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/51a78191-9487-491f-bad1-ae9e123740e7/call-vcf/inputs/562856125/upload.txt.gz --id ieu-b-10 --json /data/cromwell-executions/qc/51a78191-9487-491f-bad1-ae9e123740e7/call-vcf/inputs/562856125/ieu-b-10_data.json --ref /data/cromwell-executions/qc/51a78191-9487-491f-bad1-ae9e123740e7/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/51a78191-9487-491f-bad1-ae9e123740e7/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-10/ieu-b-10.vcf.gz --rm_chr_prefix --cohort_cases 9671 --cohort_controls 29677; 1.2.1",
"file_date": "2020-06-26T15:18:33.533994",
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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/51a78191-9487-491f-bad1-ae9e123740e7/call-ldsc/inputs/562856125/ieu-b-10.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-10/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Fri Jun 26 15:25:34 2020
Reading summary statistics from /data/cromwell-executions/qc/51a78191-9487-491f-bad1-ae9e123740e7/call-ldsc/inputs/562856125/ieu-b-10.vcf.gz ...
Read summary statistics for 4862769 SNPs.
Dropped 11434 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, 930582 SNPs remain.
After merging with regression SNP LD, 930582 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0314 (0.0173)
Lambda GC: 1.194
Mean Chi^2: 1.1913
Intercept: 1.1639 (0.0101)
Ratio: 0.8568 (0.0528)
Analysis finished at Fri Jun 26 15:28:10 2020
Total time elapsed: 2.0m:36.81sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9402,
"inflation_factor": 1.1909,
"mean_EFFECT": 0.0007,
"n": "-Inf",
"n_snps": 4862782,
"n_clumped_hits": 1,
"n_p_sig": 4,
"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": 28996,
"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": 930582,
"ldsc_nsnp_merge_regression_ld": 930582,
"ldsc_observed_scale_h2_beta": 0.0314,
"ldsc_observed_scale_h2_se": 0.0173,
"ldsc_intercept_beta": 1.1639,
"ldsc_intercept_se": 0.0101,
"ldsc_lambda_gc": 1.194,
"ldsc_mean_chisq": 1.1913,
"ldsc_ratio": 0.8568
}
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 | 4862779 | 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 | 4862782 | 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 | 8.638433e+00 | 5.865020e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.200000e+01 | 2.30000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.980983e+07 | 5.499637e+07 | 3.30120e+04 | 3.481541e+07 | 7.129924e+07 | 1.144377e+08 | 2.49219e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 6.963000e-04 | 1.619080e-02 | -1.51322e-01 | -8.257000e-03 | 4.211000e-04 | 9.229200e-03 | 1.92876e-01 | ▁▂▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.348290e-02 | 6.379600e-03 | 8.38360e-03 | 9.049900e-03 | 1.092100e-02 | 1.542740e-02 | 8.75774e-02 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.730882e-01 | 2.956290e-01 | 0.00000e+00 | 2.099999e-01 | 4.617001e-01 | 7.300002e-01 | 1.00000e+00 | ▇▆▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.730932e-01 | 2.956302e-01 | 0.00000e+00 | 2.098431e-01 | 4.617308e-01 | 7.300942e-01 | 1.00000e+00 | ▇▇▆▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.062228e-01 | 2.567318e-01 | 2.60000e-03 | 9.060000e-02 | 2.251000e-01 | 4.741000e-01 | 9.90000e-01 | ▇▃▂▂▁ |
| numeric | AF_reference | 28996 | 0.9940372 | NA | NA | NA | NA | NA | NA | NA | 3.074937e-01 | 2.470186e-01 | 1.99700e-04 | 1.034350e-01 | 2.360220e-01 | 4.676520e-01 | 1.00000e+00 | ▇▅▃▂▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1029805 | rs6689308 | A | G | -0.0050973 | 0.0113023 | 0.6520997 | 0.6519907 | 0.1685 | 0.3156950 | NA |
| 1 | 1030565 | rs6687776 | C | T | -0.0023476 | 0.0112865 | 0.8352000 | 0.8352284 | 0.1684 | 0.3067090 | NA |
| 1 | 1030633 | rs6678318 | G | A | -0.0022920 | 0.0112907 | 0.8395000 | 0.8391359 | 0.1683 | 0.3065100 | NA |
| 1 | 1031973 | rs9651270 | C | T | -0.0015743 | 0.0116615 | 0.8923000 | 0.8926114 | 0.1611 | 0.3107030 | NA |
| 1 | 1033596 | rs6604964 | T | C | -0.0014353 | 0.0116692 | 0.9022000 | 0.9021065 | 0.1609 | 0.3117010 | NA |
| 1 | 1033670 | rs6604966 | T | C | -0.0024406 | 0.0116777 | 0.8342000 | 0.8344482 | 0.1608 | 0.3158950 | NA |
| 1 | 1033680 | rs6604967 | T | A | -0.0025221 | 0.0116765 | 0.8292000 | 0.8289873 | 0.1608 | 0.3117010 | NA |
| 1 | 1033994 | rs6698368 | C | T | -0.0025916 | 0.0116739 | 0.8243000 | 0.8243143 | 0.1609 | 0.3115020 | NA |
| 1 | 1034200 | rs77977351 | T | C | -0.0021481 | 0.0116742 | 0.8540001 | 0.8540130 | 0.1609 | 0.3115020 | NA |
| 1 | 1036601 | rs72910156 | C | T | 0.0654638 | 0.0285868 | 0.0219999 | 0.0220213 | 0.0242 | 0.0399361 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 139314056 | rs5955415 | C | G | 0.0065677 | 0.0149265 | 0.6600001 | 0.6599371 | 0.0969 | 0.125033 | NA |
| 23 | 139314798 | rs62609008 | C | A | 0.0076393 | 0.0149791 | 0.6100002 | 0.6100515 | 0.0961 | 0.106755 | NA |
| 23 | 139315107 | rs62609010 | T | A | 0.0082786 | 0.0149703 | 0.5800000 | 0.5802637 | 0.0962 | 0.107020 | NA |
| 23 | 139316769 | rs73230748 | T | C | 0.0096035 | 0.0149354 | 0.5199996 | 0.5202229 | 0.0967 | 0.121060 | NA |
| 23 | 139317055 | rs62609011 | C | A | 0.0096027 | 0.0149343 | 0.5199996 | 0.5202247 | 0.0967 | 0.116026 | NA |
| 23 | 139317165 | rs28877369 | C | G | 0.0078335 | 0.0149495 | 0.5999997 | 0.6002789 | 0.0965 | 0.116291 | NA |
| 23 | 139317337 | rs55757628 | A | G | 0.0072163 | 0.0149717 | 0.6300007 | 0.6298069 | 0.0962 | 0.107285 | NA |
| 23 | 139319949 | rs140616281 | A | G | 0.0082804 | 0.0149735 | 0.5800000 | 0.5802623 | 0.0962 | 0.116291 | NA |
