Summary
Summary {data-width=650}
Manhattan plot
manhattan_plot
QQ plot
qq_plot
AF plot
af_plot
P-Z plot
pz_plot
beta_std plot
beta_std_plot
Metadata
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"file_date": "2019-10-26T21:50:13.415067",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006696/EBI-a-GCST006696_data.json --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/hg38/hg38.fa; 1.1.1",
"reference": "file:/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/b37/human_g1k_v37.fasta",
"bcftools_annotateVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
"bcftools_annotateCommand": "annotate -a /mnt/storage/home/gh13047/mr-eve/vcf-reference-datasets/dbsnp/dbsnp.v153.b37.vcf.gz -c ID -o /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006696/EBI-a-GCST006696.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006696/EBI-a-GCST006696_data.vcf.gz; Date=Sat Oct 26 22:11:07 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006696/ebi-a-GCST006696.vcf.gz; Date=Sun May 10 00:49:30 2020"
}
LDSC
*********************************************************************
* LD Score Regression (LDSC)
* Version 1.0.1
* (C) 2014-2019 Brendan Bulik-Sullivan and Hilary Finucane
* Broad Institute of MIT and Harvard / MIT Department of Mathematics
* GNU General Public License v3
*********************************************************************
Call:
./ldsc.py \
--h2 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006696/EBI-a-GCST006696.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006696/ldsc.txt \
--snplist /data/ref/snplist.gz \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Sat Oct 26 22:36:28 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006696/EBI-a-GCST006696.vcf.gz ...
and extracting SNPs specified in /data/ref/snplist.gz ...
Traceback (most recent call last):
File "./ldsc/ldsc.py", line 647, in <module>
sumstats.estimate_h2(args, log)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
args, log, args.h2)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 246, in _read_ld_sumstats
sumstats = _read_sumstats(args, log, fh, alleles=alleles, dropna=dropna)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 165, in _read_sumstats
sumstats = ps.sumstats(fh, alleles=alleles, dropna=dropna, slh=args.snplist)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 85, in sumstats
x = read_vcf(fh, alleles, slh)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 161, in read_vcf
with gzip.open(slh) as f:
File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 34, in open
return GzipFile(filename, mode, compresslevel)
File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 94, in __init__
fileobj = self.myfileobj = __builtin__.open(filename, mode or 'rb')
IOError: [Errno 2] No such file or directory: '/data/ref/snplist.gz'
Analysis finished at Sat Oct 26 22:37:44 2019
Total time elapsed: 1.0m:16.65sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9528,
"inflation_factor": 1.1474,
"mean_EFFECT": -0,
"n": "-Inf",
"n_snps": 11490493,
"n_clumped_hits": 4,
"n_p_sig": 174,
"n_mono": 0,
"n_ns": 2134,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 571861,
"n_est": "NA",
"ratio_se_n": "NA",
"mean_diff": "NaN",
"ratio_diff": "NaN",
"sd_y_est1": "NaN",
"sd_y_est2": "NA",
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": "NA",
"ldsc_nsnp_merge_regression_ld": "NA",
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": "NA",
"ldsc_intercept_se": "NA",
"ldsc_lambda_gc": "NA",
"ldsc_mean_chisq": "NA",
"ldsc_ratio": "NA"
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | TRUE |
| n_p_sig | FALSE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | TRUE |
| ldsc_intercept_beta | TRUE |
| n_clumped_hits | FALSE |
| r2_sum1 | FALSE |
| r2_sum2 | FALSE |
| r2_sum3 | FALSE |
| r2_sum4 | FALSE |
Definitions
General metrics
af_correlation: Correlation coefficient betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.n: Maximum value of reported sample size across all SNPs, \(n\).n_clumped_hits: Number of clumped hits.n_snps: Number of SNPsn_p_sig: Number of SNPs with pvalue below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations for<*>column.
se_n metrics
n_est: Estimated sample size value, \(\widehat{n}\).ratio_se_n: \(\texttt{ratio_se_n} = \frac{\sqrt{\widehat{n}}}{\sqrt{n}}\). We expectratio_se_nto be 1. When it is not 1, it implies that the trait did not have a variance of 1, the reported sample size is wrong, or that the SNP-level effective sample sizes differ markedly from the reported sample size.mean_diff: \(\texttt{mean_diff} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta_j}{\texttt{n_snps}}\), mean difference between the standardised beta, predicted from P-values, and the observed beta. The difference should be very close to zero if trait has a variance of 1.- \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
- \({z}_j = \frac{\beta_j}{{se}_j}\),
- and \(\beta_j\) is the reported effect size.
ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean ofdiffand the mean ofdiff2(expected difference between the standardised beta predicted from P-values, and the standardised beta derived from the observed beta divided by the predicted SD; NOT reported). The ratio should be close to 1. If different from 1, then implies that the betas are not in a standard deviation scale.- \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
- \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
sd_y_est1: The standard deviation for the trait inferred from the reported sample size, median standard errors for the SNP-trait assocations and SNP variances.- \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
- \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
- and \({se}_j\) is the reported standard error.
sd_y_est2: The standard deviation for the trait inferred from the reported sample size, Z statistics for the SNP-trait effects (beta/se) and allele frequency.- \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
- \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).2: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var2}}}\), \(\texttt{var2} = {\widehat{\texttt{sd1}}_{y}}^2\),3: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var3}}}\), \(\texttt{var3} = {\widehat{\texttt{sd2}}_{y}}^2\),4: \(r^2 = \sum_j{\frac{F_j}{F_j + n - 2}}\), \(F = \frac{\beta_j^2}{{se}_j^2}\).
LDSC metrics
Metrics from LD regression
ldsc_nsnp_merge_refpanel_ld: Number of remaining SNPs after merging with reference panel LD.ldsc_nsnp_merge_regression_ld: Number of remaining SNPs after merging with regression SNP LD.ldsc_observed_scale_h2_{beta,se}Coefficient value and SE for total observed scale h2.ldsc_intercept_{beta,se}: Coefficient value and SE for intercept. Intercept is expected to be 1.ldsc_lambda_gc: Lambda GC statistics.ldsc_mean_chisq: Mean \(\chi^2\) statistics.ldsc_ratio: \(\frac{\texttt{ldsc_intercept_beta} - 1}{\texttt{ldsc_mean_chisq} - 1}\), the proportion of the inflation in the mean \(\chi^2\) that the LD Score regression intercepts ascribes to causes other than polygenic heritability. The value of ratio should be close to zero, though in practice values of 0.1-0.2 are not uncommon, probably due to sample/reference LD Score mismatch or model misspecification (e.g., low LD variants have slightly higher \(h^2\) per SNP).
Flags
When a metric needs attention, the flag should return TRUE.
af_correlation:abs(af_correlation)< 0.7.inflation_factor:inflation_factor> 1.2.n:n(max reported sample size) < 10000.is_snpid_non_unique: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_mean_chisq< 0.7.n_p_sig:n_p_sig> 1000.miss_<*>:n_miss_<*>/n_snps> 0.01.ldsc_ratio:ldsc_ratio> 0.5ldsc_intercept_beta:ldsc_intercept_beta> 1.5n_clumped_hits:n_clumped_hits> 1000r2_sum<*>:r2_sum<*>> 0.5
Plots
- Manhattan plot
- Red line: \(-log_{10}^{5 \times 10^{-8}}\)
- Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
- QQ plot
- AF plot
- P-Z plot
- beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)
Diagnostics
Details
Summary stats
