Mining GWAS Catalog & 1000 Genomes Dataset. Segun Fatumo

Size: px

Start display at page:

Download "Mining GWAS Catalog & 1000 Genomes Dataset. Segun Fatumo"

Hilary Webster
6 years ago
Views:

1 Mining GWAS Catalog & 1000 Genomes Dataset Segun Fatumo

2 What is GWAS Catalog NHGRI GWA Catalog

3 Citation How to cite the NHGRI GWAS Catalog: Hindorff LA, MacArthur J (European Bioinformatics Institute), Morales J (European Bioinformatics Institute), Junkins HA, Hall PN, Klemm AK, and Manolio TA. A Catalog of Published Genome-Wide Association Studies. Available at: Accessed [date of access]. How to cite the NHGRI GWAS Catalog paper: Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, Klemm A, Flicek P, Manolio T, Hindorff L, and Parkinson H. The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Research, 2014, Vol. 42 (Database issue): D1001-D1006.

4 Class Exercise Download the NGHRI GWAS catalog In tab delimited format to your Linux system What is the number of columns on your downloaded gwas catalog What is the header on column 28? Using a spreadsheet (Ms Excel) Extract All SNPs that have been found to be associated with HDL Cholesterol BMI Your trait of interest Print only columns 2,8,30,24,22 and 28 in this order. Extract only where p-value is 5 X 10^-8 Count the number of SNPs found for each traits. Report only the unique SNPs. Hint: Use your knowledge of SQL, Bash scripting, python. If you cant get your way around this, we do solve it together.

5 1000 Genomes

6 Glossary Pilot: The 1000 Genomes project ran a pilot study between 2008 and 2010 Phase 1: The initial round of exome and low coverage sequencing of 1000 individuals Phase 2: Expanded sequencing of 1700 individuals and method improvement Phase 3: Sequencing of 2500 individuals and a new variation catalogue SAM/BAM: Sequence Alignment/Map Format, an alignment format VCF: Variant Call Format, a variant format 6

7 The 1000 Genomes Project: Overview International project to construct a foundational data set for human genetics Discover virtually all common human variations by investigating many genomes at the base pair level Consortium with multiple centers, platforms, funders Aims Discover population level human genetic variations of all types (95% of variation > 1% frequency) Define haplotype structure in the human genome Develop sequence analysis methods, tools, and other reagents that can be transferred to other sequencing projects 7

8 Phase 1 populations EUROPE CEU A. 85 B. All LCL C. 45m/40f D. 78t/3d/4s IBS A. 14 B. All LCL C. 7m/7f D. 14t GBR A. 89 B. All LCL C. 41m/48f D. 3d/86s FIN A. 93 B. All LCL C. 35m/58f D. 93s TSI A. 98 B. All LCL C. 50m/48f D. 98s AMERICAS MXL A. 66 B. All LCL C. 31m/35f D. 59t/3d/4s Utah, USA Los Angeles, USA Southwest, USA Finland Great Britain Spain Italy Beijing, China Hu Nan and Fu Jian Provinces, China Tokyo, Japan EAST ASIA JPT A. 89 B. All LCL C. 50m/39f D. 89s PUR A. 55 B. 35bld/20LCL C. 28m/27f D. 47t/8d CLM A. 60 B. All LCL C. 29m/31f D. 55t/5d New 1000 Genomes Puerto Rico Medellín, Colombia ASW A. 61 B. All LCL C. 24m/37f D. 28t/22d/11s Ibadan, Nigeria YRI A. 88 B. All LCL C. 43m/45f D. 65t/21d/2s Webuye, Kenya LWK A. 97 B. All LCL C. 48m/49f D. 4d/93s CHB A. 97 B. All LCL C. 44m/53f D. 97s CHS A. 100 B. All LCL C. 50m/50f D. 100t HapMap 3 AFRICA 8 Figure S Genomes Project Phase I populations Populations collected as part of the HapMap project (blue) and the 1000 Genomes Project (green) include: Europe (IBS (Iberian populations in Spain), GBR (British from England and Scotland ), CEU

