Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

manhattan_plot

QQ plot

qq_plot

qq_plot

AF plot

af_plot

af_plot

P-Z plot

pz_plot

pz_plot

beta_std 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-4849_0/ukb-d-4849_0.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-4849_0/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 16:54:58 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-4849_0/ukb-d-4849_0.vcf.gz ...
Read summary statistics for 9767518 SNPs.
Dropped 7408 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, 1276221 SNPs remain.
After merging with regression SNP LD, 1276221 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0003 (0.0035)
Lambda GC: 0.9932
Mean Chi^2: 0.9944
Intercept: 0.9952 (0.006)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 16:56:37 2019
Total time elapsed: 1.0m:39.44s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9404,
    "inflation_factor": 1.0028,
    "mean_EFFECT": 4.3059e-06,
    "n": 119880,
    "n_snps": 9767518,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1068289,
    "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": 194119,
    "n_est": 119875.6611,
    "ratio_se_n": 1,
    "mean_diff": 0,
    "ratio_diff": 596.9024,
    "sd_y_est1": 0.105,
    "sd_y_est2": 0.105,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1276221,
    "ldsc_nsnp_merge_regression_ld": 1276221,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 0.9952,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 0.9932,
    "ldsc_mean_chisq": 0.9944,
    "ldsc_ratio": 0.8571
}

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 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 between AF and AF_reference.
  • inflation_factor (lambda): Genomic inflation factor.
  • mean_EFFECT: Mean of EFFECT size.
  • n: Maximum value of reported sample size across all SNPs, \(n\).
  • n_clumped_hits: Number of clumped hits.
  • n_snps: Number of SNPs
  • n_p_sig: Number of SNPs with pvalue below 5e-8.
  • n_mono: Number of monomorphic (MAF == 1 or MAF == 0) SNPs.
  • n_ns: Number of SNPs with nonsense values:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 0 or > 1.
  • n_mac: Number of cases where MAC (\(2 \times N \times MAF\)) is less than 6.
  • is_snpid_unique: true if the combination of ID REF ALT is unique and therefore no duplication in snpid.
  • n_miss_<*>: Number of NA observations 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 expect ratio_se_n to 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 of diff and the mean of diff2 (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<*>: r2 statistics under various assumptions
    • 1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).
    • 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: NOT is_snpid_unique.
  • mean_EFFECT_nonfinite: mean(EFFECT) is NA, NaN, or Inf.
  • mean_EFFECT_05: abs(mean(EFFECT)) > 0.5.
  • mean_EFFECT_01: abs(mean(EFFECT)) > 0.1.
  • mean_chisq: ldsc_mean_chisq > 1.3 or ldsc_mean_chisq < 0.7.
  • n_p_sig: n_p_sig > 1000.
  • miss_<*>: n_miss_<*> / n_snps > 0.01.
