Assembling genomes using ABySS
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ABySS is a genome assembler that uses de Bruijn graphs and operates in two stages: the first stage generates contigs from the reads using de Bruijn graphs and techniques like pruning tips and popping bubbles, while the second stage scaffolds the contigs using paired-end information and algorithms to align reads, estimate distances, find consistent paths, and merge contigs. The document provides details on each step of ABySS and shows that it can assemble half a genome into large contigs from short reads in a distributed computing environment.
Assembling genomes using ABySS
- 1. Assembling genomes using ABySS dnGASP 2011 Shaun Jackman BC Genome Sciences Centre sjackman@bcgsc.ca abyss-users@bcgsc.ca
- 2. An assembly in two stages ● Stage I: Sequence assembly algorithm ● Stage II: Paired-end assembly algorithm 2
- 3. Stage 1 Sequence assembly algorithm ● Load the reads, Load k-mers breaking each read into k-mers ● Find adjacent k-mers, which Find overlaps overlap by k-1 bases ● Remove k-mers resulting from Prune tips read errors ● Remove variant sequences Pop bubbles ● Generate contigs Generate contigs 3
- 4. Load the reads ● For each input read of length l, (l - k + 1) k-mers are generated by sliding a window of length k over the read Read (l = 12): ● Each k-mer is a vertex of ATCATACATGAT the de Bruijn graph k-mers (k = 9): ATCATACAT ●Two adjacent k-mers are TCATACATG an edge of the de Bruijn CATACATGA ATACATGAT graph 4
- 5. De Bruijn Graph ● A simple graph for k = 5 ● Two reads – GGACATC – GGACAGA GACAT ACATC GGACA GACAG ACAGA 5
- 6. Pruning tips ● Read errors cause tips 6
- 7. Pruning tips ● Read errors cause tips ● Pruning tips removes the erroneous reads from the assembly 7
- 8. Popping bubbles ● Variant sequences cause bubbles ● Popping bubbles removes the variant sequence from the assembly ● Repeat sequences with small differences also cause bubbles 8
- 9. Assemble contigs ● Remove ambiguous edges ● Output contigs in FASTA format 9
- 10. Paired-end assembly algorithm Stage 2 ● Align the reads to the contigs of the first stage ● Generate an empirical fragment-size distribution using the paired reads that align to the same contig ● Estimate the distance between contigs using the paired reads that align to different contigs 10
- 11. Align the reads to the contigs KAligner ● Every k-mer in the single-end assembly is unique ● KAligner can map reads with k consecutive correct bases ● ABySS may use other aligners, including BWA and bowtie 11
- 12. Empirical fragment-size distribution ParseAligns ● Generate an empirical fragment-size distribution using the paired reads that align to the same contig 12
- 13. Estimate distances between contigs DistanceEst ● Estimate the distance between contigs using the paired reads that align to different contigs d = 25 ± 8 d=3±5 d=6±5 d=4±3 13
- 14. Maximum likelihood estimator DistanceEst ● Use the empirical paired- end size distribution ● Maximize the likelihood function ● Find the most likely distance between the two contigs 14
- 15. Paired-end algorithm continued... ● Find paths through the contig adjacency graph that agree with Generate paths the distance estimates ● Merge overlapping paths Merge paths ● Merge the contigs in these paths Generate contigs and output the FASTA file 15
- 16. Find consistent paths SimpleGraph ● Find paths through the contig adjacency graph that agree with the distance estimates d=4±3 Actual distance = 3 16
- 17. Merge overlapping paths MergePaths ● Merge paths that overlap 17
- 18. Generate the FASTA output ● Merge the contigs in these paths. ● Output the FASTA file GATTTTTG GAC GTCTTGATCTT CAC GTATTG CTATT 18
- 19. Assembly process ● Stage 1 completed in 3.5 hours ● Used 72 processors on six machines ● Peak memory usage of 180 GB of RAM ● Stage 2 completed in 9 hours ● Used 12 processors on one machine ● Peak memory usage of 48 GB of RAM ● Assembly parameters k=64 s=200 n=10 19
- 20. Assembly results Level 1: 500-bp paired-end reads ● Assembled half the genome in 7,676 contigs larger than the N50 of 50,612 bp ● Assembled 1.81 Gbp in 170,407 contigs larger than 200 bp ● The largest contig is 1,158,576 bp ● Removed 1,296,819 variant sequences 20
- 21. Alignments to the reference ● Aligned the 170,407 contigs longer than 200 bp ● 96.2% align at least 99% length ● 1.2% align between 90% and 99% length ● 2.5% align less than 90% length >99% 90-99% <90% 21
- 22. Works in progress ● Replace complex variant sequences with Ns ● Scaffold over gaps and simple repeat sequence using large fragment mate-pair reads ● Filling in gaps with sequence using localized microassembly 22
- 23. ABySS Publications IEEE InfoVis 2009
- 24. Acknowledgments Supervisors ● İnanç Birol ● Steven Jones Team ● Readman Chiu ● Rod Docking ● Karen Mungall ● Jenny Qian 24
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