| 23 | 139320136 | rs76621315 | C | G | 0.0082547 | 0.0149272 | 0.5800000 | 0.5802644 | 0.0968 | 0.114437 | NA |
| 23 | 139325995 | rs62609013 | G | A | 0.0080563 | 0.0149467 | 0.5900000 | 0.5898869 | 0.0965 | 0.101987 | NA |
bcf preview
1 1029805 rs891281851 A G . PASS AF=0.1685 ES:SE:LP:AF:ID -0.00509732:0.0113023:0.185686:0.1685:rs891281851
1 1030565 rs6687776 C T . PASS AF=0.1684 ES:SE:LP:AF:ID -0.0023476:0.0112865:0.0782095:0.1684:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.1683 ES:SE:LP:AF:ID -0.002292:0.0112907:0.0759793:0.1683:rs6678318
1 1031973 rs9651270 C T . PASS AF=0.1611 ES:SE:LP:AF:ID -0.00157431:0.0116615:0.0494891:0.1611:rs9651270
1 1033596 rs6604964 T C . PASS AF=0.1609 ES:SE:LP:AF:ID -0.00143532:0.0116692:0.0446972:0.1609:rs6604964
1 1033670 rs1370950991 T C . PASS AF=0.1608 ES:SE:LP:AF:ID -0.00244064:0.0116777:0.0787298:0.1608:rs1370950991
1 1033680 rs1370950991 T A . PASS AF=0.1608 ES:SE:LP:AF:ID -0.00252213:0.0116765:0.0813407:0.1608:rs1370950991
1 1033994 rs6698368 C T . PASS AF=0.1609 ES:SE:LP:AF:ID -0.0025916:0.0116739:0.0839147:0.1609:rs6698368
1 1034200 rs77977351 T C . PASS AF=0.1609 ES:SE:LP:AF:ID -0.00214806:0.0116742:0.0685421:0.1609:rs77977351
1 1036601 rs72910156 C T . PASS AF=0.0242 ES:SE:LP:AF:ID 0.0654638:0.0285868:1.65758:0.0242:rs72910156
1 1036860 rs11579922 A C . PASS AF=0.1304 ES:SE:LP:AF:ID -0.017295:0.0126796:0.762959:0.1304:rs11579922
1 1036959 rs1162868282 T C . PASS AF=0.1169 ES:SE:LP:AF:ID -0.026296:0.0131546:1.34046:0.1169:rs1162868282
1 1037303 rs11260592 T C . PASS AF=0.1432 ES:SE:LP:AF:ID -0.00978826:0.0120545:0.37976:0.1432:rs11260592
1 1037313 rs11260593 A G . PASS AF=0.1474 ES:SE:LP:AF:ID -0.00804109:0.0118426:0.303818:0.1474:rs11260593
1 1037367 rs11260594 G A . PASS AF=0.1432 ES:SE:LP:AF:ID -0.00977758:0.0120562:0.37976:0.1432:rs11260594
1 1038088 rs66622470 G C . PASS AF=0.1433 ES:SE:LP:AF:ID -0.0101104:0.0120506:0.396314:0.1433:rs66622470
1 1039098 rs11260595 C A . PASS AF=0.0246 ES:SE:LP:AF:ID 0.0622853:0.0283502:1.55284:0.0246:rs11260595
1 1039268 rs9329410 T C . PASS AF=0.1434 ES:SE:LP:AF:ID -0.0106113:0.0120446:0.421934:0.1434:rs9329410
1 1039817 rs1205065516 A G . PASS AF=0.1433 ES:SE:LP:AF:ID -0.0111339:0.0120497:0.449283:0.1433:rs1205065516
1 1040026 rs6671356 T C . PASS AF=0.1437 ES:SE:LP:AF:ID -0.0108017:0.0120287:0.433091:0.1437:rs6671356
1 1040472 rs6664124 C T . PASS AF=0.1435 ES:SE:LP:AF:ID -0.0116281:0.0120373:0.476384:0.1435:rs6664124
1 1040794 rs6687681 G A . PASS AF=0.1435 ES:SE:LP:AF:ID -0.0119178:0.0120382:0.492144:0.1435:rs6687681
1 1040824 rs6656379 T C . PASS AF=0.1478 ES:SE:LP:AF:ID -0.010013:0.0118217:0.4011:0.1478:rs6656379
