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/31049aaf-ed05-4c04-873b-12a2ec594d32/call-vcf/inputs/562856129/upload.txt.gz --id ieu-b-14 --json /data/cromwell-executions/qc/31049aaf-ed05-4c04-873b-12a2ec594d32/call-vcf/inputs/562856129/ieu-b-14_data.json --ref /data/cromwell-executions/qc/31049aaf-ed05-4c04-873b-12a2ec594d32/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/31049aaf-ed05-4c04-873b-12a2ec594d32/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-14/ieu-b-14.vcf.gz --rm_chr_prefix --cohort_cases 803 --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/31049aaf-ed05-4c04-873b-12a2ec594d32/call-ldsc/inputs/562856129/ieu-b-14.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-14/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Fri Jun 26 15:31:42 2020
Reading summary statistics from /data/cromwell-executions/qc/31049aaf-ed05-4c04-873b-12a2ec594d32/call-ldsc/inputs/562856129/ieu-b-14.vcf.gz ...
Read summary statistics for 4948701 SNPs.
Dropped 11749 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, 947276 SNPs remain.
After merging with regression SNP LD, 947276 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0526 (0.0191)
Lambda GC: 1.1045
Mean Chi^2: 1.1117
Intercept: 1.0756 (0.0096)
Ratio: 0.6768 (0.0856)
Analysis finished at Fri Jun 26 15:32:52 2020
Total time elapsed: 1.0m:10.3sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9302,
"inflation_factor": 1.0966,
"mean_EFFECT": 0.0001,
"n": "-Inf",
"n_snps": 4948714,
"n_clumped_hits": 1,
"n_p_sig": 25,
"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": 29692,
"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": 947276,
"ldsc_nsnp_merge_regression_ld": 947276,
"ldsc_observed_scale_h2_beta": 0.0526,
"ldsc_observed_scale_h2_se": 0.0191,
"ldsc_intercept_beta": 1.0756,
"ldsc_intercept_se": 0.0096,
"ldsc_lambda_gc": 1.1045,
"ldsc_mean_chisq": 1.1117,
"ldsc_ratio": 0.6768
}
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 | TRUE |
| 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 | 4948711 | 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 | 4948714 | 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 | 8.637404e+00 | 5.866381e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.200000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.979477e+07 | 5.501312e+07 | 3.30120e+04 | 3.477162e+07 | 7.128607e+07 | 1.144270e+08 | 2.492190e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 9.340000e-05 | 2.632100e-03 | -3.21779e-02 | -1.369200e-03 | 3.490000e-05 | 1.460600e-03 | 3.483790e-02 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.277600e-03 | 1.083400e-03 | 1.17010e-03 | 1.530100e-03 | 1.839900e-03 | 2.598200e-03 | 7.430900e-03 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.860723e-01 | 2.925482e-01 | 0.00000e+00 | 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 | 4.860732e-01 | 2.925225e-01 | 0.00000e+00 | 2.290137e-01 | 4.813224e-01 | 7.392211e-01 | 9.999999e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.082420e-01 | 2.579571e-01 | 1.00004e-02 | 9.079010e-02 | 2.281290e-01 | 4.785468e-01 | 9.899980e-01 | ▇▃▂▂▁ |
