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": "2019-10-27T07:18:59.867813",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST001969/EBI-a-GCST001969_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-GCST001969/EBI-a-GCST001969.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST001969/EBI-a-GCST001969_data.vcf.gz; Date=Sun Oct 27 07:23:25 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST001969/ebi-a-GCST001969.vcf.gz; Date=Sun May 10 02:22:09 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-GCST001969/EBI-a-GCST001969.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-GCST001969/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 07:46:01 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST001969/EBI-a-GCST001969.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 07:46:18 2019
Total time elapsed: 17.2sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9334,
"inflation_factor": 1.1162,
"mean_EFFECT": -0.0001,
"n": "-Inf",
"n_snps": 2509620,
"n_clumped_hits": 15,
"n_p_sig": 557,
"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": 20758,
"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 | 2503137 | 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 | 2503150 | 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 | 8.588579e+00 | 5.657327e+00 | 1.0000 | 4.000000e+00 | 8.000000e+00 | 1.200000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.886338e+07 | 5.566267e+07 | 11523.0000 | 3.269740e+07 | 7.034516e+07 | 1.142992e+08 | 2.492190e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.341000e-04 | 1.098415e-01 | -2.6093 | -5.160000e-02 | 2.000000e-04 | 5.120000e-02 | 2.843300e+00 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.630380e-02 | 6.237040e-02 | 0.0494 | 5.450000e-02 | 6.440000e-02 | 9.040000e-02 | 1.267700e+00 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.815515e-01 | 2.934920e-01 | 0.0000 | 2.224001e-01 | 4.760998e-01 | 7.358004e-01 | 9.999000e-01 | ▇▇▇▇▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.815510e-01 | 2.934919e-01 | 0.0000 | 2.224313e-01 | 4.761283e-01 | 7.357530e-01 | 9.998205e-01 | ▇▇▇▇▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.585658e-01 | 2.682614e-01 | 0.0028 | 1.271000e-01 | 2.939000e-01 | 5.528000e-01 | 9.965000e-01 | ▇▅▃▃▂ |
| numeric | AF_reference | 20758 | 0.9917072 | NA | NA | NA | NA | NA | NA | NA | 3.593724e-01 | 2.569820e-01 | 0.0000 | 1.433710e-01 | 2.963260e-01 | 5.441290e-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 | 0.1632 | 0.2577 | 0.5266002 | 0.5265413 | 0.0609 | 0.0371406 | NA |
| 1 | 723819 | rs11804171 | T | A | 0.1410 | 0.2581 | 0.5847995 | 0.5848598 | 0.0611 | 0.1345850 | NA |
| 1 | 723891 | rs2977670 | G | C | -0.1500 | 0.2696 | 0.5779004 | 0.5779512 | 0.9379 | 0.7799520 | NA |
| 1 | 750235 | rs12138618 | G | A | -0.1359 | 0.2259 | 0.5474003 | 0.5474447 | 0.0672 | NA | NA |
| 1 | 752566 | rs3094315 | G | A | 0.0165 | 0.0845 | 0.8447000 | 0.8451845 | 0.8163 | 0.7182510 | NA |
| 1 | 754192 | rs3131968 | A | G | 0.0590 | 0.1121 | 0.5984998 | 0.5986688 | 0.8588 | 0.6785140 | NA |
| 1 | 768448 | rs12562034 | G | A | -0.1886 | 0.1197 | 0.1150000 | 0.1151167 | 0.1434 | 0.1918930 | NA |