9 Phase 2/3 populations Barbados Ghana Pakistan Peru Nigeria India Bangladesh Sierra Leone Sri Lanka USA Vietnam 9

10 Hapmap, The Pilot Project and The Main Hapmap Starting in 2002 Last release contained ~3m snps 1400 individuals 11 populations High Throughput genotyping chips 10 Project 1000 Genomes Pilot project Started in 2008 Paper release contained ~14 million snps 179 individuals 4 populations Low coverage next generation sequencing 1000 Genomes Phase 1 Started in 2009 Phase 1 release has 36.6millon snps, 3.8millon indels and 14K deletions 1094 individuals 14 populations Low coverage and exome next generation sequencing 1000 Genomes Phase 2 Started in individuals 19 Populations Low coverage and exome next generation sequencing

11 Timeline September 2007: 1000 Genomes project formally proposed Cambridge, UK April 2008: First Submission of Data to the Short Read Archive. May 2008: First public data release. October 2008: SAM/BAM Format Defined. December 2008: First High Coverage Variants Released. December 2008: First 1000 genomes browser released May 2009: First Indel Calls released. July 2009: VCF Format defined August 2009: First Large Scale Deletions released. December 2009: First Main Project Sequence Data Released. March 2010: Low Coverage Pilot Variant Release made July 2010: Phased genotypes for 159 Individuals released. October 2010: A Map of Human Variation from population scale sequencing is published in Nature. January 2011: Final Phase 1 Low coverage alignments are released May appears on Twitter May 2011: First Variant Release made on more than 1000 individuals October 2011: Phase 1 integrated variant release made March 2012: Phase 2 Alignment release November 2012: An integrated map of genetic variation from 11 1,092 human genomes in Nature

12 Fraction of variant sites present in an individual that are NOT already represented in dbsnp Date Fraction not in dbsnp February, % February, % April, % February, % Now <1% Ryan Poplin, David Altshuler

13 Data Availability FTP site: ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/ Raw Data Files Web site: Release Announcements Documentation Ensembl Style Browser: Browse 1000 Genomes variants in Genomic Context Variant Effect Predictor Data Slicer Other Tools 13

14 The 1000 Genomes Project data Data are available through: The 1000 Genomes website: NCBI: ftp://ftptrace.ncbi.nlm.nih.gov/1000genomes EBI: ftp://ftp.1000genomes.ebi.ac.uk Amazon:

15 Command Line Tools Samtools VCFTools Tabix (Please note it is best to use the trunk svn code for this as the release has a bug) svn co 15

16 Fastq files Sequence HS18_6628:8:1108:8213:186084#2/1 GGTTAGGGTTAGGGTTAGGGTTAGGGTTAGGGTTAGG + DCDHKHKKIJGNNHIJIIKLLMCLKMAILIJH3K>HL1I=>MK.D 16

17 BAM files Alignment Data ERR M = NAME DESCRIPTION 17 QNAME FLAG RNAME POS MAPQ CIGAR MRNM MPOS ISIZE SEQ QUAL Query NAME of the read or read pair Bitwise FLAG (pairing, strand, mate strand etc Reference Sequence NAME 1-Based leftmost POSition of clipped alignment MAPping Quality (Phred-scaled) Extended CIGAR string (operations: MIDNSHP) Mate Reference NaMe ( = if same as RNAME) 1-Based leftmost Mate POSition Inferred Insert SIZE Query SEQuence on the same strand as the reference Query QUALity (ASCII-33=Phred base quality)

18 More Information About BAM Files 18

19 VCF Files Variant Call Data TAB Delimited Text Format NAME CHROM POS ID REF ALT QUAL FILTER INFO FORMAT DESCRIPTION Chromosome name Position in chromosome Unique Identifer of variant Reference Allele Alternative Allele Phred scaled quality value Site filter information User extensible annotation Describes the format of the subsequent fields, must always contain Genotype Individual Genotype 19 Fields These columns contain the individual genotype data for each individual in the file