| numeric | AF_reference | 29692 | 0.9940001 | NA | NA | NA | NA | NA | NA | NA | 3.093838e-01 | 2.467430e-01 | 1.99700e-04 | 1.052320e-01 | 2.394170e-01 | 4.704470e-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 | -0.0031365 | 0.0019615 | 0.1100001 | 0.1098159 | 0.1633560 | 0.3156950 | NA |
| 1 | 1030565 | rs6687776 | C | T | -0.0034131 | 0.0019593 | 0.0819993 | 0.0815085 | 0.1631710 | 0.3067090 | NA |
| 1 | 1030633 | rs6678318 | G | A | -0.0034137 | 0.0019593 | 0.0810009 | 0.0814607 | 0.1631780 | 0.3065100 | NA |
| 1 | 1031973 | rs9651270 | C | T | -0.0036382 | 0.0019917 | 0.0680002 | 0.0677435 | 0.1598460 | 0.3107030 | NA |
| 1 | 1033596 | rs6604964 | T | C | -0.0035643 | 0.0019932 | 0.0739997 | 0.0737486 | 0.1597180 | 0.3117010 | NA |
| 1 | 1033670 | rs6604966 | T | C | -0.0035258 | 0.0019940 | 0.0769999 | 0.0770210 | 0.1596780 | 0.3158950 | NA |
| 1 | 1033680 | rs6604967 | T | A | -0.0035722 | 0.0019940 | 0.0729995 | 0.0732092 | 0.1596580 | 0.3117010 | NA |
| 1 | 1033994 | rs6698368 | C | T | -0.0035736 | 0.0019935 | 0.0729995 | 0.0730292 | 0.1597210 | 0.3115020 | NA |
| 1 | 1034200 | rs77977351 | T | C | -0.0035793 | 0.0019936 | 0.0729995 | 0.0725909 | 0.1597270 | 0.3115020 | NA |
| 1 | 1036601 | rs72910156 | C | T | 0.0038372 | 0.0047257 | 0.4199997 | 0.4167949 | 0.0237643 | 0.0399361 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 139314056 | rs5955415 | C | G | -0.0017688 | 0.0020339 | 0.3800004 | 0.3844773 | 0.096387 | 0.125033 | NA |
| 23 | 139314798 | rs62609008 | C | A | -0.0015938 | 0.0020424 | 0.4400003 | 0.4351727 | 0.095486 | 0.106755 | NA |
| 23 | 139315107 | rs62609010 | T | A | -0.0014838 | 0.0020410 | 0.4700002 | 0.4672226 | 0.095583 | 0.107020 | NA |
| 23 | 139316769 | rs73230748 | T | C | -0.0016085 | 0.0020372 | 0.4299995 | 0.4297908 | 0.095973 | 0.121060 | NA |
| 23 | 139317055 | rs62609011 | C | A | -0.0015152 | 0.0020368 | 0.4600002 | 0.4569371 | 0.096032 | 0.116026 | NA |
| 23 | 139317165 | rs28877369 | C | G | -0.0017209 | 0.0020378 | 0.4000000 | 0.3983782 | 0.095924 | 0.116291 | NA |
| 23 | 139317337 | rs55757628 | A | G | -0.0016558 | 0.0020405 | 0.4199997 | 0.4170988 | 0.095637 | 0.107285 | NA |
| 23 | 139319949 | rs140616281 | A | G | -0.0016656 | 0.0020422 | 0.4100001 | 0.4147481 | 0.095560 | 0.116291 | NA |
| 23 | 139320136 | rs76621315 | C | G | -0.0016207 | 0.0020360 | 0.4299995 | 0.4260309 | 0.096144 | 0.114437 | NA |
