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/2b8fd4f0-efb4-412f-a577-509ce6e49890/call-vcf/inputs/562856127/upload.txt.gz --id ieu-b-12 --json /data/cromwell-executions/qc/2b8fd4f0-efb4-412f-a577-509ce6e49890/call-vcf/inputs/562856127/ieu-b-12_data.json --ref /data/cromwell-executions/qc/2b8fd4f0-efb4-412f-a577-509ce6e49890/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/2b8fd4f0-efb4-412f-a577-509ce6e49890/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-12/ieu-b-12.vcf.gz --rm_chr_prefix --cohort_cases 415 --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/2b8fd4f0-efb4-412f-a577-509ce6e49890/call-ldsc/inputs/562856127/ieu-b-12.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-12/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Fri Jun 26 15:29:18 2020
Reading summary statistics from /data/cromwell-executions/qc/2b8fd4f0-efb4-412f-a577-509ce6e49890/call-ldsc/inputs/562856127/ieu-b-12.vcf.gz ...
Read summary statistics for 4986327 SNPs.
Dropped 11903 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, 951458 SNPs remain.
After merging with regression SNP LD, 951458 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0709 (0.0178)
Lambda GC: 1.0902
Mean Chi^2: 1.0848
Intercept: 1.0386 (0.0089)
Ratio: 0.4549 (0.105)
Analysis finished at Fri Jun 26 15:30:49 2020
Total time elapsed: 1.0m:30.97sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9302,
"inflation_factor": 1.0966,
"mean_EFFECT": -0.0001,
"n": "-Inf",
"n_snps": 4986340,
"n_clumped_hits": 0,
"n_p_sig": 0,
"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": 29930,
"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": 951458,
"ldsc_nsnp_merge_regression_ld": 951458,
"ldsc_observed_scale_h2_beta": 0.0709,
"ldsc_observed_scale_h2_se": 0.0178,
"ldsc_intercept_beta": 1.0386,
"ldsc_intercept_se": 0.0089,
"ldsc_lambda_gc": 1.0902,
"ldsc_mean_chisq": 1.0848,
"ldsc_ratio": 0.4552
}
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 | 4986336 | 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 | 4986340 | 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 | 8.645322e+00 | 5.872666e+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 | 7.978939e+07 | 5.501088e+07 | 3.30120e+04 | 3.477034e+07 | 7.128492e+07 | 1.143940e+08 | 2.492190e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -6.570000e-05 | 2.074900e-03 | -1.67760e-02 | -1.202900e-03 | -6.830000e-05 | 1.066900e-03 | 2.486410e-02 | ▁▇▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.832200e-03 | 8.743000e-04 | 9.37900e-04 | 1.227800e-03 | 1.478400e-03 | 2.093000e-03 | 5.961000e-03 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.880105e-01 | 2.909011e-01 | 1.00000e-07 | 2.300001e-01 | 4.799997e-01 | 7.400005e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.880122e-01 | 2.908761e-01 | 1.00000e-07 | 2.342805e-01 | 4.828523e-01 | 7.394842e-01 | 9.999996e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.075408e-01 | 2.582665e-01 | 1.00004e-02 | 8.992100e-02 | 2.269470e-01 | 4.776580e-01 | 9.899970e-01 | ▇▃▂▂▁ |
