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/89fa4a85-68d2-4d01-9ab8-b09a4c088451/call-vcf/inputs/562856126/upload.txt.gz --id ieu-b-11 --json /data/cromwell-executions/qc/89fa4a85-68d2-4d01-9ab8-b09a4c088451/call-vcf/inputs/562856126/ieu-b-11_data.json --ref /data/cromwell-executions/qc/89fa4a85-68d2-4d01-9ab8-b09a4c088451/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/89fa4a85-68d2-4d01-9ab8-b09a4c088451/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-11/ieu-b-11.vcf.gz --rm_chr_prefix --cohort_cases 2716 --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/89fa4a85-68d2-4d01-9ab8-b09a4c088451/call-ldsc/inputs/562856126/ieu-b-11.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-11/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Fri Jun 26 15:28:49 2020
Reading summary statistics from /data/cromwell-executions/qc/89fa4a85-68d2-4d01-9ab8-b09a4c088451/call-ldsc/inputs/562856126/ieu-b-11.vcf.gz ...
Read summary statistics for 4988859 SNPs.
Dropped 11901 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, 951149 SNPs remain.
After merging with regression SNP LD, 951149 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.019 (0.0177)
Lambda GC: 1.092
Mean Chi^2: 1.0914
Intercept: 1.0778 (0.0091)
Ratio: 0.8509 (0.1)
Analysis finished at Fri Jun 26 15:30:22 2020
Total time elapsed: 1.0m:33.06sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9303,
"inflation_factor": 1.0966,
"mean_EFFECT": 0.0002,
"n": "-Inf",
"n_snps": 4988872,
"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": 29961,
"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": 951149,
"ldsc_nsnp_merge_regression_ld": 951149,
"ldsc_observed_scale_h2_beta": 0.019,
"ldsc_observed_scale_h2_se": 0.0177,
"ldsc_intercept_beta": 1.0778,
"ldsc_intercept_se": 0.0091,
"ldsc_lambda_gc": 1.092,
"ldsc_mean_chisq": 1.0914,
"ldsc_ratio": 0.8512
}
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 | 4988868 | 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 | 4988872 | 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 | 8.645297e+00 | 5.871550e+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 | 7.979539e+07 | 5.501469e+07 | 3.30120e+04 | 3.478304e+07 | 7.128905e+07 | 1.144090e+08 | 2.492190e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.564000e-04 | 4.697100e-03 | -4.21327e-02 | -2.407600e-03 | 1.091000e-04 | 2.651500e-03 | 5.098380e-02 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.069800e-03 | 1.948100e-03 | 2.08050e-03 | 2.723800e-03 | 3.280800e-03 | 4.648200e-03 | 1.321090e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.859218e-01 | 2.922194e-01 | 3.00000e-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 | 4.859219e-01 | 2.921951e-01 | 3.00000e-07 | 2.292423e-01 | 4.807067e-01 | 7.390304e-01 | 9.999999e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.074413e-01 | 2.583547e-01 | 1.00004e-02 | 8.974500e-02 | 2.268750e-01 | 4.775642e-01 | 9.899940e-01 | ▇▃▂▂▁ |
