CNVs
CNV Names
ENSG00000005
206
56928 19 2279629 2306099 AC004410.1 3 G_247,G_281,
G_177
ENSG00000005
844
16 30391572 30442006 ITGAL 2 G_171,G_241
Temp_ID Chr. Case Start Case End Case Size # of
Genes
Ensembl Gene
Names (Gene
Alias)
G_151 14 106223861 106246130 22270 2 ENSG0000021937
3 (IGHV1-68),…
G_152 7 61718176 62343621 625446 2 ENSG0000019923
1 (snoU2_19),…

8. Annotate FPC Regions with Standard
Gene IDs
• Next we would like to annotate "interesting" genes in
detail and prioritize them based on their relevance to
FPC – I hope to automate this pipeline!
• Previously, we determined regions of non-overlaps
based on regions of overlapping CNVs vs. Controls
• Now, using a variety of genome browsers, we find the
genes that coincide with our FPC CNVs and Our
Controls then find the set of disjoint genes
Only FPC AMP
Genes (1864)
Only FPC Del
Genes (84)
Only CTRL
AMP Genes
(14272)
Only CTRL DEL
Genes (1257)
Genes in
FPC &
CTRL AMPs
(1678)
Genes in
FPC &
CTRL DELs
(428)

9. Thank you for listening…
Acknowledgements: Dr. Wigdan Al-Sukhni