  • ldsc_ratio: ldsc_ratio > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_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 9760656 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 47373 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 29806 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.078383e+00 6.175378e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.875120e+07 5.610732e+07 3.0200e+02 3.244627e+07 6.964686e+07 1.147537e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.300000e-06 9.809000e-04 -9.1317e-03 -4.669000e-04 -2.000000e-06 4.633000e-04 1.107230e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.493000e-04 4.923000e-04 3.5240e-04 4.701000e-04 6.304000e-04 1.090100e-03 2.762000e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.996482e-01 2.888001e-01 1.0000e-07 2.492361e-01 4.993988e-01 7.501096e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.996468e-01 2.888009e-01 1.0000e-07 2.492340e-01 4.993973e-01 7.501088e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.600032e-01 2.628979e-01 9.3985e-03 4.273430e-02 1.572935e-01 4.138550e-01 9.906010e-01 ▇▂▂▁▁
numeric AF_reference 194119 0.9801261 NA NA NA NA NA 2.595306e-01 2.537223e-01 0.0000e+00 4.832270e-02 1.725240e-01 4.097440e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.198800e+05 0.000000e+00 1.1988e+05 1.198800e+05 1.198800e+05 1.198800e+05 1.198800e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0006001 0.0007506 0.4240148 0.4240139 0.1114330 0.1894970 119880
1 693731 rs12238997 A G -0.0005924 0.0007101 0.4041122 0.4041108 0.1166860 0.1417730 119880
1 707522 rs371890604 G C -0.0005837 0.0007969 0.4638654 0.4638630 0.0981079 0.1293930 119880
1 717587 rs144155419 G A -0.0004962 0.0019136 0.7953830 0.7953823 0.0156650 0.0045926 119880
1 730087 rs148120343 T C -0.0004202 0.0009904 0.6713237 0.6713216 0.0567674 0.0127796 119880
1 731718 rs142557973 T C -0.0005019 0.0006741 0.4565517 0.4565506 0.1225130 0.1543530 119880
1 732032 rs61770163 A C -0.0005039 0.0007184 0.4829865 0.4829855 0.1220470 0.1555510 119880
1 734349 rs141242758 T C -0.0005158 0.0006745 0.4444921 0.4444904 0.1217290 0.1525560 119880
1 749963 rs529266287 T TAA 0.0010215 0.0006649 0.1244649 0.1244630 0.8689610 0.7641770 119880
1 751343 rs28544273 T A -0.0007547 0.0006587 0.2518750 0.2518720 0.1236210 0.2426120 119880
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0009029 0.0007860 0.2506888 0.2506867 0.0549631 0.0309934 119880
23 154923374 rs111332691 T A 0.0007840 0.0008573 0.3604823 0.3604797 0.0442568 0.0116556 119880
23 154925045 rs509981 C T -0.0000092 0.0004122 0.9822560 0.9822558 0.2438930 0.3634440 119880
23 154925895 rs538470 C T 0.0000374 0.0004214 0.9292830 0.9292832 0.2403940 0.3634440 119880
23 154927581 rs644138 G A -0.0002382 0.0003877 0.5389531 0.5389526 0.2992620 0.4635760 119880
23 154929412 rs557132 C T -0.0000026 0.0004123 0.9950210 0.9950215 0.2437180 0.3568210 119880
23 154929637 rs35185538 CT C 0.0001224 0.0004301 0.7760148 0.7760153 0.2277460 0.3011920 119880
23 154929952 rs4012982 CAA C -0.0001479 0.0004339 0.7331182 0.7331191 0.2377740 0.3165560 119880
23 154930230 rs781880 A G -0.0000591 0.0004122 0.8860389 0.8860385 0.2442010 0.3618540 119880
23 154930487 rs781879 T A 0.0037279 0.0014336 0.0093134 0.0093120 0.0190232 0.1263580 119880

