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": "2019-10-27T07:19:19.011956",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004733/EBI-a-GCST004733_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-GCST004733/EBI-a-GCST004733.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004733/EBI-a-GCST004733_data.vcf.gz; Date=Sun Oct 27 07:23:56 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST004733/ebi-a-GCST004733.vcf.gz; Date=Sun May 10 05:59:45 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-GCST004733/EBI-a-GCST004733.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-GCST004733/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 Sun Oct 27 07:46:08 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004733/EBI-a-GCST004733.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 Sun Oct 27 07:46:25 2019
Total time elapsed: 16.8sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9289,
"inflation_factor": 1.0334,
"mean_EFFECT": -0,
"n": "-Inf",
"n_snps": 2528636,
"n_clumped_hits": 6,
"n_p_sig": 204,
"n_mono": 0,
"n_ns": 0,
"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": 20554,
"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 | 42 | 0 | 2521999 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 2522015 | 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 | 8.585213e+00 | 5.661373e+00 | 1.000000 | 4.000000e+00 | 8.000000e+00 | 1.200000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.893008e+07 | 5.580136e+07 | 6689.000000 | 3.262738e+07 | 7.033301e+07 | 1.144649e+08 | 2.492190e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -3.620000e-05 | 1.124690e-02 | -0.654340 | -4.990000e-03 | -3.500000e-05 | 4.907000e-03 | 6.301080e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.746900e-03 | 6.865300e-03 | 0.004849 | 5.420000e-03 | 6.435000e-03 | 8.976000e-03 | 4.009530e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.946228e-01 | 2.903352e-01 | 0.000000 | 2.422418e-01 | 4.929218e-01 | 7.461841e-01 | 9.999890e-01 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.923537e-01 | 2.909177e-01 | 0.000000 | 2.389042e-01 | 4.898126e-01 | 7.444191e-01 | 9.999843e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.590206e-01 | 2.698856e-01 | 0.010001 | 1.249135e-01 | 2.948090e-01 | 5.555415e-01 | 9.899980e-01 | ▇▅▃▂▂ |
| numeric | AF_reference | 20554 | 0.9918502 | NA | NA | NA | NA | NA | NA | NA | 3.617947e-01 | 2.555418e-01 | 0.000000 | 1.467650e-01 | 3.001200e-01 | 5.459270e-01 | 1.000000e+00 | ▇▆▃▃▂ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 721290 | rs12565286 | G | C | -0.007425 | 0.016351 | 0.6521192 | 0.6497564 | 0.052682 | 0.0371406 | NA |
| 1 | 723819 | rs11804171 | T | A | -0.003790 | 0.016302 | 0.8174310 | 0.8161599 | 0.055861 | 0.1345850 | NA |
| 1 | 723891 | rs2977670 | G | C | 0.003977 | 0.012964 | 0.7606642 | 0.7590165 | 0.932639 | 0.7799520 | NA |
| 1 | 752566 | rs3094315 | G | A | 0.012614 | 0.007430 | 0.0918502 | 0.0895621 | 0.786077 | 0.7182510 | NA |
| 1 | 754192 | rs3131968 | A | G | 0.012484 | 0.008004 | 0.1214571 | 0.1188260 | 0.862176 | 0.6785140 | NA |
| 1 | 761732 | rs2286139 | C | T | 0.018032 | 0.009822 | 0.0683376 | 0.0663756 | 0.768103 | 0.6257990 | NA |
| 1 | 768448 | rs12562034 | G | A | 0.005974 | 0.017698 | 0.7375169 | 0.7357006 | 0.090450 | 0.1918930 | NA |