| 1 | 775659 | rs2905035 | A | G | 0.0799 | 0.0965 | 0.4075004 | 0.4076822 | 0.8615 | 0.7450080 | NA |
| 1 | 776546 | rs12124819 | A | G | -0.0732 | 0.1194 | 0.5396995 | 0.5398331 | 0.2286 | 0.0756789 | NA |
| 1 | 777122 | rs2980319 | A | T | 0.0713 | 0.0967 | 0.4606998 | 0.4609205 | 0.8618 | 0.7472040 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51196164 | rs8136603 | A | T | 0.1445 | 0.1420 | 0.3087003 | 0.3088654 | 0.0644 | 0.1427720 | NA |
| 22 | 51211392 | rs3888396 | T | C | -0.2736 | 0.2665 | 0.3046001 | 0.3045892 | 0.0917 | 0.1641370 | NA |
| 22 | 51212875 | rs2238837 | A | C | -0.0230 | 0.0884 | 0.7949999 | 0.7947242 | 0.3854 | 0.3724040 | NA |
| 22 | 51216564 | rs9616970 | T | C | 0.0488 | 0.1106 | 0.6589994 | 0.6590467 | 0.1440 | 0.1563500 | NA |
| 22 | 51217134 | rs117417021 | A | G | -0.0020 | 0.0895 | 0.9825000 | 0.9821717 | 0.4329 | 0.2671730 | NA |
| 22 | 51222100 | rs114553188 | G | T | 0.1128 | 0.1436 | 0.4320997 | 0.4321515 | 0.0617 | 0.0880591 | NA |
| 22 | 51223637 | rs375798137 | G | A | 0.1144 | 0.1444 | 0.4280998 | 0.4282186 | 0.0617 | 0.0788738 | NA |
| 22 | 51229805 | rs9616985 | T | C | 0.1100 | 0.1762 | 0.5327004 | 0.5324368 | 0.0868 | 0.0730831 | NA |
| 23 | 91415872 | rs6562597 | G | A | 0.0904 | 0.2097 | 0.6664998 | 0.6664015 | 0.0240 | 0.0021192 | NA |
| 23 | 118495837 | rs12882977 | G | A | 0.0574 | 0.0512 | 0.2627000 | 0.2622480 | 0.4638 | 0.2307280 | NA |
bcf preview
1 721290 rs12565286 G C . PASS AF=0.0609 ES:SE:LP:AF:ID 0.1632:0.2577:0.278519:0.0609:rs12565286
1 723819 rs11804171 T A . PASS AF=0.0611 ES:SE:LP:AF:ID 0.141:0.2581:0.232993:0.0611:rs11804171
1 723891 rs2977670 G C . PASS AF=0.9379 ES:SE:LP:AF:ID -0.15:0.2696:0.238147:0.9379:rs2977670
1 750235 rs12138618 G A . PASS AF=0.0672 ES:SE:LP:AF:ID -0.1359:0.2259:0.261695:0.0672:rs12138618
1 752566 rs3094315 G A . PASS AF=0.8163 ES:SE:LP:AF:ID 0.0165:0.0845:0.0732975:0.8163:rs3094315
1 754192 rs3131968 A G . PASS AF=0.8588 ES:SE:LP:AF:ID 0.059:0.1121:0.222936:0.8588:rs3131968
1 768448 rs12562034 G A . PASS AF=0.1434 ES:SE:LP:AF:ID -0.1886:0.1197:0.939302:0.1434:rs12562034
1 775659 rs2905035 A G . PASS AF=0.8615 ES:SE:LP:AF:ID 0.0799:0.0965:0.389872:0.8615:rs2905035
1 776546 rs12124819 A G . PASS AF=0.2286 ES:SE:LP:AF:ID -0.0732:0.1194:0.267848:0.2286:rs12124819
1 777122 rs2980319 A T . PASS AF=0.8618 ES:SE:LP:AF:ID 0.0713:0.0967:0.336582:0.8618:rs2980319
1 779322 rs4040617 A G . PASS AF=0.1389 ES:SE:LP:AF:ID -0.0484:0.0992:0.203703:0.1389:rs4040617
1 780785 rs2977612 T A . PASS AF=0.8612 ES:SE:LP:AF:ID 0.064:0.1002:0.281831:0.8612:rs2977612
1 785050 rs2905062 G A . PASS AF=0.8583 ES:SE:LP:AF:ID 0.0669:0.1001:0.297569:0.8583:rs2905062
1 785989 rs2980300 T C . PASS AF=0.8513 ES:SE:LP:AF:ID 0.0369:0.0969:0.152674:0.8513:rs2980300
1 798026 rs4951864 C T . PASS AF=0.8932 ES:SE:LP:AF:ID 0.1366:0.1583:0.410833:0.8932:rs4951864
1 798801 rs12132517 G A . PASS AF=0.1144 ES:SE:LP:AF:ID -0.1522:0.1597:0.467628:0.1144:rs12132517
1 798959 rs11240777 G A . PASS AF=0.2165 ES:SE:LP:AF:ID -0.0904:0.1142:0.367847:0.2165:rs11240777