20 Variant Call Data Headers ##fileformat=vcfv4.1 ##INFO=<ID=RSQ,Number=1,Type=Float,Description="Genotype imputation quality from MaCH/Thunder"> ##INFO=<ID=AC,Number=.,Type=Integer,Description="Alternate Allele Count"> ##INFO=<ID=AN,Number=1,Type=Integer,Description="Total Allele Count"> ##INFO=<ID=AA,Number=1,Type=String,Description="Ancestral Allele, ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/reference/ancestral_alignmen ts/readme"> ##INFO=<ID=AF,Number=1,Type=Float,Description="Global Allele Frequency based on AC/AN > ##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype"> ##FORMAT=<ID=DS,Number=1,Type=Float,Description="Genotype dosage from MaCH/Thunder"> ##FORMAT=<ID=GL,Number=.,Type=Float,Description="Genotype Likelihoods"> 20

21 Variant Call Data Example 1000 Genomes Data CHROM 4 POS ID rs REF T ALT C QUAL 100 FILTER PASS INFO AA=T;AN=2184;AC=1;RSQ=0.8138;AF=0.0005; FORMAT GT:DS:GL GENOTYPE 0 0:0.000:-0.03,-1.19,

22 More Information About VCF Files VCF variant files All indexed for fast retrieval

23 Class Exercise Download from 1000 Genomes the vcf data for a gene of interest. If you don t have a gene of interest, look for a gene in GWAS catalog that is associated with a Lipid traits eg PCSK9 Extract the genotype of same gene for only European population Convert your vcf genotype data to a plink format (ped & map) Hint : You will need to know the chr and location of the gene before you can download it

24 Data Slicing All alignment and variant files are indexed so subsections can be downloaded remotely Use samtools to get subsections of bam files samtools view ment/hg01375.mapped.illumina.bwa.clm.low_coverage bam 6: Use tabix to get subsections of vcf files tabix -h ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/working/ _omni_genotypes_and_intensities/Omni25_genotypes_ 2141_samples.b37.vcf.gz 6: You can also use the web Data Slicer interface to do this 24

25 Data Slicing VCFtools provides some useful additional functionality on the command line including: vcf-compare, comparision and stats about two or more vcf files vcf-isec, creates an intersection of two or more vcf files vcf-subset, will subset a vcf file only retaining the specified individual columns vcf-validator, will validate a particular 25

Data Slicing http://browser.1000genomes.org/tools.

26 Data Slicing ata/selectslice

27 Variant Effect Predictor Predicts Functional Consequences of Variants Both Web Front end and API script Can provide sift/polyphen/condel consequences Refseq gene names HGVS output Can run from a cache as well as Database Convert from one input format to another Script available for download from: ftp://ftp.ensembl.org/pub/misc-scripts/variant_effect_predictor/ Variations 27

29 Variant Effect Predictor perl variant_effect_predictor.pl -input 6_ _ vcf -sift p -polyphen p check_existing less variant_effect_output.txt #Uploaded_variation Location Allele Gene Feature Feature_type Consequence cdna_position CDS_position Protein_position Amino_acids Codons Exi sting_variation Extra rs : A ENSG ENST Transcript DOWNSTREAM rs rs : A ENSG ENST Transcript INTRONIC rs _ _c/t 6: T ENSG ENST Transcript NON_SYNONYMOUS_CODING R/H cgc/cac - PolyPhen=possibly_damaging;SIFT=deleterious 29

30 VCF to PED LD Visualization tools like Haploview require PED files VCF to PED converts VCF to PED Will a file divide by individual or population ens/userdata/haploview 30

31 31 VCF to PED

32 VCF to PED perl vcf_to_ped_convert.pl -vcf ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/ /all.chr6.pha se1_integrated_calls snps_indels_svs.genotypes.vcf.gz - sample_panel_file ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/ /phase1_inte grated_calls all.panel -region 6: population CEU Output should be two files 6_ info 6_ ped 32

33 Access to backend Ensembl databases Public MySQL database at mysql-db.1000genomes.org port 4272 Full programmatic access with Ensembl API The 1000 Genomes Pilot uses Ensembl v60 databases and the NCBI36 assembly (this is frozen) The 1000 Genomes main project currently uses Ensembl v63 databases n/index.html ml

34 Announcements genomes-annoucement-mailing-list ts/rss.xml 34

Genome variation - part 1

Genome variation - part 1 Dr Jason Wong Prince of Wales Clinical School Introductory bioinformatics for human genomics workshop, UNSW Day 2 Friday 21 th January 2016 Aims of the session Introduce major