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10 Billion Piece Jigsaw Puzzles John Cleary Netvalue Ltd. Real Time Genomics.

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Presentation on theme: "10 Billion Piece Jigsaw Puzzles John Cleary Netvalue Ltd. Real Time Genomics."— Presentation transcript:

1 10 Billion Piece Jigsaw Puzzles John Cleary Netvalue Ltd. Real Time Genomics

2

3 million 100 thousand 10 thousand 10 million 100 million billion 10 billion 100 billion thousand hundred

4 Genome Transcriptome Cancer

5 Genomes of … human reference species mouse, chimp, arabidopsis… agricultural species cattle, sheep, pig, … rice, wheat, grape … bacterial disease, human “ecosystem”

6 Differences between … Individuals Populations disease and “quantitative traits” Somatic and tumor genomes Transcriptome of child and parents Bacterial populations of individuals

7 Human Genome 3 billion Nucleotides

8 Shapes of the Jigsaw Pieces CompanyLengths (nt) Illumina Complete Genomics36 Ion Torrentupto 200 Oxford Nanopore(?)upto 50,000 Pacific Biosciences100*

9 Differences between genomes - SNPs A C G T T A G T G A A C G T T C G T G A A C G T T G G T G A ~ 1 / 1,000 3,000,000 nt

10 REF: aatgttttctcagaatgtggagaaccttggtgcggacgatgcgcaat_atagggtgggtaccgtccggatac_gctgc______aat______ctgcaatgggaacgacatgatacaatcctgacgggcggtatagaggttctgttgcgtagttagtgttcgtgctgg SIM: T AAGAAT CALL: T G CALL: T T READ: ATGTTTTCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GC READ: TTCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AA READ: TCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG READ: CTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______A READ: AATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______AATAAT READ: ATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AA-______GAATAATC READ: ATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______AATAATC READ: GGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCA READ: GGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCA READ: TGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAAT READ: GAACCTTGGTGCGGACGATGCGCAATTATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAAT READ: AACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGG READ: CTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAA READ: CTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAA READ: TGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACA READ: TGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAAT READ: GCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATC READ: CAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTG READ: _ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGG READ: TAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGG READ: GGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCG READ: TGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTA READ: GGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTAT READ: GTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAG READ: TACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGA READ: CGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGT READ: TTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTT READ: CGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTG READ: TGCAAGAAT______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGT READ: AC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCG READ: AT______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGTTAGTGTT READ: ______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGTTAGTGTTCG

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12 Differences between human genomes - MNPs A C G T T A G T G A A C G T T C A G A A C G T T G T G A

13 Differences between human genomes - indels A C G T T A G T G A A C G T T G T G A A C G T T G G T G A ~ 1 / 10, ,000

14 Differences between genomes - inserts A C G T T A G T G A Up to 1,000,000 nt total 3,000,000 nt T T A G G A C C C A

15 Differences between genomes – structural variants Tandem Repeat Inversion Copy

16 Solving the Jigsaw Indexing Alignment SNP/MNP/Indel/SV calling Mapping

17 Indexing A C G T T A G T G A A G A C G T T C G T G A A G A C G T T C G T G A A G A C G T T A G T G A A G 4.5 billion

18 Aligning A C G T T A G T G A A G A C G T T C G T G A A G 1.6 billion

19 Cutting Edge Run Human genome (3 billion nt) 1 billion reads of 100 nt coverage of 30 Indexing + Aligning in 27 minutes

20 i7 Quad Core

21 2 sockets X 4 cores X 2 hyperthreads = GB RAM 10 computers 1 TB disk/genome = 500GB + 200GB + 200GB + 0.3GB X thousands of genomes

22 Shapes of the Jigsaw Pieces CompanyLengths (nt) Illumina Complete Genomics36 Ion Torrentupto 200 Oxford Nanopore(?)upto 50,000 Pacific Biosciences100*

