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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}
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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22506_114/ukb-d-22506_114.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22506_114/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Mon Nov 25 14:53:17 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22506_114/ukb-d-22506_114.vcf.gz ...
Read summary statistics for 13567195 SNPs.
Dropped 12679 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0933 (0.008)
Lambda GC: 1.1626
Mean Chi^2: 1.181
Intercept: 1.0125 (0.0074)
Ratio: 0.0688 (0.0411)
Analysis finished at Mon Nov 25 14:55:26 2019
Total time elapsed: 2.0m:9.33sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9521,
"inflation_factor": 1.1011,
"mean_EFFECT": -0.0001,
"n": 91353,
"n_snps": 13567195,
"n_clumped_hits": 5,
"n_p_sig": 501,
"n_mono": 0,
"n_ns": 1251239,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 563226,
"n_est": 91690.9383,
"ratio_se_n": 1.0018,
"mean_diff": -0.0001,
"ratio_diff": 38.8708,
"sd_y_est1": 0.4869,
"sd_y_est2": 0.4878,
"r2_sum1": 0.0006,
"r2_sum2": 0.0025,
"r2_sum3": 0.0024,
"r2_sum4": 0.0024,
"ldsc_nsnp_merge_refpanel_ld": 1283504,
"ldsc_nsnp_merge_regression_ld": 1283504,
"ldsc_observed_scale_h2_beta": 0.0933,
"ldsc_observed_scale_h2_se": 0.008,
"ldsc_intercept_beta": 1.0125,
"ldsc_intercept_se": 0.0074,
"ldsc_lambda_gc": 1.1626,
"ldsc_mean_chisq": 1.181,
"ldsc_ratio": 0.0691
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| 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 | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 0 | 1.0000000 | 3 | 94 | 0 | 13555180 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57048 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33330 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051360e+00 | 6.184981e+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 | 7.902469e+07 | 5.591662e+07 | 3.02000e+02 | 3.292761e+07 | 7.013430e+07 | 1.148618e+08 | 2.492309e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -6.480000e-05 | 1.337810e-02 | -1.67623e-01 | -3.755900e-03 | -2.590000e-05 | 3.686900e-03 | 1.636990e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.535900e-03 | 9.190100e-03 | 1.88030e-03 | 2.724300e-03 | 5.011200e-03 | 1.369280e-02 | 4.618030e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.843276e-01 | 2.922248e-01 | 0.00000e+00 | 2.281498e-01 | 4.790822e-01 | 7.367871e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.843258e-01 | 2.922258e-01 | 0.00000e+00 | 2.281470e-01 | 4.790802e-01 | 7.367862e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.910631e-01 | 2.544736e-01 | 1.00000e-03 | 7.498000e-03 | 6.029320e-02 | 2.957790e-01 | 9.990000e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 563226 | 0.9584862 | NA | NA | NA | NA | NA | 1.965199e-01 | 2.471444e-01 | 0.00000e+00 | 5.790700e-03 | 8.446490e-02 | 3.085060e-01 | 1.000000e+00 | ▇▂▁▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.135300e+04 | 0.000000e+00 | 9.13530e+04 | 9.135300e+04 | 9.135300e+04 | 9.135300e+04 | 9.135300e+04 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 692794 | rs530212009 | CA | C | 0.0025352 | 0.0039792 | 0.5240443 | 0.5240431 | 0.1114110 | 0.1894970 | 91353 |
| 1 | 693731 | rs12238997 | A | G | -0.0014448 | 0.0037688 | 0.7014585 | 0.7014585 | 0.1163870 | 0.1417730 | 91353 |
| 1 | 707522 | rs371890604 | G | C | 0.0019302 | 0.0042368 | 0.6486942 | 0.6486932 | 0.0978018 | 0.1293930 | 91353 |
| 1 | 717587 | rs144155419 | G | A | -0.0097345 | 0.0101084 | 0.3355436 | 0.3355405 | 0.0157459 | 0.0045926 | 91353 |
| 1 | 723329 | rs189787166 | A | T | 0.0185081 | 0.0293587 | 0.5284258 | 0.5284245 | 0.0017874 | 0.0003994 | 91353 |
| 1 | 730087 | rs148120343 | T | C | 0.0033365 | 0.0052259 | 0.5231750 | 0.5231736 | 0.0569530 | 0.0127796 | 91353 |