| numeric | AF_reference | 29930 | 0.9939976 | NA | NA | NA | NA | NA | NA | NA | 3.087892e-01 | 2.468718e-01 | 1.99700e-04 | 1.046330e-01 | 2.384190e-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 | -0.0006763 | 0.0015692 | 0.6700003 | 0.6664554 | 0.1636760 | 0.3156950 | NA |
| 1 | 1030565 | rs6687776 | C | T | 0.0010007 | 0.0015745 | 0.5300002 | 0.5250381 | 0.1637620 | 0.3067090 | NA |
| 1 | 1030633 | rs6678318 | G | A | 0.0010012 | 0.0015745 | 0.5199996 | 0.5248751 | 0.1637690 | 0.3065100 | NA |
| 1 | 1031973 | rs9651270 | C | T | -0.0006272 | 0.0015928 | 0.6899999 | 0.6937294 | 0.1602360 | 0.3107030 | NA |
| 1 | 1033596 | rs6604964 | T | C | -0.0006034 | 0.0015940 | 0.7099994 | 0.7050559 | 0.1601010 | 0.3117010 | NA |
| 1 | 1033670 | rs6604966 | T | C | -0.0005986 | 0.0015946 | 0.7099994 | 0.7073802 | 0.1600540 | 0.3158950 | NA |
| 1 | 1033680 | rs6604967 | T | A | -0.0005987 | 0.0015946 | 0.7099994 | 0.7073269 | 0.1600400 | 0.3117010 | NA |
| 1 | 1033994 | rs6698368 | C | T | -0.0006075 | 0.0015942 | 0.6999999 | 0.7031496 | 0.1601040 | 0.3115020 | NA |
| 1 | 1034200 | rs77977351 | T | C | -0.0006062 | 0.0015943 | 0.6999999 | 0.7037994 | 0.1601100 | 0.3115020 | NA |
| 1 | 1036601 | rs72910156 | C | T | -0.0001882 | 0.0038346 | 0.9599999 | 0.9608614 | 0.0236323 | 0.0399361 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 139314056 | rs5955415 | C | G | 0.0003609 | 0.0016340 | 0.8300000 | 0.8252065 | 0.096653 | 0.125033 | NA |
| 23 | 139314798 | rs62609008 | C | A | 0.0003465 | 0.0016409 | 0.8300000 | 0.8327787 | 0.095736 | 0.106755 | NA |
| 23 | 139315107 | rs62609010 | T | A | 0.0003300 | 0.0016399 | 0.8400000 | 0.8405216 | 0.095825 | 0.107020 | NA |
| 23 | 139316769 | rs73230748 | T | C | 0.0003348 | 0.0016368 | 0.8400000 | 0.8379245 | 0.096222 | 0.121060 | NA |
| 23 | 139317055 | rs62609011 | C | A | 0.0002065 | 0.0016366 | 0.9000000 | 0.8996027 | 0.096248 | 0.116026 | NA |
| 23 | 139317165 | rs28877369 | C | G | 0.0002216 | 0.0016372 | 0.8900000 | 0.8923297 | 0.096172 | 0.116291 | NA |
| 23 | 139317337 | rs55757628 | A | G | 0.0003416 | 0.0016394 | 0.8300000 | 0.8349495 | 0.095897 | 0.107285 | NA |
| 23 | 139319949 | rs140616281 | A | G | 0.0001967 | 0.0016409 | 0.9000000 | 0.9045717 | 0.095801 | 0.116291 | NA |
| 23 | 139320136 | rs76621315 | C | G | 0.0002051 | 0.0016359 | 0.9000000 | 0.9002096 | 0.096371 | 0.114437 | NA |
| 23 | 139325995 | rs62609013 | G | A | 0.0004721 | 0.0016374 | 0.7700005 | 0.7731139 | 0.096216 | 0.101987 | NA |