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111433 ES:SE:LP:AF:SS:ID   -0.000600081:0.000750592:0.372619:0.111433:119880:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116686 ES:SE:LP:AF:SS:ID   -0.000592412:0.000710069:0.393498:0.116686:119880:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0981079    ES:SE:LP:AF:SS:ID   -0.000583713:0.000796877:0.333608:0.0981079:119880:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015665 ES:SE:LP:AF:SS:ID   -0.000496242:0.00191357:0.0994237:0.015665:119880:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0567674    ES:SE:LP:AF:SS:ID   -0.000420249:0.000990371:0.173068:0.0567674:119880:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122513 ES:SE:LP:AF:SS:ID   -0.000501866:0.000674063:0.34051:0.122513:119880:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122047 ES:SE:LP:AF:SS:ID   -0.000503931:0.000718353:0.316065:0.122047:119880:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121729 ES:SE:LP:AF:SS:ID   -0.000515753:0.000674511:0.352136:0.121729:119880:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.868961 ES:SE:LP:AF:SS:ID   0.00102146:0.00066488:0.904953:0.868961:119880:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123621 ES:SE:LP:AF:SS:ID   -0.000754733:0.000658687:0.598815:0.123621:119880:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143235 ES:SE:LP:AF:SS:ID   -0.00094945:0.000652277:0.837116:0.143235:119880:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12374  ES:SE:LP:AF:SS:ID   -0.000765004:0.000657732:0.611199:0.12374:119880:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87014  ES:SE:LP:AF:SS:ID   0.000667572:0.000640643:0.526662:0.87014:119880:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874828 ES:SE:LP:AF:SS:ID   0.00086261:0.000651426:0.73179:0.874828:119880:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129435 ES:SE:LP:AF:SS:ID   -0.000591211:0.000642036:0.447164:0.129435:119880:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0367284    ES:SE:LP:AF:SS:ID   0.000436136:0.00115866:0.15082:0.0367284:119880:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869751 ES:SE:LP:AF:SS:ID   0.000632298:0.000639997:0.49057:0.869751:119880:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869872 ES:SE:LP:AF:SS:ID   0.000660441:0.000640347:0.519468:0.869872:119880:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869742 ES:SE:LP:AF:SS:ID   0.000633375:0.000639958:0.491718:0.869742:119880:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869867 ES:SE:LP:AF:SS:ID   0.000625129:0.000638918:0.4843:0.869867:119880:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126721 ES:SE:LP:AF:SS:ID   -0.000722638:0.000651943:0.572392:0.126721:119880:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869453 ES:SE:LP:AF:SS:ID   0.000641508:0.000637451:0.502736:0.869453:119880:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86866  ES:SE:LP:AF:SS:ID   0.000526669:0.000636674:0.389219:0.86866:119880:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869599 ES:SE:LP:AF:SS:ID   0.00062989:0.000637958:0.490163:0.869599:119880:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869606 ES:SE:LP:AF:SS:ID   0.000629783:0.000638004:0.490008:0.869606:119880:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869614 ES:SE:LP:AF:SS:ID   0.000629479:0.000638023:0.489674:0.869614:119880:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870038 ES:SE:LP:AF:SS:ID   0.000617877:0.000639648:0.47617:0.870038:119880:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0996424    ES:SE:LP:AF:SS:ID   -0.000851332:0.000741807:0.600124:0.0996424:119880:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873975 ES:SE:LP:AF:SS:ID   0.000804383:0.000649396:0.666609:0.873975:119880:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863333 ES:SE:LP:AF:SS:ID   0.00050786:0.000636768:0.37148:0.863333:119880:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868756 ES:SE:LP:AF:SS:ID   0.000729438:0.000642885:0.59086:0.868756:119880:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86552  ES:SE:LP:AF:SS:ID   0.000662294:0.000642828:0.518731:0.86552:119880:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0992499    ES:SE:LP:AF:SS:ID   -0.000896314:0.00077094:0.610862:0.0992499:119880:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870772 ES:SE:LP:AF:SS:ID   0.000734697:0.000650247:0.587486:0.870772:119880:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870772 ES:SE:LP:AF:SS:ID   0.000734705:0.000650247:0.587494:0.870772:119880:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870774 ES:SE:LP:AF:SS:ID   0.000736819:0.000650281:0.589756:0.870774:119880:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871164 ES:SE:LP:AF:SS:ID   0.000774105:0.000650678:0.630467:0.871164:119880:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126297 ES:SE:LP:AF:SS:ID   -0.000688282:0.000651106:0.536899:0.126297:119880:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106113 ES:SE:LP:AF:SS:ID   -0.000419087:0.00070811:0.256522:0.106113:119880:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854694 ES:SE:LP:AF:SS:ID   0.000426731:0.000636739:0.298655:0.854694:119880:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838005 ES:SE:LP:AF:SS:ID   -0.00155621:0.000626055:1.88841:0.838005:119880:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.762449 ES:SE:LP:AF:SS:ID   -0.000309257:0.000503781:0.268169:0.762449:119880:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106119 ES:SE:LP:AF:SS:ID   0.00119203:0.000692377:1.06989:0.106119:119880:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.129609 ES:SE:LP:AF:SS:ID   -0.000546267:0.000641919:0.403649:0.129609:119880:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129306 ES:SE:LP:AF:SS:ID   -0.000551618:0.000641351:0.409223:0.129306:119880:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.105397 ES:SE:LP:AF:SS:ID   0.00113816:0.000697885:0.9875:0.105397:119880:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.104406 ES:SE:LP:AF:SS:ID   0.00114247:0.000703632:0.9811:0.104406:119880:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.829416 ES:SE:LP:AF:SS:ID   0.00052084:0.000625396:0.392599:0.829416:119880:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.869532 ES:SE:LP:AF:SS:ID   0.000624566:0.000638701:0.483939:0.869532:119880:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129371 ES:SE:LP:AF:SS:ID   -0.000552514:0.000641012:0.41036:0.129371:119880:rs59066358