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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"Gwas2VCF_command": "--data /data/cromwell-executions/qc/815ed387-bf5e-4297-ad06-fb6d61a5b68e/call-vcf/inputs/562856132/upload.txt.gz --id ieu-b-17 --json /data/cromwell-executions/qc/815ed387-bf5e-4297-ad06-fb6d61a5b68e/call-vcf/inputs/562856132/ieu-b-17_data.json --ref /data/cromwell-executions/qc/815ed387-bf5e-4297-ad06-fb6d61a5b68e/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/815ed387-bf5e-4297-ad06-fb6d61a5b68e/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-17/ieu-b-17.vcf.gz --rm_chr_prefix --cohort_cases 1181 --cohort_controls 29677; 1.2.1",
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}
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 /data/cromwell-executions/qc/815ed387-bf5e-4297-ad06-fb6d61a5b68e/call-ldsc/inputs/562856132/ieu-b-17.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-17/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Fri Jun 26 15:41:59 2020
Reading summary statistics from /data/cromwell-executions/qc/815ed387-bf5e-4297-ad06-fb6d61a5b68e/call-ldsc/inputs/562856132/ieu-b-17.vcf.gz ...
Read summary statistics for 4983212 SNPs.
Dropped 11883 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 950987 SNPs remain.
After merging with regression SNP LD, 950987 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1522 (0.0237)
Lambda GC: 1.1395
Mean Chi^2: 1.1542
Intercept: 1.0497 (0.0106)
Ratio: 0.3222 (0.0691)
Analysis finished at Fri Jun 26 15:42:47 2020
Total time elapsed: 48.43sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9303,
"inflation_factor": 1.1474,
"mean_EFFECT": -0.0001,
"n": "-Inf",
"n_snps": 4983225,
"n_clumped_hits": 1,
"n_p_sig": 42,
"n_mono": 0,
"n_ns": 0,
"n_mac": 0,
"is_snpid_unique": true,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 29911,
"n_est": "NA",
"ratio_se_n": "NA",
"mean_diff": "NaN",
"ratio_diff": "NaN",
"sd_y_est1": "NA",
"sd_y_est2": "NA",
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 950987,
"ldsc_nsnp_merge_regression_ld": 950987,
"ldsc_observed_scale_h2_beta": 0.1522,
"ldsc_observed_scale_h2_se": 0.0237,
"ldsc_intercept_beta": 1.0497,
"ldsc_intercept_se": 0.0106,
"ldsc_lambda_gc": 1.1395,
"ldsc_mean_chisq": 1.1542,
"ldsc_ratio": 0.3223
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| is_snpid_non_unique | FALSE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | FALSE |
| n_p_sig | FALSE |
| miss_EFFECT | FALSE |
| miss_SE | FALSE |
| miss_PVAL | FALSE |
| ldsc_ratio | FALSE |
| ldsc_intercept_beta | FALSE |