| skim_type | skim_variable | n_missing | complete_rate | character.min | character.max | character.empty | character.n_unique | character.whitespace | logical.mean | logical.count | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 0 | 1.0000000 | 3 | 64 | 0 | 11459425 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 60 | 0 | 400 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 50 | 0 | 353 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 11473380 | 0.0000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.857713e+00 | 5.769205e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▆▅▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.421648e+07 | 5.207056e+07 | 173.0000000 | 3.148452e+07 | 6.642770e+07 | 1.080978e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -4.840000e-05 | 1.619690e-02 | -0.2703860 | -4.269800e-03 | -7.900000e-06 | 4.225400e-03 | 2.544780e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.132420e-02 | 1.078520e-02 | 0.0021698 | 2.804200e-03 | 6.178000e-03 | 1.757450e-02 | 1.402840e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.784618e-01 | 2.943403e-01 | 0.0000000 | 2.200002e-01 | 4.700002e-01 | 7.300002e-01 | 1.000000e+00 | ▇▇▇▆▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.784540e-01 | 2.943199e-01 | 0.0000000 | 2.182639e-01 | 4.705242e-01 | 7.334580e-01 | 9.999999e-01 | ▇▇▆▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.663688e-01 | 2.446030e-01 | 0.0010010 | 4.428000e-03 | 3.527400e-02 | 2.391680e-01 | 9.990000e-01 | ▇▁▁▁▁ |
| numeric | AF_reference | 571861 | 0.9501576 | NA | NA | NA | NA | NA | NA | NA | 1.741593e-01 | 2.396161e-01 | 0.0000000 | 2.995200e-03 | 5.630990e-02 | 2.605830e-01 | 1.000000e+00 | ▇▂▁▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 13169 | rs1436530583 | A | G | 0.0147870 | 0.0297179 | 0.6200004 | 0.6187809 | 0.997286 | NA | NA |
| 1 | 15850 | rs575961614 | G | A | 0.0065720 | 0.0107830 | 0.5400003 | 0.5422096 | 0.021348 | 0.0005990 | NA |
| 1 | 15893 | rs555382915 | T | C | -0.0019632 | 0.0033518 | 0.5700002 | 0.5580777 | 0.778475 | 0.0001997 | NA |
| 1 | 30912 | rs571608907 | C | T | -0.0153429 | 0.0309077 | 0.6100002 | 0.6196050 | 0.996851 | 0.0001997 | NA |
| 1 | 49298 | rs200943160 | T | C | 0.0039104 | 0.0038818 | 0.3100002 | 0.3137705 | 0.623709 | 0.7821490 | NA |
| 1 | 54676 | rs2462492 | C | T | 0.0020564 | 0.0038457 | 0.6100002 | 0.5928476 | 0.400717 | NA | NA |
| 1 | 54712 | rs568927205 | T | TTTTC | -0.0004952 | 0.0030412 | 0.8499999 | 0.8706407 | 0.585464 | NA | NA |
| 1 | 55326 | rs3107975 | T | C | -0.0234672 | 0.0215228 | 0.2800000 | 0.2755628 | 0.008399 | 0.0459265 | NA |
| 1 | 55389 | rs1190986229 | T | C | 0.0043762 | 0.0215175 | 0.8499999 | 0.8388376 | 0.004168 | NA | NA |
| 1 | 70728 | rs1259734071 | C | T | -0.0371603 | 0.0393220 | 0.3599996 | 0.3446458 | 0.002139 | NA | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51226692 | rs150189434 | G | A | 0.0169857 | 0.0290379 | 0.5600000 | 0.5585818 | 0.001672 | 0.0155751 | NA |
| 22 | 51227766 | rs186062720 | T | C | 0.0398455 | 0.0278322 | 0.1499999 | 0.1522488 | 0.002276 | 0.0005990 | NA |
| 22 | 51229805 | rs9616985 | T | C | 0.0107659 | 0.0042192 | 0.0100000 | 0.0107212 | 0.073179 | 0.0730831 | NA |