1 962210 rs3128126 A G . PASS AF=0.4491 ES:SE:LP:AF:ID -0.1396:0.1009:0.777804:0.4491:rs3128126
1 990380 rs3121561 C T . PASS AF=0.3045 ES:SE:LP:AF:ID -0.1276:0.0896:0.811353:0.3045:rs3121561
1 998501 rs3813193 G C . PASS AF=0.2137 ES:SE:LP:AF:ID 0.0208:0.0856:0.0926424:0.2137:rs3813193
1 1003629 rs4075116 C T . PASS AF=0.7437 ES:SE:LP:AF:ID 0.0455:0.0701:0.28693:0.7437:rs4075116
1 1005806 rs3934834 C T . PASS AF=0.1969 ES:SE:LP:AF:ID 0.0187:0.0785:0.090765:0.1969:rs3934834
1 1017170 rs3766193 C G . PASS AF=0.5437 ES:SE:LP:AF:ID 0.0203:0.0628:0.12697:0.5437:rs3766193
1 1017197 rs3766192 C T . PASS AF=0.551 ES:SE:LP:AF:ID 0.0429:0.0593:0.328457:0.551:rs3766192
1 1017587 rs3766191 C T . PASS AF=0.1874 ES:SE:LP:AF:ID 0.0073:0.0818:0.0319843:0.1874:rs3766191
1 1018562 rs9442371 C T . PASS AF=0.5582 ES:SE:LP:AF:ID 0.0366:0.0582:0.275806:0.5582:rs9442371
1 1018704 rs9442372 A G . PASS AF=0.5586 ES:SE:LP:AF:ID 0.0353:0.0578:0.266722:0.5586:rs9442372
1 1021346 rs10907177 A G . PASS AF=0.1866 ES:SE:LP:AF:ID -0.0072:0.0842:0.0306307:0.1866:rs10907177
1 1021415 rs3737728 A G . PASS AF=0.7283 ES:SE:LP:AF:ID 0.013:0.0626:0.0778457:0.7283:rs3737728
1 1021583 rs10907178 A C . PASS AF=0.1862 ES:SE:LP:AF:ID -0.0419:0.0877:0.198665:0.1862:rs10907178
1 1021695 rs9442398 A G . PASS AF=0.7364 ES:SE:LP:AF:ID 0.0205:0.0656:0.122226:0.7364:rs9442398
1 1022037 rs6701114 C T . PASS AF=0.5422 ES:SE:LP:AF:ID 0.0339:0.0662:0.215597:0.5422:rs6701114
1 1025301 rs9442400 T C . PASS AF=0.9485 ES:SE:LP:AF:ID 0.7099:0.322:1.56146:0.9485:rs9442400
1 1026707 rs4074137 C A . PASS AF=0.6094 ES:SE:LP:AF:ID 0.143:0.0699:1.38998:0.6094:rs4074137
1 1030565 rs6687776 C T . PASS AF=0.1765 ES:SE:LP:AF:ID 0.1966:0.079:1.89279:0.1765:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.161 ES:SE:LP:AF:ID 0.2064:0.0932:1.57138:0.161:rs6678318
1 1031540 rs9651273 A G . PASS AF=0.7309 ES:SE:LP:AF:ID 0.2066:0.0676:2.64936:0.7309:rs9651273
1 1036959 rs11579015 T C . PASS AF=0.1105 ES:SE:LP:AF:ID 0.1385:0.0999:0.78094:0.1105:rs11579015
1 1040026 rs6671356 T C . PASS AF=0.1435 ES:SE:LP:AF:ID 0.2219:0.0891:1.89483:0.1435:rs6671356
1 1046164 rs6666280 C T . PASS AF=0.1364 ES:SE:LP:AF:ID 0.1945:0.0881:1.56607:0.1364:rs6666280
1 1048955 rs4970405 A G . PASS AF=0.1035 ES:SE:LP:AF:ID 0.0607:0.0956:0.279593:0.1035:rs4970405
1 1049950 rs12726255 A G . PASS AF=0.1394 ES:SE:LP:AF:ID 0.1882:0.0853:1.56193:0.1394:rs12726255
1 1053452 rs4970409 G A . PASS AF=0.0985 ES:SE:LP:AF:ID 0.1218:0.1062:0.599808:0.0985:rs4970409
1 1060174 rs7548798 C T . PASS AF=0.3298 ES:SE:LP:AF:ID -0.2519:0.0865:2.4443:0.3298:rs7548798
1 1060235 rs7540009 G A . PASS AF=0.0366 ES:SE:LP:AF:ID 0.2875:0.1934:0.862646:0.0366:rs7540009
1 1060608 rs17160824 G A . PASS AF=0.115 ES:SE:LP:AF:ID 0.1261:0.1001:0.682354:0.115:rs17160824
1 1061115 rs17160826 T C . PASS AF=0.1089 ES:SE:LP:AF:ID 0.1078:0.1019:0.537752:0.1089:rs17160826
1 1061152 rs12748370 T C . PASS AF=0.1075 ES:SE:LP:AF:ID 0.0895:0.1039:0.410497:0.1075:rs12748370
1 1061166 rs11807848 T C . PASS AF=0.4046 ES:SE:LP:AF:ID -0.1047:0.0695:0.880085:0.4046:rs11807848
1 1062015 rs9659914 C T . PASS AF=0.0356 ES:SE:LP:AF:ID 0.3047:0.1988:0.902049:0.0356:rs9659914