| 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 | 1 | 0.9999998 | 3 | 35 | 0 | 4983221 | 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 | 4983225 | 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 | 8.644360e+00 | 5.871952e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.979436e+07 | 5.500323e+07 | 3.30120e+04 | 3.478181e+07 | 7.129471e+07 | 1.143980e+08 | 2.492190e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.196000e-04 | 3.402300e-03 | -3.17390e-02 | -1.964800e-03 | -1.176000e-04 | 1.727000e-03 | 4.806390e-02 | ▁▇▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.921000e-03 | 1.394800e-03 | 1.49750e-03 | 1.956500e-03 | 2.356500e-03 | 3.337000e-03 | 9.512900e-03 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.807270e-01 | 2.935319e-01 | 0.00000e+00 | 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 | 4.807257e-01 | 2.935046e-01 | 0.00000e+00 | 2.226531e-01 | 4.736722e-01 | 7.343870e-01 | 9.999997e-01 | ▇▇▇▇▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.074961e-01 | 2.583313e-01 | 1.00004e-02 | 8.984280e-02 | 2.268260e-01 | 4.776390e-01 | 9.899980e-01 | ▇▃▂▂▁ |
| numeric | AF_reference | 29911 | 0.9939977 | NA | NA | NA | NA | NA | NA | NA | 3.087596e-01 | 2.469170e-01 | 1.99700e-04 | 1.046330e-01 | 2.382190e-01 | 4.696490e-01 | 1.000000e+00 | ▇▅▃▂▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1029805 | rs6689308 | A | G | 0.0004870 | 0.0025017 | 0.8499999 | 0.8456582 | 0.1637790 | 0.3156950 | NA |
| 1 | 1030565 | rs6687776 | C | T | 0.0009507 | 0.0025210 | 0.7099994 | 0.7060907 | 0.1636840 | 0.3067090 | NA |
| 1 | 1030633 | rs6678318 | G | A | 0.0009446 | 0.0025211 | 0.7099994 | 0.7079045 | 0.1636910 | 0.3065100 | NA |
| 1 | 1031973 | rs9651270 | C | T | 0.0012112 | 0.0025392 | 0.6300007 | 0.6333410 | 0.1604300 | 0.3107030 | NA |
| 1 | 1033596 | rs6604964 | T | C | 0.0012403 | 0.0025411 | 0.6300007 | 0.6254891 | 0.1602990 | 0.3117010 | NA |
| 1 | 1033670 | rs6604966 | T | C | 0.0013575 | 0.0025420 | 0.5900000 | 0.5933248 | 0.1602660 | 0.3158950 | NA |
| 1 | 1033680 | rs6604967 | T | A | 0.0012613 | 0.0025419 | 0.6200004 | 0.6197674 | 0.1602400 | 0.3117010 | NA |
| 1 | 1033994 | rs6698368 | C | T | 0.0013871 | 0.0025413 | 0.5900000 | 0.5851955 | 0.1603220 | 0.3115020 | NA |
| 1 | 1034200 | rs77977351 | T | C | 0.0014472 | 0.0025414 | 0.5700002 | 0.5690531 | 0.1603340 | 0.3115020 | NA |
| 1 | 1036601 | rs72910156 | C | T | 0.0000221 | 0.0061509 | 1.0000000 | 0.9971285 | 0.0235736 | 0.0399361 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 139284404 | rs430026 | G | A | 0.0006038 | 0.0015533 | 0.6999999 | 0.6974766 | 0.415249 | 0.308609 | NA |
| 23 | 139287243 | rs412811 | T | C | 0.0005599 | 0.0015334 | 0.7199992 | 0.7150195 | 0.444821 | 0.460397 | NA |
| 23 | 139288359 | rs367697 | C | T | 0.0011441 | 0.0015128 | 0.4500005 | 0.4494566 | 0.480606 | 0.488477 | NA |
| 23 | 139289049 | rs387193 | A | G | 0.0010919 | 0.0015359 | 0.4799997 | 0.4771352 | 0.443187 | 0.450331 | NA |
| 23 | 139315107 | rs62609010 | T | A | 0.0013624 | 0.0026310 | 0.5999997 | 0.6045836 | 0.095920 | 0.107020 | NA |
| 23 | 139317055 | rs62609011 | C | A | 0.0017538 | 0.0026249 | 0.5000000 | 0.5040533 | 0.096414 | 0.116026 | NA |
| 23 | 139317165 | rs28877369 | C | G | 0.0017569 | 0.0026258 | 0.5000000 | 0.5034397 | 0.096339 | 0.116291 | NA |
