Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
The use of BEDTools to analyze
CNV regions
Leandro Lima
CAG analytical meeting - Dec 10, 2014
Center for Applied Genomics
...
Motivation
• In genetics, many analyses are a subtype of
set theory or intervals arithmetic
• Examples:
1. Check coverage ...
The BEDTools suite
(some examples)
• intersect
The BEDTools suite
(some examples)
• cluster
The BEDTools suite
(some examples)
• merge
The BEDTools suite
(some examples)
• genomecov
Evolution of DGV
(Database of Genomic Variants)
• DGV is a curated catalogue of human genomic
structural variation
• The c...
Increase in Variation Data
Source: http://dgv.tcag.ca/dgv/app/statistics
Example 1 – Evolution of DGV
per year, by chromosome
• First, we have to select regions of the references with
year of pub...
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Increase in Variation Data
(by chromosome)
Example 2: find de novo CNVs
• Step 1: merge parents CNVs
• Step 2: get regions that do not overlap with
CNVs from child
Example 2: find de novo CNVs
• Merge parents CNVs
Example 2: find de novo CNVs
• intersect -v Child CNVs
Parents CNVs
inherited
de novo
Example 2: find de novo CNVs
• cluster (to find de novo CNVs that happen in
more than one family)
Example 3: find novel CNVs
• intersect -v De novo CNVs
DGV
previously
reported
novel (never reported)
Questions?
The use of BEDTools to analyze CNV regions
The use of BEDTools to analyze CNV regions
The use of BEDTools to analyze CNV regions
The use of BEDTools to analyze CNV regions
Upcoming SlideShare
Loading in …5
×

The use of BEDTools to analyze CNV regions

1,019 views

Published on

I show some examples of how to use BEDTools to solve different tasks realted to copy-number variation analysis.

Published in: Data & Analytics
  • Be the first to comment

  • Be the first to like this

The use of BEDTools to analyze CNV regions

  1. 1. The use of BEDTools to analyze CNV regions Leandro Lima CAG analytical meeting - Dec 10, 2014 Center for Applied Genomics The Children’s Hospital of Philadelphia
  2. 2. Motivation • In genetics, many analyses are a subtype of set theory or intervals arithmetic • Examples: 1. Check coverage in a genome / exome 2. Find de novo CNVs 3. Find novel CNVs in a database
  3. 3. The BEDTools suite (some examples) • intersect
  4. 4. The BEDTools suite (some examples) • cluster
  5. 5. The BEDTools suite (some examples) • merge
  6. 6. The BEDTools suite (some examples) • genomecov
  7. 7. Evolution of DGV (Database of Genomic Variants) • DGV is a curated catalogue of human genomic structural variation • The content of the database is only representing structural variation identified in healthy control samples • The Database of Genomic Variants provides a useful catalog of control data for studies aiming to correlate genomic variation with phenotypic data
  8. 8. Increase in Variation Data Source: http://dgv.tcag.ca/dgv/app/statistics
  9. 9. Example 1 – Evolution of DGV per year, by chromosome • First, we have to select regions of the references with year of publication less or equal to a specific year • Then, use bedtools genomecov to get the percentage of each chromosomes covered by the variant regions
  10. 10. Increase in Variation Data (by chromosome)
  11. 11. Increase in Variation Data (by chromosome)
  12. 12. Increase in Variation Data (by chromosome)
  13. 13. Increase in Variation Data (by chromosome)
  14. 14. Increase in Variation Data (by chromosome)
  15. 15. Increase in Variation Data (by chromosome)
  16. 16. Increase in Variation Data (by chromosome)
  17. 17. Increase in Variation Data (by chromosome)
  18. 18. Increase in Variation Data (by chromosome)
  19. 19. Increase in Variation Data (by chromosome)
  20. 20. Increase in Variation Data (by chromosome)
  21. 21. Increase in Variation Data (by chromosome)
  22. 22. Example 2: find de novo CNVs • Step 1: merge parents CNVs • Step 2: get regions that do not overlap with CNVs from child
  23. 23. Example 2: find de novo CNVs • Merge parents CNVs
  24. 24. Example 2: find de novo CNVs • intersect -v Child CNVs Parents CNVs inherited de novo
  25. 25. Example 2: find de novo CNVs • cluster (to find de novo CNVs that happen in more than one family)
  26. 26. Example 3: find novel CNVs • intersect -v De novo CNVs DGV previously reported novel (never reported)
  27. 27. Questions?

×