| numeric | AF_reference | 29961 | 0.9939944 | NA | NA | NA | NA | NA | NA | NA | 3.086758e-01 | 2.469660e-01 | 1.99700e-04 | 1.044330e-01 | 2.381460e-01 | 4.694490e-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 | -0.0003524 | 0.0034837 | 0.9199999 | 0.9194248 | 0.163448 | 0.3156950 | NA |
| 1 | 1030565 | rs6687776 | C | T | 0.0007277 | 0.0034787 | 0.8300000 | 0.8343121 | 0.163449 | 0.3067090 | NA |
| 1 | 1030633 | rs6678318 | G | A | 0.0007293 | 0.0034788 | 0.8300000 | 0.8339352 | 0.163455 | 0.3065100 | NA |
| 1 | 1031973 | rs9651270 | C | T | 0.0005145 | 0.0035360 | 0.8800001 | 0.8843049 | 0.160140 | 0.3107030 | NA |
| 1 | 1033596 | rs6604964 | T | C | 0.0006527 | 0.0035379 | 0.8499999 | 0.8536394 | 0.160023 | 0.3117010 | NA |
| 1 | 1033670 | rs6604966 | T | C | 0.0003854 | 0.0035401 | 0.9100000 | 0.9132992 | 0.159928 | 0.3158950 | NA |
| 1 | 1033680 | rs6604967 | T | A | 0.0003377 | 0.0035400 | 0.9199999 | 0.9239917 | 0.159909 | 0.3117010 | NA |
| 1 | 1033994 | rs6698368 | C | T | 0.0001780 | 0.0035398 | 0.9599999 | 0.9598936 | 0.159948 | 0.3115020 | NA |
| 1 | 1034200 | rs77977351 | T | C | 0.0003882 | 0.0035393 | 0.9100000 | 0.9126604 | 0.159985 | 0.3115020 | NA |
| 1 | 1036601 | rs72910156 | C | T | 0.0280467 | 0.0083607 | 0.0007900 | 0.0007948 | 0.024196 | 0.0399361 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 139314056 | rs5955415 | C | G | 0.0043122 | 0.0035893 | 0.2300001 | 0.2296018 | 0.097138 | 0.125033 | NA |
| 23 | 139314798 | rs62609008 | C | A | 0.0045207 | 0.0036045 | 0.2099999 | 0.2097748 | 0.096244 | 0.106755 | NA |
| 23 | 139315107 | rs62609010 | T | A | 0.0045565 | 0.0036024 | 0.2099999 | 0.2059217 | 0.096340 | 0.107020 | NA |
| 23 | 139316769 | rs73230748 | T | C | 0.0050004 | 0.0035939 | 0.1600000 | 0.1641248 | 0.096798 | 0.121060 | NA |
| 23 | 139317055 | rs62609011 | C | A | 0.0050324 | 0.0035932 | 0.1600000 | 0.1613577 | 0.096853 | 0.116026 | NA |
| 23 | 139317165 | rs28877369 | C | G | 0.0045607 | 0.0035958 | 0.2000000 | 0.2046773 | 0.096703 | 0.116291 | NA |
| 23 | 139317337 | rs55757628 | A | G | 0.0046662 | 0.0036007 | 0.2000000 | 0.1950035 | 0.096427 | 0.107285 | NA |
| 23 | 139319949 | rs140616281 | A | G | 0.0047868 | 0.0036034 | 0.1800002 | 0.1840475 | 0.096364 | 0.116291 | NA |
| 23 | 139320136 | rs76621315 | C | G | 0.0049531 | 0.0035917 | 0.1700000 | 0.1678824 | 0.096964 | 0.114437 | NA |
| 23 | 139325995 | rs62609013 | G | A | 0.0042244 | 0.0035980 | 0.2399999 | 0.2403587 | 0.096650 | 0.101987 | NA |
bcf preview