| 23 | 139317337 | rs55757628 | A | G | 0.0014873 | 0.0026300 | 0.5700002 | 0.5717279 | 0.096007 | 0.107285 | NA |
| 23 | 139320136 | rs76621315 | C | G | 0.0016768 | 0.0026237 | 0.5199996 | 0.5227440 | 0.096534 | 0.114437 | NA |
| 23 | 139325995 | rs62609013 | G | A | 0.0012235 | 0.0026268 | 0.6400000 | 0.6413803 | 0.096294 | 0.101987 | NA |
bcf preview
1 1029805 rs891281851 A G . PASS AF=0.163779 ES:SE:LP:AF:ID 0.000486976:0.00250166:0.0705811:0.163779:rs891281851
1 1030565 rs6687776 C T . PASS AF=0.163684 ES:SE:LP:AF:ID 0.000950717:0.00252105:0.148742:0.163684:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.163691 ES:SE:LP:AF:ID 0.000944574:0.00252107:0.148742:0.163691:rs6678318
1 1031973 rs9651270 C T . PASS AF=0.16043 ES:SE:LP:AF:ID 0.00121125:0.00253915:0.200659:0.16043:rs9651270
1 1033596 rs6604964 T C . PASS AF=0.160299 ES:SE:LP:AF:ID 0.00124026:0.00254107:0.200659:0.160299:rs6604964
1 1033670 rs1370950991 T C . PASS AF=0.160266 ES:SE:LP:AF:ID 0.0013575:0.00254202:0.229148:0.160266:rs1370950991
1 1033680 rs1370950991 T A . PASS AF=0.16024 ES:SE:LP:AF:ID 0.00126126:0.00254194:0.207608:0.16024:rs1370950991
1 1033994 rs6698368 C T . PASS AF=0.160322 ES:SE:LP:AF:ID 0.00138706:0.00254128:0.229148:0.160322:rs6698368
1 1034200 rs77977351 T C . PASS AF=0.160334 ES:SE:LP:AF:ID 0.00144722:0.00254145:0.244125:0.160334:rs77977351
1 1036601 rs72910156 C T . PASS AF=0.0235736 ES:SE:LP:AF:ID 2.21364e-05:0.00615087:-0:0.0235736:rs72910156
1 1036860 rs11579922 A C . PASS AF=0.127069 ES:SE:LP:AF:ID 0.00125013:0.00277966:0.187087:0.127069:rs11579922
1 1036959 rs1162868282 T C . PASS AF=0.1133 ES:SE:LP:AF:ID 0.00132946:0.00289555:0.187087:0.1133:rs1162868282
1 1037303 rs11260592 T C . PASS AF=0.14033 ES:SE:LP:AF:ID 0.00135121:0.00263706:0.21467:0.14033:rs11260592
1 1037313 rs11260593 A G . PASS AF=0.140409 ES:SE:LP:AF:ID 0.00135242:0.00263712:0.21467:0.140409:rs11260593
1 1037367 rs11260594 G A . PASS AF=0.140329 ES:SE:LP:AF:ID 0.00134067:0.00263736:0.21467:0.140329:rs11260594
1 1038088 rs66622470 G C . PASS AF=0.140398 ES:SE:LP:AF:ID 0.00132679:0.00263579:0.21467:0.140398:rs66622470
1 1039098 rs11260595 C A . PASS AF=0.0239033 ES:SE:LP:AF:ID 2.78686e-05:0.0060987:-0:0.0239033:rs11260595
1 1039268 rs9329410 T C . PASS AF=0.14056 ES:SE:LP:AF:ID 0.00128086:0.0026333:0.200659:0.14056:rs9329410
1 1039817 rs1205065516 A G . PASS AF=0.140458 ES:SE:LP:AF:ID 0.00126435:0.00263477:0.200659:0.140458:rs1205065516
1 1040026 rs6671356 T C . PASS AF=0.140841 ES:SE:LP:AF:ID 0.00115102:0.00262965:0.180456:0.140841:rs6671356
1 1040472 rs6664124 C T . PASS AF=0.140739 ES:SE:LP:AF:ID 0.00113427:0.00263111:0.173925:0.140739:rs6664124
1 1040794 rs6687681 G A . PASS AF=0.140716 ES:SE:LP:AF:ID 0.00114264:0.00263135:0.180456:0.140716:rs6687681
1 1040824 rs6656379 T C . PASS AF=0.140868 ES:SE:LP:AF:ID 0.00118602:0.00263016:0.187087:0.140868:rs6656379