| 1 | 775659 | rs2905035 | A | G | 0.008259 | 0.008310 | 0.3237830 | 0.3202897 | 0.862967 | 0.7450080 | NA |
| 1 | 777122 | rs2980319 | A | T | 0.008964 | 0.008299 | 0.2834849 | 0.2800842 | 0.828374 | 0.7472040 | NA |
| 1 | 779322 | rs4040617 | A | G | -0.014555 | 0.008889 | 0.1039829 | 0.1015434 | 0.136823 | 0.2264380 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51196164 | rs8136603 | A | T | -0.039940 | 0.016870 | 0.0187642 | 0.0179079 | 0.057777 | 0.1427720 | NA |
| 22 | 51211392 | rs3888396 | T | C | 0.067796 | 0.018413 | 0.0002580 | 0.0002314 | 0.097523 | 0.1641370 | NA |
| 22 | 51212875 | rs2238837 | A | C | -0.005421 | 0.007672 | 0.4829465 | 0.4798179 | 0.379879 | 0.3724040 | NA |
| 22 | 51216564 | rs9616970 | T | C | -0.044221 | 0.012937 | 0.0006930 | 0.0006304 | 0.147532 | 0.1563500 | NA |
| 22 | 51217134 | rs117417021 | A | G | -0.009575 | 0.008212 | 0.2469329 | 0.2436239 | 0.418019 | 0.2671730 | NA |
| 22 | 51219006 | rs28729663 | G | A | -0.023445 | 0.011923 | 0.0509143 | 0.0492562 | 0.170451 | 0.2052720 | NA |
| 22 | 51223637 | rs375798137 | G | A | -0.043143 | 0.015559 | 0.0059160 | 0.0055565 | 0.060493 | 0.0788738 | NA |
| 22 | 51229805 | rs9616985 | T | C | -0.042836 | 0.017419 | 0.0146379 | 0.0139265 | 0.087972 | 0.0730831 | NA |
| 23 | 91415872 | rs6562597 | G | A | -0.010512 | 0.027453 | 0.7038336 | 0.7017873 | 0.019521 | 0.0021192 | NA |
| 23 | 118495837 | rs12882977 | G | A | 0.001209 | 0.005081 | 0.8132669 | 0.8119235 | 0.485973 | 0.2307280 | NA |
bcf preview
1 721290 rs12565286 G C . PASS AF=0.052682 ES:SE:LP:AF:ID -0.007425:0.016351:0.185673:0.052682:rs12565286
1 723819 rs11804171 T A . PASS AF=0.055861 ES:SE:LP:AF:ID -0.00379:0.016302:0.0875489:0.055861:rs11804171
1 723891 rs2977670 G C . PASS AF=0.932639 ES:SE:LP:AF:ID 0.003977:0.012964:0.118807:0.932639:rs2977670
1 752566 rs3094315 G A . PASS AF=0.786077 ES:SE:LP:AF:ID 0.012614:0.00743:1.03692:0.786077:rs3094315
1 754192 rs3131968 A G . PASS AF=0.862176 ES:SE:LP:AF:ID 0.012484:0.008004:0.915577:0.862176:rs3131968
1 761732 rs2286139 C T . PASS AF=0.768103 ES:SE:LP:AF:ID 0.018032:0.009822:1.16534:0.768103:rs2286139
1 768448 rs12562034 G A . PASS AF=0.09045 ES:SE:LP:AF:ID 0.005974:0.017698:0.132228:0.09045:rs12562034
1 775659 rs2905035 A G . PASS AF=0.862967 ES:SE:LP:AF:ID 0.008259:0.00831:0.489746:0.862967:rs2905035
1 777122 rs2980319 A T . PASS AF=0.828374 ES:SE:LP:AF:ID 0.008964:0.008299:0.54747:0.828374:rs2980319
1 779322 rs4040617 A G . PASS AF=0.136823 ES:SE:LP:AF:ID -0.014555:0.008889:0.983038:0.136823:rs4040617
1 780785 rs2977612 T A . PASS AF=0.862192 ES:SE:LP:AF:ID 0.008754:0.009255:0.458855:0.862192:rs2977612
1 785050 rs2905062 G A . PASS AF=0.860442 ES:SE:LP:AF:ID 0.013939:0.008897:0.921478:0.860442:rs2905062
1 785989 rs2980300 T C . PASS AF=0.791641 ES:SE:LP:AF:ID 0.011899:0.00871:0.757165:0.791641:rs2980300
1 798026 rs4951864 C T . PASS AF=0.901949 ES:SE:LP:AF:ID -0.004901:0.015465:0.123192:0.901949:rs4951864
1 798801 rs12132517 G A . PASS AF=0.103935 ES:SE:LP:AF:ID 0.005065:0.015819:0.12461:0.103935:rs12132517
1 798959 rs11240777 G A . PASS AF=0.254362 ES:SE:LP:AF:ID -0.006233:0.008481:0.331963:0.254362:rs11240777
1 888659 rs3748597 T C . PASS AF=0.940654 ES:SE:LP:AF:ID 0.013756:0.019118:0.323328:0.940654:rs3748597
1 918573 rs2341354 A G . PASS AF=0.540738 ES:SE:LP:AF:ID -0.00595:0.007693:0.354086:0.540738:rs2341354