| 23 | 139325995 | rs62609013 | G | A | -0.0015876 | 0.0020381 | 0.4400003 | 0.4360128 | 0.095950 | 0.101987 | NA |
bcf preview
1 1029805 rs891281851 A G . PASS AF=0.163356 ES:SE:LP:AF:ID -0.00313648:0.0019615:0.958607:0.163356:rs891281851
1 1030565 rs6687776 C T . PASS AF=0.163171 ES:SE:LP:AF:ID -0.0034131:0.0019593:1.08619:0.163171:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.163178 ES:SE:LP:AF:ID -0.00341367:0.00195932:1.09151:0.163178:rs6678318
1 1031973 rs9651270 C T . PASS AF=0.159846 ES:SE:LP:AF:ID -0.00363822:0.00199168:1.16749:0.159846:rs9651270
1 1033596 rs6604964 T C . PASS AF=0.159718 ES:SE:LP:AF:ID -0.00356427:0.00199325:1.13077:0.159718:rs6604964
1 1033670 rs1370950991 T C . PASS AF=0.159678 ES:SE:LP:AF:ID -0.00352585:0.00199399:1.11351:0.159678:rs1370950991
1 1033680 rs1370950991 T A . PASS AF=0.159658 ES:SE:LP:AF:ID -0.00357221:0.00199395:1.13668:0.159658:rs1370950991
1 1033994 rs6698368 C T . PASS AF=0.159721 ES:SE:LP:AF:ID -0.00357359:0.00199347:1.13668:0.159721:rs6698368
1 1034200 rs77977351 T C . PASS AF=0.159727 ES:SE:LP:AF:ID -0.00357928:0.00199359:1.13668:0.159727:rs77977351
1 1036601 rs72910156 C T . PASS AF=0.0237643 ES:SE:LP:AF:ID 0.00383725:0.00472571:0.376751:0.0237643:rs72910156
1 1036860 rs11579922 A C . PASS AF=0.126832 ES:SE:LP:AF:ID -0.00277395:0.00217685:0.69897:0.126832:rs11579922
1 1036959 rs1162868282 T C . PASS AF=0.112852 ES:SE:LP:AF:ID -0.00360799:0.00226921:0.958607:0.112852:rs1162868282
1 1037303 rs11260592 T C . PASS AF=0.140225 ES:SE:LP:AF:ID -0.00157524:0.00206251:0.346787:0.140225:rs11260592
1 1037313 rs11260593 A G . PASS AF=0.140332 ES:SE:LP:AF:ID -0.00141293:0.0020625:0.309804:0.140332:rs11260593
1 1037367 rs11260594 G A . PASS AF=0.14023 ES:SE:LP:AF:ID -0.00154588:0.00206277:0.346787:0.14023:rs11260594
1 1038088 rs66622470 G C . PASS AF=0.140295 ES:SE:LP:AF:ID -0.00159045:0.0020615:0.356547:0.140295:rs66622470
1 1039098 rs11260595 C A . PASS AF=0.0241893 ES:SE:LP:AF:ID 0.00518924:0.00467328:0.568636:0.0241893:rs11260595
1 1039268 rs9329410 T C . PASS AF=0.140517 ES:SE:LP:AF:ID -0.00149709:0.00205883:0.327902:0.140517:rs9329410
1 1039817 rs1205065516 A G . PASS AF=0.140292 ES:SE:LP:AF:ID -0.00211829:0.00206137:0.522879:0.140292:rs1205065516
1 1040026 rs6671356 T C . PASS AF=0.140804 ES:SE:LP:AF:ID -0.00155387:0.00205592:0.346787:0.140804:rs6671356
1 1040472 rs6664124 C T . PASS AF=0.140579 ES:SE:LP:AF:ID -0.00217315:0.00205846:0.537602:0.140579:rs6664124
1 1040794 rs6687681 G A . PASS AF=0.140541 ES:SE:LP:AF:ID -0.00227742:0.00205873:0.568636:0.140541:rs6687681
1 1040824 rs6656379 T C . PASS AF=0.140734 ES:SE:LP:AF:ID -0.00198152:0.00205751:0.468521:0.140734:rs6656379
1 1040985 rs6697379 C G . PASS AF=0.14053 ES:SE:LP:AF:ID -0.00217325:0.0020587:0.537602:0.14053:rs6697379
1 1041700 rs6604968 A G . PASS AF=0.140595 ES:SE:LP:AF:ID -0.00263196:0.0020584:0.69897:0.140595:rs6604968