1 1040985 rs6697379 C G . PASS AF=0.1435 ES:SE:LP:AF:ID -0.0116768:0.0120379:0.478862:0.1435:rs6697379
1 1041700 rs6604968 A G . PASS AF=0.1436 ES:SE:LP:AF:ID -0.0120871:0.012039:0.501001:0.1436:rs6604968
1 1041786 rs6604969 T C . PASS AF=0.1436 ES:SE:LP:AF:ID -0.0130651:0.0120415:0.556268:0.1436:rs6604969
1 1042483 rs12733365 C T . PASS AF=0.1435 ES:SE:LP:AF:ID -0.0125691:0.0120394:0.528122:0.1435:rs12733365
1 1042527 rs1486993720 G C . PASS AF=0.1158 ES:SE:LP:AF:ID -0.0251581:0.0132202:1.24397:0.1158:rs1486993720
1 1042673 rs897825316 C T . PASS AF=0.1445 ES:SE:LP:AF:ID -0.0130381:0.0120723:0.552687:0.1445:rs897825316
1 1042927 rs4970354 G T . PASS AF=0.1435 ES:SE:LP:AF:ID -0.0125672:0.0120376:0.527975:0.1435:rs4970354
1 1043053 rs4970355 A G . PASS AF=0.1434 ES:SE:LP:AF:ID -0.0122709:0.0120421:0.510886:0.1434:rs4970355
1 1045473 rs11586034 G A . PASS AF=0.1153 ES:SE:LP:AF:ID -0.0260186:0.0132478:1.30487:0.1153:rs11586034
1 1046073 rs11590188 C A . PASS AF=0.1418 ES:SE:LP:AF:ID -0.0128713:0.0121085:0.540758:0.1418:rs11590188
1 1046164 rs386627439 C T . PASS AF=0.1434 ES:SE:LP:AF:ID -0.0125237:0.012042:0.525056:0.1434:rs386627439
1 1046717 rs34820586 G C . PASS AF=0.1162 ES:SE:LP:AF:ID -0.0267244:0.0131972:1.36785:0.1162:rs34820586
1 1046861 rs12723165 G A . PASS AF=0.1162 ES:SE:LP:AF:ID -0.0271588:0.0131967:1.4022:0.1162:rs12723165
1 1047374 rs12743678 T A . PASS AF=0.147 ES:SE:LP:AF:ID -0.0109789:0.0118562:0.450506:0.147:rs12743678
1 1048501 rs7518814 G A . PASS AF=0.1418 ES:SE:LP:AF:ID -0.0128105:0.0121082:0.537752:0.1418:rs7518814
1 1048955 rs4970405 A G . PASS AF=0.1057 ES:SE:LP:AF:ID -0.034906:0.0137534:1.9535:0.1057:rs4970405
1 1048989 rs4970406 A G . PASS AF=0.1179 ES:SE:LP:AF:ID -0.0226921:0.0132084:1.06697:0.1179:rs4970406
1 1049083 rs4970407 C A . PASS AF=0.117 ES:SE:LP:AF:ID -0.0236713:0.013239:1.1323:0.117:rs4970407
1 1049950 rs12726255 A G . PASS AF=0.1468 ES:SE:LP:AF:ID -0.005082:0.0118738:0.174899:0.1468:rs12726255
1 1052946 rs12755848 G T . PASS AF=0.1153 ES:SE:LP:AF:ID -0.0239559:0.013272:1.14783:0.1153:rs12755848
1 1053452 rs4970409 G A . PASS AF=0.1152 ES:SE:LP:AF:ID -0.024132:0.0132739:1.1604:0.1152:rs4970409
1 1053670 rs4970410 G A . PASS AF=0.1414 ES:SE:LP:AF:ID -0.00462848:0.0121482:0.152859:0.1414:rs4970410
1 1053724 rs4970411 A G . PASS AF=0.141 ES:SE:LP:AF:ID -0.00500123:0.0121685:0.166789:0.141:rs4970411
1 1054552 rs12567697 G A . PASS AF=0.1143 ES:SE:LP:AF:ID -0.0237692:0.0133236:1.12808:0.1143:rs12567697
1 1054893 rs4970412 T C . PASS AF=0.1453 ES:SE:LP:AF:ID -0.00432446:0.011946:0.14442:0.1453:rs4970412
1 1055653 rs34808604 C G . PASS AF=0.1145 ES:SE:LP:AF:ID -0.0238627:0.0133163:1.13632:0.1145:rs34808604
1 1055797 rs76744376 A G . PASS AF=0.1157 ES:SE:LP:AF:ID -0.0216763:0.0133393:0.982132:0.1157:rs76744376