| 1 | 731718 | rs142557973 | T | C | -0.0008397 | 0.0035768 | 0.8143899 | 0.8143901 | 0.1222870 | 0.1543530 | 91353 |
| 1 | 732032 | rs61770163 | A | C | 0.0001547 | 0.0038143 | 0.9676411 | 0.9676407 | 0.1219550 | 0.1555510 | 91353 |
| 1 | 734349 | rs141242758 | T | C | -0.0008933 | 0.0035795 | 0.8029339 | 0.8029329 | 0.1215170 | 0.1525560 | 91353 |
| 1 | 740284 | rs61770167 | C | T | -0.0025524 | 0.0163948 | 0.8762830 | 0.8762820 | 0.0057670 | 0.0023962 | 91353 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154923311 | rs141127553 | C | T | 0.0011108 | 0.0041837 | 0.7906204 | 0.7906192 | 0.0553192 | 0.0309934 | 91353 |
| 23 | 154923374 | rs111332691 | T | A | 0.0026333 | 0.0045524 | 0.5629736 | 0.5629720 | 0.0448863 | 0.0116556 | 91353 |
| 23 | 154925045 | rs509981 | C | T | -0.0040368 | 0.0021951 | 0.0659204 | 0.0659177 | 0.2442380 | 0.3634440 | 91353 |
| 23 | 154925895 | rs538470 | C | T | -0.0035955 | 0.0022443 | 0.1091481 | 0.1091454 | 0.2407140 | 0.3634440 | 91353 |
| 23 | 154927581 | rs644138 | G | A | -0.0032602 | 0.0020646 | 0.1143089 | 0.1143069 | 0.2999670 | 0.4635760 | 91353 |
| 23 | 154929412 | rs557132 | C | T | -0.0040844 | 0.0021958 | 0.0628767 | 0.0628726 | 0.2440870 | 0.3568210 | 91353 |
| 23 | 154929637 | rs35185538 | CT | C | -0.0030184 | 0.0022929 | 0.1880429 | 0.1880403 | 0.2285200 | 0.3011920 | 91353 |
| 23 | 154929952 | rs4012982 | CAA | C | -0.0043514 | 0.0023109 | 0.0597035 | 0.0596997 | 0.2380650 | 0.3165560 | 91353 |
| 23 | 154930230 | rs781880 | A | G | -0.0038830 | 0.0021950 | 0.0768989 | 0.0768951 | 0.2445480 | 0.3618540 | 91353 |
| 23 | 154930487 | rs781879 | T | A | 0.0012005 | 0.0074448 | 0.8718960 | 0.8718955 | 0.0196444 | 0.1263580 | 91353 |
bcf preview
1 692794 rs530212009 CA C . PASS AF=0.111411 ES:SE:LP:AF:SS:ID 0.00253525:0.0039792:0.280632:0.111411:91353:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116387 ES:SE:LP:AF:SS:ID -0.00144479:0.00376883:0.153998:0.116387:91353:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0978018 ES:SE:LP:AF:SS:ID 0.00193019:0.00423679:0.18796:0.0978018:91353:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0157459 ES:SE:LP:AF:SS:ID -0.00973453:0.0101084:0.474251:0.0157459:91353:rs144155419
1 723329 rs189787166 A T . PASS AF=0.0017874 ES:SE:LP:AF:SS:ID 0.0185081:0.0293587:0.277016:0.0017874:91353:rs189787166
1 730087 rs148120343 T C . PASS AF=0.056953 ES:SE:LP:AF:SS:ID 0.00333654:0.00522591:0.281353:0.056953:91353:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122287 ES:SE:LP:AF:SS:ID -0.000839712:0.0035768:0.0891676:0.122287:91353:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121955 ES:SE:LP:AF:SS:ID 0.000154735:0.00381426:0.0142857:0.121955:91353:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121517 ES:SE:LP:AF:SS:ID -0.000893278:0.00357951:0.0953202:0.121517:91353:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00576701 ES:SE:LP:AF:SS:ID -0.00255241:0.0163948:0.0573556:0.00576701:91353:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00183911 ES:SE:LP:AF:SS:ID 0.0702618:0.0312906:1.60658:0.00183911:91353:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.86901 ES:SE:LP:AF:SS:ID -3.67271e-05:0.00352109:0.00362932:0.86901:91353:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00160747 ES:SE:LP:AF:SS:ID 0.00270278:0.0309955:0.0312776:0.00160747:91353:rs190826124
1 751343 rs28544273 T A . PASS AF=0.123604 ES:SE:LP:AF:SS:ID -0.000155909:0.00349092:0.0157532:0.123604:91353:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143109 ES:SE:LP:AF:SS:ID -0.00484057:0.00345555:0.792433:0.143109:91353:rs200141114
1 751756 rs28527770 T C . PASS AF=0.12374 ES:SE:LP:AF:SS:ID -0.000172:0.00348586:0.0174362:0.12374:91353:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869977 ES:SE:LP:AF:SS:ID 0.000475584:0.00339652:0.0512722:0.869977:91353:rs3115860
1 753425 rs3131970 T C . PASS AF=0.874656 ES:SE:LP:AF:SS:ID -0.000597407:0.00345188:0.0641911:0.874656:91353:rs3131970