1 1040985 rs6697379 C G . PASS AF=0.140691 ES:SE:LP:AF:ID 0.00114654:0.00263142:0.180456:0.140691:rs6697379
1 1041700 rs6604968 A G . PASS AF=0.140848 ES:SE:LP:AF:ID 0.00121658:0.00263045:0.19382:0.140848:rs6604968
1 1041786 rs6604969 T C . PASS AF=0.140859 ES:SE:LP:AF:ID 0.00121776:0.00263018:0.19382:0.140859:rs6604969
1 1042483 rs12733365 C T . PASS AF=0.140719 ES:SE:LP:AF:ID 0.00116894:0.00263109:0.180456:0.140719:rs12733365
1 1042527 rs1486993720 G C . PASS AF=0.113058 ES:SE:LP:AF:ID 0.00101945:0.00290003:0.136677:0.113058:rs1486993720
1 1042673 rs897825316 C T . PASS AF=0.141854 ES:SE:LP:AF:ID 0.00131709:0.00263867:0.207608:0.141854:rs897825316
1 1042927 rs4970354 G T . PASS AF=0.140705 ES:SE:LP:AF:ID 0.00117655:0.00263089:0.187087:0.140705:rs4970354
1 1043053 rs4970355 A G . PASS AF=0.140634 ES:SE:LP:AF:ID 0.00120905:0.00263145:0.187087:0.140634:rs4970355
1 1045473 rs11586034 G A . PASS AF=0.112189 ES:SE:LP:AF:ID 0.00046136:0.00291153:0.0604807:0.112189:rs11586034
1 1046073 rs11590188 C A . PASS AF=0.139095 ES:SE:LP:AF:ID 0.00133827:0.00264671:0.21467:0.139095:rs11590188
1 1046164 rs386627439 C T . PASS AF=0.140702 ES:SE:LP:AF:ID 0.0013562:0.00263104:0.21467:0.140702:rs386627439
1 1046717 rs34820586 G C . PASS AF=0.113139 ES:SE:LP:AF:ID 0.00121751:0.00289919:0.173925:0.113139:rs34820586
1 1046861 rs12723165 G A . PASS AF=0.11313 ES:SE:LP:AF:ID 0.00122044:0.00289916:0.173925:0.11313:rs12723165
1 1047374 rs12743678 T A . PASS AF=0.140336 ES:SE:LP:AF:ID 0.00146883:0.00263409:0.236572:0.140336:rs12743678
1 1048501 rs7518814 G A . PASS AF=0.139101 ES:SE:LP:AF:ID 0.00133229:0.00264673:0.21467:0.139101:rs7518814
1 1048955 rs4970405 A G . PASS AF=0.105047 ES:SE:LP:AF:ID 0.00232336:0.00299441:0.356547:0.105047:rs4970405
1 1048989 rs4970406 A G . PASS AF=0.113813 ES:SE:LP:AF:ID 0.000768811:0.00289614:0.102373:0.113813:rs4970406
1 1049083 rs4970407 C A . PASS AF=0.113027 ES:SE:LP:AF:ID 0.000912817:0.00290204:0.124939:0.113027:rs4970407
1 1049950 rs12726255 A G . PASS AF=0.13885 ES:SE:LP:AF:ID -0.00109295:0.00265536:0.167491:0.13885:rs12726255
1 1052946 rs12755848 G T . PASS AF=0.112065 ES:SE:LP:AF:ID 0.0012823:0.00291985:0.180456:0.112065:rs12755848
1 1053452 rs4970409 G A . PASS AF=0.112067 ES:SE:LP:AF:ID 0.00128054:0.00291963:0.180456:0.112067:rs4970409
1 1053670 rs4970410 G A . PASS AF=0.137713 ES:SE:LP:AF:ID -0.00113851:0.00266925:0.173925:0.137713:rs4970410
1 1053724 rs4970411 A G . PASS AF=0.137339 ES:SE:LP:AF:ID -0.000987248:0.00267331:0.148742:0.137339:rs4970411
1 1054552 rs12567697 G A . PASS AF=0.111067 ES:SE:LP:AF:ID 0.00118342:0.00293275:0.161151:0.111067:rs12567697
1 1054893 rs4970412 T C . PASS AF=0.137518 ES:SE:LP:AF:ID -0.00116536:0.00267104:0.180456:0.137518:rs4970412
1 1055653 rs34808604 C G . PASS AF=0.111222 ES:SE:LP:AF:ID 0.0012446:0.00293024:0.173925:0.111222:rs34808604
1 1055797 rs76744376 A G . PASS AF=0.111703 ES:SE:LP:AF:ID 0.00124855:0.00292632:0.173925:0.111703:rs76744376