1 1041786 rs6604969 T C . PASS AF=0.140592 ES:SE:LP:AF:ID -0.00272335:0.00205852:0.721246:0.140592:rs6604969
1 1042483 rs12733365 C T . PASS AF=0.140472 ES:SE:LP:AF:ID -0.00262368:0.00205906:0.69897:0.140472:rs12733365
1 1042527 rs1486993720 G C . PASS AF=0.112689 ES:SE:LP:AF:ID -0.00326145:0.00227037:0.823909:0.112689:rs1486993720
1 1042673 rs897825316 C T . PASS AF=0.141543 ES:SE:LP:AF:ID -0.00295511:0.00206527:0.823909:0.141543:rs897825316
1 1042927 rs4970354 G T . PASS AF=0.140458 ES:SE:LP:AF:ID -0.00261697:0.0020589:0.69897:0.140458:rs4970354
1 1043053 rs4970355 A G . PASS AF=0.140386 ES:SE:LP:AF:ID -0.00260819:0.00205935:0.677781:0.140386:rs4970355
1 1045473 rs11586034 G A . PASS AF=0.111889 ES:SE:LP:AF:ID -0.0032224:0.00227871:0.79588:0.111889:rs11586034
1 1046073 rs11590188 C A . PASS AF=0.138668 ES:SE:LP:AF:ID -0.00329957:0.00207266:0.958607:0.138668:rs11590188
1 1046164 rs386627439 C T . PASS AF=0.140421 ES:SE:LP:AF:ID -0.00271887:0.00205918:0.721246:0.140421:rs386627439
1 1046717 rs34820586 G C . PASS AF=0.112751 ES:SE:LP:AF:ID -0.00327712:0.00226983:0.823909:0.112751:rs34820586
1 1046861 rs12723165 G A . PASS AF=0.112742 ES:SE:LP:AF:ID -0.00327271:0.0022698:0.823909:0.112742:rs12723165
1 1047374 rs12743678 T A . PASS AF=0.14005 ES:SE:LP:AF:ID -0.00261167:0.0020615:0.677781:0.14005:rs12743678
1 1048501 rs7518814 G A . PASS AF=0.138694 ES:SE:LP:AF:ID -0.00314625:0.00207225:0.886057:0.138694:rs7518814
1 1048955 rs4970405 A G . PASS AF=0.104695 ES:SE:LP:AF:ID -0.00209411:0.00234333:0.431798:0.104695:rs4970405
1 1048989 rs4970406 A G . PASS AF=0.113603 ES:SE:LP:AF:ID -0.00248694:0.00226487:0.568636:0.113603:rs4970406
1 1049083 rs4970407 C A . PASS AF=0.112755 ES:SE:LP:AF:ID -0.00273364:0.0022698:0.638272:0.112755:rs4970407
1 1049950 rs12726255 A G . PASS AF=0.138972 ES:SE:LP:AF:ID -0.00229902:0.00207368:0.568636:0.138972:rs12726255
1 1052946 rs12755848 G T . PASS AF=0.111757 ES:SE:LP:AF:ID -0.00254798:0.00228432:0.585027:0.111757:rs12755848
1 1053452 rs4970409 G A . PASS AF=0.111755 ES:SE:LP:AF:ID -0.00260152:0.00228413:0.60206:0.111755:rs4970409
1 1053670 rs4970410 G A . PASS AF=0.137842 ES:SE:LP:AF:ID -0.00204436:0.00208476:0.481486:0.137842:rs4970410
1 1053724 rs4970411 A G . PASS AF=0.137417 ES:SE:LP:AF:ID -0.00220979:0.00208826:0.537602:0.137417:rs4970411
1 1054552 rs12567697 G A . PASS AF=0.110773 ES:SE:LP:AF:ID -0.00261124:0.00229432:0.585027:0.110773:rs12567697
1 1054893 rs4970412 T C . PASS AF=0.137702 ES:SE:LP:AF:ID -0.00194605:0.00208581:0.455932:0.137702:rs4970412
1 1055653 rs34808604 C G . PASS AF=0.110944 ES:SE:LP:AF:ID -0.00240369:0.00229236:0.537602:0.110944:rs34808604
1 1055797 rs76744376 A G . PASS AF=0.111454 ES:SE:LP:AF:ID -0.00239132:0.0022891:0.522879:0.111454:rs76744376