1 926431 rs4970403 A T . PASS AF=0.917343 ES:SE:LP:AF:ID -0.006017:0.022133:0.103903:0.917343:rs4970403
1 947034 rs2465126 G A . PASS AF=0.885288 ES:SE:LP:AF:ID 0.007381:0.019451:0.150965:0.885288:rs2465126
1 962210 rs3128126 A G . PASS AF=0.439242 ES:SE:LP:AF:ID 0.009097:0.009914:0.441028:0.439242:rs3128126
1 990380 rs3121561 C T . PASS AF=0.291829 ES:SE:LP:AF:ID 0.014395:0.008773:0.986022:0.291829:rs3121561
1 990417 rs2465136 T C . PASS AF=0.343467 ES:SE:LP:AF:ID -0.000415:0.008153:0.0178749:0.343467:rs2465136
1 998501 rs3813193 G C . PASS AF=0.179487 ES:SE:LP:AF:ID 0.008819:0.012067:0.329686:0.179487:rs3813193
1 1003629 rs4075116 C T . PASS AF=0.724831 ES:SE:LP:AF:ID -0.00725:0.006703:0.548495:0.724831:rs4075116
1 1005806 rs3934834 C T . PASS AF=0.158432 ES:SE:LP:AF:ID 0.004596:0.01018:0.184419:0.158432:rs3934834
1 1017170 rs3766193 C G . PASS AF=0.540249 ES:SE:LP:AF:ID -0.009594:0.006057:0.936396:0.540249:rs3766193
1 1017197 rs3766192 C T . PASS AF=0.549475 ES:SE:LP:AF:ID -0.009493:0.00563:1.0262:0.549475:rs3766192
1 1017587 rs3766191 C T . PASS AF=0.15266 ES:SE:LP:AF:ID 0.004818:0.009349:0.215492:0.15266:rs3766191
1 1018562 rs9442371 C T . PASS AF=0.558091 ES:SE:LP:AF:ID -0.009565:0.005462:1.08572:0.558091:rs9442371
1 1018704 rs9442372 A G . PASS AF=0.558568 ES:SE:LP:AF:ID -0.010006:0.005468:1.15949:0.558568:rs9442372
1 1021346 rs10907177 A G . PASS AF=0.156788 ES:SE:LP:AF:ID 0.003571:0.010227:0.137392:0.156788:rs10907177
1 1021415 rs3737728 A G . PASS AF=0.709676 ES:SE:LP:AF:ID -0.010737:0.006287:1.04613:0.709676:rs3737728
1 1021583 rs10907178 A C . PASS AF=0.157974 ES:SE:LP:AF:ID 0.005727:0.009239:0.268972:0.157974:rs10907178
1 1021695 rs9442398 A G . PASS AF=0.718069 ES:SE:LP:AF:ID -0.008799:0.006947:0.680811:0.718069:rs9442398
1 1022037 rs6701114 C T . PASS AF=0.541506 ES:SE:LP:AF:ID -0.010703:0.006081:1.09406:0.541506:rs6701114
1 1026707 rs4074137 C A . PASS AF=0.587036 ES:SE:LP:AF:ID -0.010104:0.009905:0.507069:0.587036:rs4074137
1 1030565 rs6687776 C T . PASS AF=0.15854 ES:SE:LP:AF:ID 0.001551:0.009095:0.0627405:0.15854:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.141443 ES:SE:LP:AF:ID 0.004325:0.010093:0.173571:0.141443:rs6678318
1 1031540 rs9651273 A G . PASS AF=0.681122 ES:SE:LP:AF:ID -0.008079:0.009105:0.422105:0.681122:rs9651273
1 1036959 rs11579015 T C . PASS AF=0.082597 ES:SE:LP:AF:ID -0.00679:0.01037:0.287642:0.082597:rs11579015
1 1039098 rs11260595 C A . PASS AF=0.033928 ES:SE:LP:AF:ID 0.02115:0.030148:0.313278:0.033928:rs11260595
1 1040026 rs6671356 T C . PASS AF=0.134125 ES:SE:LP:AF:ID 0.000217:0.009831:0.00766965:0.134125:rs6671356
1 1041700 rs6604968 A G . PASS AF=0.189407 ES:SE:LP:AF:ID 0.005362:0.010275:0.218674:0.189407:rs6604968
1 1046164 rs6666280 C T . PASS AF=0.101226 ES:SE:LP:AF:ID -0.001867:0.010696:0.0642852:0.101226:rs6666280
1 1048955 rs4970405 A G . PASS AF=0.092116 ES:SE:LP:AF:ID -0.00603:0.008994:0.296188:0.092116:rs4970405
1 1049950 rs12726255 A G . PASS AF=0.099659 ES:SE:LP:AF:ID -0.000519:0.011863:0.0153197:0.099659:rs12726255
1 1053452 rs4970409 G A . PASS AF=0.079623 ES:SE:LP:AF:ID -0.003006:0.011857:0.0962363:0.079623:rs4970409
1 1060174 rs7548798 C T . PASS AF=0.337464 ES:SE:LP:AF:ID 0.007517:0.011771:0.278962:0.337464:rs7548798
1 1060608 rs17160824 G A . PASS AF=0.086542 ES:SE:LP:AF:ID -0.004525:0.01215:0.147794:0.086542:rs17160824