1 1029805 rs891281851 A G . PASS AF=0.163448 ES:SE:LP:AF:ID -0.000352406:0.00348371:0.0362122:0.163448:rs891281851
1 1030565 rs6687776 C T . PASS AF=0.163449 ES:SE:LP:AF:ID 0.000727659:0.00347872:0.0809219:0.163449:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.163455 ES:SE:LP:AF:ID 0.000729345:0.00347875:0.0809219:0.163455:rs6678318
1 1031973 rs9651270 C T . PASS AF=0.16014 ES:SE:LP:AF:ID 0.000514544:0.00353604:0.0555173:0.16014:rs9651270
1 1033596 rs6604964 T C . PASS AF=0.160023 ES:SE:LP:AF:ID 0.000652666:0.00353793:0.0705811:0.160023:rs6604964
1 1033670 rs1370950991 T C . PASS AF=0.159928 ES:SE:LP:AF:ID 0.000385438:0.00354009:0.0409586:0.159928:rs1370950991
1 1033680 rs1370950991 T A . PASS AF=0.159909 ES:SE:LP:AF:ID 0.000337741:0.00354001:0.0362122:0.159909:rs1370950991
1 1033994 rs6698368 C T . PASS AF=0.159948 ES:SE:LP:AF:ID 0.000178008:0.00353983:0.0177288:0.159948:rs6698368
1 1034200 rs77977351 T C . PASS AF=0.159985 ES:SE:LP:AF:ID 0.000388204:0.00353931:0.0409586:0.159985:rs77977351
1 1036601 rs72910156 C T . PASS AF=0.024196 ES:SE:LP:AF:ID 0.0280467:0.00836071:3.10237:0.024196:rs72910156
1 1036860 rs11579922 A C . PASS AF=0.126502 ES:SE:LP:AF:ID -0.00478517:0.00388237:0.657577:0.126502:rs11579922
1 1036959 rs1162868282 T C . PASS AF=0.112663 ES:SE:LP:AF:ID -0.00611369:0.00404238:0.886057:0.112663:rs1162868282
1 1037303 rs11260592 T C . PASS AF=0.140153 ES:SE:LP:AF:ID -0.000621591:0.00367366:0.0604807:0.140153:rs11260592
1 1037313 rs11260593 A G . PASS AF=0.14027 ES:SE:LP:AF:ID -0.000360175:0.00367295:0.0362122:0.14027:rs11260593
1 1037367 rs11260594 G A . PASS AF=0.140152 ES:SE:LP:AF:ID -0.00062277:0.00367406:0.0604807:0.140152:rs11260594
1 1038088 rs66622470 G C . PASS AF=0.140217 ES:SE:LP:AF:ID -0.000660628:0.00367198:0.0655015:0.140217:rs66622470
1 1039098 rs11260595 C A . PASS AF=0.0245347 ES:SE:LP:AF:ID 0.0276657:0.00829117:3.07058:0.0245347:rs11260595
1 1039268 rs9329410 T C . PASS AF=0.14037 ES:SE:LP:AF:ID -0.000765235:0.00366871:0.0809219:0.14037:rs9329410
1 1039817 rs1205065516 A G . PASS AF=0.140279 ES:SE:LP:AF:ID -0.000718831:0.00367066:0.0757207:0.140279:rs1205065516
1 1040026 rs6671356 T C . PASS AF=0.140649 ES:SE:LP:AF:ID -0.000930592:0.00366376:0.09691:0.140649:rs6671356
1 1040472 rs6664124 C T . PASS AF=0.140558 ES:SE:LP:AF:ID -0.000884563:0.0036657:0.091515:0.140558:rs6664124
1 1040794 rs6687681 G A . PASS AF=0.140537 ES:SE:LP:AF:ID -0.000858828:0.00366601:0.091515:0.140537:rs6687681
1 1040824 rs6656379 T C . PASS AF=0.140712 ES:SE:LP:AF:ID -0.000663951:0.00366363:0.0655015:0.140712:rs6656379
1 1040985 rs6697379 C G . PASS AF=0.140513 ES:SE:LP:AF:ID -0.000844101:0.00366611:0.0861861:0.140513:rs6697379
1 1041700 rs6604968 A G . PASS AF=0.140626 ES:SE:LP:AF:ID -0.00109521:0.00366528:0.113509:0.140626:rs6604968