bcf preview
1 1029805 rs891281851 A G . PASS AF=0.163676 ES:SE:LP:AF:ID -0.000676336:0.00156916:0.173925:0.163676:rs891281851
1 1030565 rs6687776 C T . PASS AF=0.163762 ES:SE:LP:AF:ID 0.00100075:0.0015745:0.275724:0.163762:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.163769 ES:SE:LP:AF:ID 0.00100115:0.00157451:0.283997:0.163769:rs6678318
1 1031973 rs9651270 C T . PASS AF=0.160236 ES:SE:LP:AF:ID -0.000627247:0.00159281:0.161151:0.160236:rs9651270
1 1033596 rs6604964 T C . PASS AF=0.160101 ES:SE:LP:AF:ID -0.000603355:0.00159405:0.148742:0.160101:rs6604964
1 1033670 rs1370950991 T C . PASS AF=0.160054 ES:SE:LP:AF:ID -0.000598591:0.00159464:0.148742:0.160054:rs1370950991
1 1033680 rs1370950991 T A . PASS AF=0.16004 ES:SE:LP:AF:ID -0.000598694:0.00159461:0.148742:0.16004:rs1370950991
1 1033994 rs6698368 C T . PASS AF=0.160104 ES:SE:LP:AF:ID -0.000607517:0.00159423:0.154902:0.160104:rs6698368
1 1034200 rs77977351 T C . PASS AF=0.16011 ES:SE:LP:AF:ID -0.000606159:0.00159433:0.154902:0.16011:rs77977351
1 1036601 rs72910156 C T . PASS AF=0.0236323 ES:SE:LP:AF:ID -0.000188172:0.00383456:0.0177288:0.0236323:rs72910156
1 1036860 rs11579922 A C . PASS AF=0.126695 ES:SE:LP:AF:ID -0.00167161:0.00174546:0.468521:0.126695:rs11579922
1 1036959 rs1162868282 T C . PASS AF=0.112959 ES:SE:LP:AF:ID -0.00122239:0.00181896:0.30103:0.112959:rs1162868282
1 1037303 rs11260592 T C . PASS AF=0.139956 ES:SE:LP:AF:ID -0.00148127:0.00165527:0.431798:0.139956:rs11260592
1 1037313 rs11260593 A G . PASS AF=0.140037 ES:SE:LP:AF:ID -0.0014889:0.00165531:0.431798:0.140037:rs11260593
1 1037367 rs11260594 G A . PASS AF=0.139955 ES:SE:LP:AF:ID -0.00148247:0.00165547:0.431798:0.139955:rs11260594
1 1038088 rs66622470 G C . PASS AF=0.140026 ES:SE:LP:AF:ID -0.00149575:0.00165445:0.431798:0.140026:rs66622470
1 1039098 rs11260595 C A . PASS AF=0.0239679 ES:SE:LP:AF:ID -0.000150155:0.00380154:0.0132283:0.0239679:rs11260595
1 1039268 rs9329410 T C . PASS AF=0.140193 ES:SE:LP:AF:ID -0.00151133:0.00165284:0.443698:0.140193:rs9329410
1 1039817 rs1205065516 A G . PASS AF=0.140094 ES:SE:LP:AF:ID -0.00150305:0.0016538:0.443698:0.140094:rs1205065516
1 1040026 rs6671356 T C . PASS AF=0.140483 ES:SE:LP:AF:ID -0.00156108:0.00165048:0.468521:0.140483:rs6671356
1 1040472 rs6664124 C T . PASS AF=0.140384 ES:SE:LP:AF:ID -0.0015529:0.00165143:0.455932:0.140384:rs6664124
1 1040794 rs6687681 G A . PASS AF=0.14036 ES:SE:LP:AF:ID -0.00154935:0.00165158:0.455932:0.14036:rs6687681
1 1040824 rs6656379 T C . PASS AF=0.140506 ES:SE:LP:AF:ID -0.00157235:0.0016508:0.468521:0.140506:rs6656379
1 1040985 rs6697379 C G . PASS AF=0.140334 ES:SE:LP:AF:ID -0.00154926:0.00165163:0.455932:0.140334:rs6697379
1 1041700 rs6604968 A G . PASS AF=0.140481 ES:SE:LP:AF:ID -0.00151393:0.00165107:0.443698:0.140481:rs6604968