23 Paired End Reads 100 nt ,000 nt Index Align Index Align Match 100 nt

24 Solving the Jigsaw without the picture Indexing Alignment Assembly

25 T A G T G A A G A A T T A C G T T C G T G A A G A C G T T C G T G A A G T A G T G A A G A A T T A C G T T ? G T G A A G A A T T

26 SNP calling 15A13CAC heterozygous SNP 15A4C 5A2C 1A2C Bayesian statistics (SNPs 1/1,000) 31A42C Throw it out

27 REF: aatgttttctcagaatgtggagaaccttggtgcggacgatgcgcaat_atagggtgggtaccgtccggatac_gctgc______aat______ctgcaatgggaacgacatgatacaatcctgacgggcggtatagaggttctgttgcgtagttagtgttcgtgctgg SIM: T AAGAAT CALL: T G CALL: T T READ: ATGTTTTCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GC READ: TTCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AA READ: TCTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG READ: CTCAGAATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______A READ: AATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______AATAAT READ: ATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AA-______GAATAATC READ: ATGTGGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAG______AATAATC READ: GGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCA READ: GGTGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCA READ: TGAACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAAT READ: GAACCTTGGTGCGGACGATGCGCAATTATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAAT READ: AACCTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGG READ: CTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAA READ: CTTGGTGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAA READ: TGCGGACGATGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACA READ: TGCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAAT READ: GCGCAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATC READ: CAAT_ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTG READ: _ATAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGG READ: TAGGGTGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGG READ: GGGTGGGTACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCG READ: TGGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTA READ: GGGTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTAT READ: GTACCGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAG READ: TACCGTCCGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGA READ: CGTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGT READ: TTCCGGATAC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTT READ: CGGATAC_GCTGCAAGAATAAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTG READ: TGCAAGAAT______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGT READ: AC_GCTGC______AAGAATAATCTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCG READ: AT______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGTTAGTGTT READ: ______AAT______CTGCAATGGGAACGACATGATACAATCCTGACGGGCGGTATAGAGGTTCTGTTGCGTAGTTAGTGTTCG

28 Comparing twins 3,000,000 SNPs Do any of them differ between the twins? 15A 4C 3A 10C 3G

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30 DNA mRNA protein Gene

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32 Cancer comparison

33 Copy Number Variants Varying levels of extraction of reads across genome (use differences) Locate boundaries (as accurately as possible) Extract number of variants Use SNPs

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36 Metagenomics or what is living on you Mapping reads back onto a database of known bacteria/viruses Many are ambiguous Many don’t map at all Estimate frequency of each species Remove human “contamination”

37 TS gi| |ref|NC_ | Bacteroides thetaiotaomicron VPI-5482 plasmid p gi| |ref|NC_ | Akkermansia muciniphila ATCC BAA gi| |ref|NC_ | Bacteroides vulgatus ATCC gi| |ref|NC_ | Bifidobacterium adolescentis ATCC TS gi| |ref|NC_ | Bacteroides thetaiotaomicron VPI-5482 plasmid p gi| |ref|NC_ | Bacteroides vulgatus ATCC gi| |ref|NC_ |Bacteroides fragilis NCTC 9343 plasmid pBF gi| |ref|NC_ |Campylobacter jejuni subsp. jejuni plasmid pTet gi| |ref|NC_ |Eubacterium rectale ATCC TS gi| |ref|NC_ | Bacteroides thetaiotaomicron VPI-5482 plasmid p gi| |ref|NC_ | Bacteroides vulgatus ATCC gi| |ref|NC_ |Campylobacter jejuni subsp. jejuni plasmid pTet gi| |ref|NC_ |Bifidobacterium longum NCC gi| |ref|NC_ |Bifidobacterium longum DJO10A

38 Metagenomics Map reads to database Estimate most likely frequencies a hill climbing estimation problem Can anything be done about unmapped reads?

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