| 22 | 51230673 | rs555680442 | G | C | 0.0260764 | 0.0292540 | 0.3599996 | 0.3727259 | 0.002149 | 0.0017971 | NA |
| 22 | 51231424 | rs539541647 | A | G | 0.0083798 | 0.0343124 | 0.8000000 | 0.8070594 | 0.001280 | 0.0011981 | NA |
| 22 | 51232488 | rs376461333 | A | G | -0.0102159 | 0.0099193 | 0.2999998 | 0.3030544 | 0.020140 | NA | NA |
| 22 | 51234033 | rs764597437 | C | T | 0.0066776 | 0.0375380 | 0.8600001 | 0.8588109 | 0.001202 | NA | NA |
| 22 | 51237063 | rs3896457 | T | C | 0.0016930 | 0.0025797 | 0.5099998 | 0.5116478 | 0.298528 | 0.2050720 | NA |
| 22 | 51239586 | rs535432390 | T | G | -0.0347853 | 0.0230865 | 0.1199999 | 0.1318779 | 0.003039 | 0.0001997 | NA |
| 23 | 65456737 | rs77978087 | G | C | 0.0003073 | 0.0026380 | 0.9199999 | 0.9072626 | 0.507184 | NA | NA |
bcf preview
1 13169 rs1436530583 A G . PASS AF=0.997286 ES:SE:LP:AF:ID 0.014787:0.0297179:0.207608:0.997286:rs1436530583
1 15850 rs575961614 G A . PASS AF=0.021348 ES:SE:LP:AF:ID 0.00657197:0.010783:0.267606:0.021348:rs575961614
1 15893 rs555382915 T C . PASS AF=0.778475 ES:SE:LP:AF:ID -0.00196317:0.00335184:0.244125:0.778475:rs555382915
1 30912 rs571608907 C T . PASS AF=0.996851 ES:SE:LP:AF:ID -0.0153429:0.0309077:0.21467:0.996851:rs571608907
1 49298 rs10399793 T C . PASS AF=0.623709 ES:SE:LP:AF:ID 0.00391035:0.00388185:0.508638:0.623709:rs10399793
1 54676 rs2462492 C T . PASS AF=0.400717 ES:SE:LP:AF:ID 0.00205635:0.0038457:0.21467:0.400717:rs2462492
1 54712 rs568927205 T TTTTC . PASS AF=0.585464 ES:SE:LP:AF:ID -0.000495245:0.00304121:0.0705811:0.585464:rs568927205
1 55326 rs3107975 T C . PASS AF=0.008399 ES:SE:LP:AF:ID -0.0234672:0.0215228:0.552842:0.008399:rs3107975
1 55389 rs1190986229 T C . PASS AF=0.004168 ES:SE:LP:AF:ID 0.00437624:0.0215175:0.0705811:0.004168:rs1190986229
1 70728 rs1259734071 C T . PASS AF=0.002139 ES:SE:LP:AF:ID -0.0371603:0.039322:0.443698:0.002139:rs1259734071
1 74356 rs1374516807 T C . PASS AF=0.996716 ES:SE:LP:AF:ID -0.0197476:0.0293857:0.30103:0.996716:rs1374516807
1 79033 rs2462495 A G . PASS AF=0.998737 ES:SE:LP:AF:ID 0.129756:0.0500149:2.02687:0.998737:rs2462495
1 81120 rs1180184210 G C . PASS AF=0.998459 ES:SE:LP:AF:ID -0.0247357:0.0387718:0.283997:0.998459:rs1180184210
1 82103 rs2020400 T C . PASS AF=0.925141 ES:SE:LP:AF:ID 0.00378409:0.00540142:0.309804:0.925141:rs2020400
1 86028 rs114608975 T C . PASS AF=0.103558 ES:SE:LP:AF:ID 0.00303299:0.00615349:0.207608:0.103558:rs114608975
1 88166 rs1329210408 T C . PASS AF=0.997833 ES:SE:LP:AF:ID 0.0153526:0.0358306:0.161151:0.997833:rs1329210408
1 91311 rs1354585492 T C . PASS AF=0.997671 ES:SE:LP:AF:ID -0.0131045:0.0307766:0.173925:0.997671:rs1354585492
1 91536 rs6702460 G T . PASS AF=0.457094 ES:SE:LP:AF:ID 0.00666916:0.00378954:1.08619:0.457094:rs6702460
1 115967 rs1310910178 C T . PASS AF=0.002549 ES:SE:LP:AF:ID -0.027599:0.0378881:0.318759:0.002549:rs1310910178
1 121759 rs975013924 C A . PASS AF=0.007664 ES:SE:LP:AF:ID -0.0147679:0.0152757:0.481486:0.007664:rs975013924
1 123130 rs1235743598 T C . PASS AF=0.994494 ES:SE:LP:AF:ID 0.0294992:0.0229791:0.677781:0.994494:rs1235743598