1 753541 rs2073813 G A . PASS AF=0.129446 ES:SE:LP:AF:SS:ID -0.00126894:0.00340699:0.149013:0.129446:91353:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0358609 ES:SE:LP:AF:SS:ID 0.00376531:0.00621917:0.26369:0.0358609:91353:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869624 ES:SE:LP:AF:SS:ID 0.000564938:0.00339352:0.0615889:0.869624:91353:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869701 ES:SE:LP:AF:SS:ID 0.000589567:0.003395:0.0644247:0.869701:91353:rs3131968
1 754334 rs3131967 T C . PASS AF=0.86962 ES:SE:LP:AF:SS:ID 0.000560172:0.00339337:0.0610387:0.86962:91353:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00531283 ES:SE:LP:AF:SS:ID 0.00718712:0.0169556:0.172854:0.00531283:91353:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00527823 ES:SE:LP:AF:SS:ID 0.00801708:0.0169977:0.195743:0.00527823:91353:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00564288 ES:SE:LP:AF:SS:ID 0.00261878:0.0167291:0.0576903:0.00564288:91353:rs184270342
1 755890 rs3115858 A T . PASS AF=0.8696 ES:SE:LP:AF:SS:ID 0.000649672:0.0033865:0.0716723:0.8696:91353:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126828 ES:SE:LP:AF:SS:ID -0.00115642:0.00345721:0.13194:0.126828:91353:rs61768170
1 756604 rs3131962 A G . PASS AF=0.869129 ES:SE:LP:AF:SS:ID 0.000567128:0.00337771:0.0621512:0.869129:91353:rs3131962
1 757640 rs3115853 G A . PASS AF=0.868516 ES:SE:LP:AF:SS:ID 0.000488774:0.00337541:0.053123:0.868516:91353:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869278 ES:SE:LP:AF:SS:ID 0.000539126:0.00338077:0.0588365:0.869278:91353:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869283 ES:SE:LP:AF:SS:ID 0.000541639:0.003381:0.0591236:0.869283:91353:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869286 ES:SE:LP:AF:SS:ID 0.000544037:0.00338103:0.0594008:0.869286:91353:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869767 ES:SE:LP:AF:SS:ID 0.000660836:0.0033901:0.0729136:0.869767:91353:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0991021 ES:SE:LP:AF:SS:ID 0.00074993:0.00394636:0.070946:0.0991021:91353:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00647948 ES:SE:LP:AF:SS:ID 0.00175105:0.0152415:0.0416583:0.00647948:91353:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.873778 ES:SE:LP:AF:SS:ID -0.000141789:0.00344046:0.0145165:0.873778:91353:rs3115851
1 761732 rs2286139 C T . PASS AF=0.86314 ES:SE:LP:AF:SS:ID 4.78644e-06:0.0033745:0.0004919:0.86314:91353:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868548 ES:SE:LP:AF:SS:ID 0.00043229:0.00340816:0.0462075:0.868548:91353:rs1057213
1 762273 rs3115849 G A . PASS AF=0.865453 ES:SE:LP:AF:SS:ID 0.000330948:0.00340879:0.0349592:0.865453:91353:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0994287 ES:SE:LP:AF:SS:ID -0.000420479:0.00408069:0.0371904:0.0994287:91353:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870755 ES:SE:LP:AF:SS:ID -0.000133736:0.00344775:0.0136498:0.870755:91353:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870755 ES:SE:LP:AF:SS:ID -0.000133637:0.00344775:0.0136399:0.870755:91353:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870752 ES:SE:LP:AF:SS:ID -0.000133346:0.00344776:0.0136094:0.870752:91353:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871109 ES:SE:LP:AF:SS:ID -8.02496e-05:0.00344931:0.00813669:0.871109:91353:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126424 ES:SE:LP:AF:SS:ID -0.000852681:0.00345319:0.0942225:0.126424:91353:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105999 ES:SE:LP:AF:SS:ID 0.000190273:0.00375342:0.0179233:0.105999:91353:rs61768174
1 766105 rs2519015 T A . PASS AF=0.854464 ES:SE:LP:AF:SS:ID -0.000176081:0.00337339:0.0184659:0.854464:91353:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00170101 ES:SE:LP:AF:SS:ID 0.0141366:0.0294434:0.199876:0.00170101:91353:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.83913 ES:SE:LP:AF:SS:ID 0.00747613:0.00333176:1.60483:0.83913:91353:rs376645387