1 1041786 rs6604969 T C . PASS AF=0.140637 ES:SE:LP:AF:ID -0.00109839:0.00366492:0.119186:0.140637:rs6604969
1 1042483 rs12733365 C T . PASS AF=0.140539 ES:SE:LP:AF:ID -0.000839319:0.00366567:0.0861861:0.140539:rs12733365
1 1042527 rs1486993720 G C . PASS AF=0.112423 ES:SE:LP:AF:ID -0.00643512:0.00404466:0.958607:0.112423:rs1486993720
1 1042673 rs897825316 C T . PASS AF=0.141618 ES:SE:LP:AF:ID -0.00107398:0.00367648:0.113509:0.141618:rs897825316
1 1042927 rs4970354 G T . PASS AF=0.140521 ES:SE:LP:AF:ID -0.000859699:0.00366539:0.091515:0.140521:rs4970354
1 1043053 rs4970355 A G . PASS AF=0.14044 ES:SE:LP:AF:ID -0.000901063:0.00366627:0.091515:0.14044:rs4970355
1 1045473 rs11586034 G A . PASS AF=0.111684 ES:SE:LP:AF:ID -0.00591204:0.00405845:0.823909:0.111684:rs11586034
1 1046073 rs11590188 C A . PASS AF=0.13895 ES:SE:LP:AF:ID -0.000352805:0.00368619:0.0362122:0.13895:rs11590188
1 1046164 rs386627439 C T . PASS AF=0.140475 ES:SE:LP:AF:ID -0.00102173:0.00366581:0.107905:0.140475:rs386627439
1 1046717 rs34820586 G C . PASS AF=0.112486 ES:SE:LP:AF:ID -0.00645268:0.00404378:0.958607:0.112486:rs34820586
1 1046861 rs12723165 G A . PASS AF=0.112473 ES:SE:LP:AF:ID -0.00647734:0.00404372:0.958607:0.112473:rs12723165
1 1047374 rs12743678 T A . PASS AF=0.140196 ES:SE:LP:AF:ID -0.000358747:0.00366797:0.0362122:0.140196:rs12743678
1 1048501 rs7518814 G A . PASS AF=0.138955 ES:SE:LP:AF:ID -0.000358924:0.00368621:0.0362122:0.138955:rs7518814
1 1048955 rs4970405 A G . PASS AF=0.104199 ES:SE:LP:AF:ID -0.00790763:0.0041819:1.22915:0.104199:rs4970405
1 1048989 rs4970406 A G . PASS AF=0.113223 ES:SE:LP:AF:ID -0.00640575:0.00403742:0.958607:0.113223:rs4970406
1 1049083 rs4970407 C A . PASS AF=0.112443 ES:SE:LP:AF:ID -0.00615651:0.00404561:0.886057:0.112443:rs4970407
1 1049950 rs12726255 A G . PASS AF=0.139178 ES:SE:LP:AF:ID 0.000282776:0.00368904:0.0268721:0.139178:rs12726255
1 1052946 rs12755848 G T . PASS AF=0.111421 ES:SE:LP:AF:ID -0.00636674:0.00407129:0.920819:0.111421:rs12755848
1 1053452 rs4970409 G A . PASS AF=0.111419 ES:SE:LP:AF:ID -0.00642893:0.00407098:0.958607:0.111419:rs4970409
1 1053670 rs4970410 G A . PASS AF=0.138146 ES:SE:LP:AF:ID 0.00107517:0.00370708:0.113509:0.138146:rs4970410
1 1053724 rs4970411 A G . PASS AF=0.137726 ES:SE:LP:AF:ID 0.0008685:0.00371313:0.0861861:0.137726:rs4970411
1 1054552 rs12567697 G A . PASS AF=0.110526 ES:SE:LP:AF:ID -0.00590335:0.00408762:0.823909:0.110526:rs12567697
1 1054893 rs4970412 T C . PASS AF=0.137935 ES:SE:LP:AF:ID 0.000589306:0.00371031:0.0604807:0.137935:rs4970412
1 1055653 rs34808604 C G . PASS AF=0.110642 ES:SE:LP:AF:ID -0.0061534:0.00408479:0.886057:0.110642:rs34808604
1 1055797 rs76744376 A G . PASS AF=0.111117 ES:SE:LP:AF:ID -0.00630507:0.0040794:0.920819:0.111117:rs76744376