1 126133 rs531293975 G T . PASS AF=0.9986 ES:SE:LP:AF:ID 0.102345:0.0458358:1.61979:0.9986:rs531293975
1 157899 rs1339985321 G C . PASS AF=0.001276 ES:SE:LP:AF:ID -0.0254054:0.0498344:0.221849:0.001276:rs1339985321
1 174747 rs1399732465 C T . PASS AF=0.025821 ES:SE:LP:AF:ID -0.00496617:0.010788:0.19382:0.025821:rs1399732465
1 234313 rs8179466 C T . PASS AF=0.074619 ES:SE:LP:AF:ID -0.00643838:0.00746007:0.408935:0.074619:rs8179466
1 526736 rs28863004 C G . PASS AF=0.005851 ES:SE:LP:AF:ID 0.00746987:0.0259512:0.119186:0.005851:rs28863004
1 534192 rs6680723 C T . PASS AF=0.240799 ES:SE:LP:AF:ID 0.00413993:0.00433012:0.481486:0.240799:rs6680723
1 534583 rs6683466 C G . PASS AF=0.00668 ES:SE:LP:AF:ID 0.0208489:0.0245123:0.408935:0.00668:rs6683466
1 544584 rs576404767 C T . PASS AF=0.001868 ES:SE:LP:AF:ID -0.00421296:0.0352403:0.0409586:0.001868:rs576404767
1 546697 rs12025928 A G . PASS AF=0.913398 ES:SE:LP:AF:ID -0.00438961:0.00538988:0.387216:0.913398:rs12025928
1 564862 rs1988726 T C . PASS AF=0.00131 ES:SE:LP:AF:ID 0.0609542:0.0532293:0.60206:0.00131:rs1988726
1 565111 rs573042692 T C . PASS AF=0.001586 ES:SE:LP:AF:ID -0.0250519:0.0421222:0.259637:0.001586:rs573042692
1 565130 rs371431021 G A . PASS AF=0.004521 ES:SE:LP:AF:ID 0.0155481:0.0270776:0.244125:0.004521:rs371431021
1 565196 rs538567606 T C . PASS AF=0.002296 ES:SE:LP:AF:ID 0.0528749:0.0374403:0.79588:0.002296:rs538567606
1 565469 rs554127336 C T . PASS AF=0.001438 ES:SE:LP:AF:ID -0.0307671:0.0504814:0.267606:0.001438:rs554127336
1 565470 rs544876160 G A . PASS AF=0.001021 ES:SE:LP:AF:ID 0.0179701:0.0435063:0.173925:0.001021:rs544876160
1 565490 rs7349153 T C . PASS AF=0.00136 ES:SE:LP:AF:ID 0.0342547:0.0533479:0.29243:0.00136:rs7349153
1 565870 rs9326619 T C . PASS AF=0.001511 ES:SE:LP:AF:ID 0.0421063:0.0512139:0.39794:0.001511:rs9326619
1 566024 rs6421779 G A . PASS AF=0.001294 ES:SE:LP:AF:ID 0.0721282:0.0534328:0.744727:0.001294:rs6421779
1 566371 rs1832731 A G . PASS AF=0.001481 ES:SE:LP:AF:ID 0.0145604:0.0527982:0.107905:0.001481:rs1832731
1 566792 rs9283152 T C . PASS AF=0.002083 ES:SE:LP:AF:ID -0.00370325:0.0462555:0.0315171:0.002083:rs9283152
1 566933 rs113120793 A G . PASS AF=0.001303 ES:SE:LP:AF:ID 0.0254302:0.0545511:0.200659:0.001303:rs113120793
1 566960 rs2185540 T C . PASS AF=0.001393 ES:SE:LP:AF:ID 0.00731667:0.0540159:0.0555173:0.001393:rs2185540
1 567006 rs565235853 G T . PASS AF=0.003015 ES:SE:LP:AF:ID -0.0220342:0.0241693:0.455932:0.003015:rs565235853
1 567867 rs2000096 A G . PASS AF=0.002924 ES:SE:LP:AF:ID -0.000876284:0.036318:0.00436481:0.002924:rs2000096
1 568072 rs2853820 A G . PASS AF=0.001527 ES:SE:LP:AF:ID 0.0152211:0.048979:0.124939:0.001527:rs2853820
1 568800 rs375217967 G A . PASS AF=0.016907 ES:SE:LP:AF:ID -0.00227356:0.0148447:0.0604807:0.016907:rs375217967
1 569204 rs112660509 T C . PASS AF=0.001859 ES:SE:LP:AF:ID 0.000665366:0.0488756:0.00436481:0.001859:rs112660509
1 569543 rs538153094 G A . PASS AF=0.001554 ES:SE:LP:AF:ID 0.0837084:0.0509083:1:0.001554:rs538153094
1 569604 rs9645429 G A . PASS AF=0.001685 ES:SE:LP:AF:ID -0.00492648:0.043296:0.0362122:0.001685:rs9645429