1 1041786 rs6604969 T C . PASS AF=0.140493 ES:SE:LP:AF:ID -0.00151672:0.0016509:0.443698:0.140493:rs6604969
1 1042483 rs12733365 C T . PASS AF=0.140357 ES:SE:LP:AF:ID -0.00154556:0.00165141:0.455932:0.140357:rs12733365
1 1042527 rs1486993720 G C . PASS AF=0.112747 ES:SE:LP:AF:ID -0.0013381:0.0018206:0.337242:0.112747:rs1486993720
1 1042673 rs897825316 C T . PASS AF=0.141555 ES:SE:LP:AF:ID -0.000879578:0.00165606:0.221849:0.141555:rs897825316
1 1042927 rs4970354 G T . PASS AF=0.140343 ES:SE:LP:AF:ID -0.00154424:0.00165128:0.455932:0.140343:rs4970354
1 1043053 rs4970355 A G . PASS AF=0.14027 ES:SE:LP:AF:ID -0.0015267:0.00165164:0.443698:0.14027:rs4970355
1 1045473 rs11586034 G A . PASS AF=0.111959 ES:SE:LP:AF:ID -0.00122235:0.00182725:0.30103:0.111959:rs11586034
1 1046073 rs11590188 C A . PASS AF=0.138707 ES:SE:LP:AF:ID -0.00158882:0.00166136:0.468521:0.138707:rs11590188
1 1046164 rs386627439 C T . PASS AF=0.140319 ES:SE:LP:AF:ID -0.00153803:0.00165144:0.455932:0.140319:rs386627439
1 1046717 rs34820586 G C . PASS AF=0.11281 ES:SE:LP:AF:ID -0.00134374:0.00182016:0.337242:0.11281:rs34820586
1 1046861 rs12723165 G A . PASS AF=0.112801 ES:SE:LP:AF:ID -0.00134287:0.00182014:0.337242:0.112801:rs12723165
1 1047374 rs12743678 T A . PASS AF=0.139939 ES:SE:LP:AF:ID -0.00150458:0.0016533:0.443698:0.139939:rs12743678
1 1048501 rs7518814 G A . PASS AF=0.138712 ES:SE:LP:AF:ID -0.00159134:0.00166137:0.468521:0.138712:rs7518814
1 1048955 rs4970405 A G . PASS AF=0.104605 ES:SE:LP:AF:ID -0.00143764:0.00188059:0.356547:0.104605:rs4970405
1 1048989 rs4970406 A G . PASS AF=0.113492 ES:SE:LP:AF:ID -0.00173063:0.00181779:0.468521:0.113492:rs4970406
1 1049083 rs4970407 C A . PASS AF=0.112698 ES:SE:LP:AF:ID -0.00168263:0.00182164:0.443698:0.112698:rs4970407
1 1049950 rs12726255 A G . PASS AF=0.138742 ES:SE:LP:AF:ID -0.00197461:0.00166406:0.619789:0.138742:rs12726255
1 1052946 rs12755848 G T . PASS AF=0.111707 ES:SE:LP:AF:ID -0.00158333:0.00183317:0.408935:0.111707:rs12755848
1 1053452 rs4970409 G A . PASS AF=0.11171 ES:SE:LP:AF:ID -0.0015873:0.00183302:0.408935:0.11171:rs4970409
1 1053670 rs4970410 G A . PASS AF=0.137612 ES:SE:LP:AF:ID -0.00198012:0.00167287:0.619789:0.137612:rs4970410
1 1053724 rs4970411 A G . PASS AF=0.137227 ES:SE:LP:AF:ID -0.00193231:0.00167548:0.60206:0.137227:rs4970411
1 1054552 rs12567697 G A . PASS AF=0.110681 ES:SE:LP:AF:ID -0.00197628:0.0018419:0.552842:0.110681:rs12567697
1 1054893 rs4970412 T C . PASS AF=0.137396 ES:SE:LP:AF:ID -0.00218505:0.00167439:0.721246:0.137396:rs4970412
1 1055653 rs34808604 C G . PASS AF=0.110824 ES:SE:LP:AF:ID -0.00199544:0.00184039:0.552842:0.110824:rs34808604
1 1055797 rs76744376 A G . PASS AF=0.111305 ES:SE:LP:AF:ID -0.00202932:0.00183782:0.568636:0.111305:rs76744376