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CIBEC Presentation Fatma Sayed.pptx
- 1. Minia University Faculty of Engineering Biomedical Engineering Department Haplotype Block Partitioning for NARAC Dataset Using Interval Graph Modeling of Clusters Algorithm Authors: Fatma S. Ibrahim Mohamed N. Saad Ashraf M. Said Hesham F. A. Hamed
- 2. Background and introduction Literature Review Dataset and system overview Implementation and findings Conclusion 2
- 3. 3
- 4. 4
- 5. 5 (SNP) is a mutation at a single nucleotide position, where a possible nucleotide type is called an allele.
- 6. FGT MATILDE 2002 2008 CIT SSLD MIG++ 2002 2005 2014 S-MIG++ 2016 BigLD 2018 6
- 7. 7 7
- 8. Extracting Chromosome 21 from entire NARAC genomic dataset NARAC 22 chromosomes input files NARAC genomic data (2,062 individuals) Perl Choosing chromosome 21 under study Genotyped ch21 dataset Map file for ch21 NARAC map file (545,080 SNPs) R Chromosomes separated data Chromosomes separated map file 8
- 9. System description start NARAC genotype dataset ch21 NARAC map file Position ch21 Reformatting Data for codeGeno function Imputation of missing data Biomarker check Recoding to 0,1,2 Genotype format Processed Genotype data Applying Big-LD algorithm Haplotype blocks Plotting the heatmap Calculating the parameters of the blocks and make the comparison among methods 9
- 10. System description start NARAC genotype dataset ch21 NARAC map file Position ch21 Reformatting Data for codeGeno function Imputation of missing data Biomarker check Recoding to 0,1,2 Genotype format Processed Genotype data Applying Big-LD algorithm Haplotype blocks Plotting the heatmap Calculating the parameters of the blocks and make the comparison among methods BigLD SSLD CIT FGT 10
- 11. Implementation Haplotype block partitioning based on BigLD method 11
- 12. Blocks features and parameters Haplotype block portioning based on BigLD method Pre-processing phase 2 (recoding) Pre-processing phase 1 (reformatting) Reading and cropping The steps of haplotype block partitioning based on BigLD method 12
- 13. Heatmap for the haplotype blocks detected by interval graph modeling of clusters for a portion of chromosome 21 from 9,993,822 bp to 14,137,685 bp. 13
- 14. 1182 blocks 8051 SNPs 14 7787 SNPs after biomarker check
- 15. FGT CI SSLD BigLD Base-pair position Plot of a sample of chromosome 21 haplotype blocks produced by FGT, CIT, SSLD, and Big-LD. 15
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- 17. 17 • Big-LD method provided robust blocks partitioning in terms of the block size and genomic coverage. • Moreover, it produced the least total number of blocks compared to CIT, FGT, and SSLD. • Big-LD produces larger LD blocks compared to other existing methods 17
- 18. 18 • The results showed the similar intersections and inconsistencies among resulted blocks. • This analysis shows that Big-LD matched more with FGT and produced much more stable large haplotype blocks for NARAC dataset 18
Editor's Notes
- I've organized my talk into eight topics shown here.
- SNP: single base mutation in DNA
- Therefore, Haplotype block partitioning is important for population genetics, association analysis, and genetic epidemiology
- This research provided an empirical comparison of haplotype blocks partitioned by four different methods for chromosome 21 of the NARAC dataset The proposed analysis demonstrated the differences and similarities among the most common four methods of haplotype partitioning. This analysis shows that Big-LD matched more with FGT and produced much more stable large haplotype blocks for NARAC dataset