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-1418_1/ukb-d-1418_1.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-1418_1/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 17:10:12 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1418_1/ukb-d-1418_1.vcf.gz ...
Read summary statistics for 13586586 SNPs.
Dropped 12711 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: 0.0147 (0.0017)
Lambda GC: 1.1065
Mean Chi^2: 1.1139
Intercept: 1.0103 (0.0074)
Ratio: 0.0901 (0.0652)
Analysis finished at Mon Nov 25 17:12:29 2019
Total time elapsed: 2.0m:16.8s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0659,
    "mean_EFFECT": 0,
    "n": 360806,
    "n_snps": 13586586,
    "n_clumped_hits": 3,
    "n_p_sig": 298,
    "n_mono": 0,
    "n_ns": 1251809,
    "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": 569292,
    "n_est": 362181.2014,
    "ratio_se_n": 1.0019,
    "mean_diff": 0,
    "ratio_diff": 557.4173,
    "sd_y_est1": 0.2439,
    "sd_y_est2": 0.2443,
    "r2_sum1": 0,
    "r2_sum2": 0.0003,
    "r2_sum3": 0.0003,
    "r2_sum4": 0.0003,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0147,
    "ldsc_observed_scale_h2_se": 0.0017,
    "ldsc_intercept_beta": 1.0103,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.1065,
    "ldsc_mean_chisq": 1.1139,
    "ldsc_ratio": 0.0904
}

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 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 1.000000 3 94 0 13574539 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 57083 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.051332e+00 6.184961e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.902504e+07 5.591474e+07 3.02000e+02 3.293101e+07 7.013846e+07 1.148589e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 1.420000e-05 3.383200e-03 -3.72266e-02 -9.132000e-04 2.100000e-06 9.221000e-04 4.666130e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 2.412600e-03 2.327200e-03 4.72100e-04 6.868000e-04 1.265700e-03 3.467100e-03 1.170550e-02 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.900059e-01 2.914416e-01 0.00000e+00 2.354101e-01 4.862090e-01 7.424804e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.900054e-01 2.914419e-01 0.00000e+00 2.354095e-01 4.862085e-01 7.424806e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 1.908017e-01 2.544021e-01 1.00000e-03 7.429400e-03 6.003010e-02 2.953020e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569292 0.958099 NA NA NA NA NA 1.963330e-01 2.471006e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.000000 NA NA NA NA NA 3.608060e+05 0.000000e+00 3.60806e+05 3.608060e+05 3.608060e+05 3.608060e+05 3.608060e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0017816 0.0010054 0.0763959 0.0763940 0.1106400 0.1894970 360806
1 693731 rs12238997 A G -0.0012734 0.0009499 0.1800732 0.1800730 0.1158360 0.1417730 360806
1 707522 rs371890604 G C -0.0013179 0.0010680 0.2171931 0.2171923 0.0973005 0.1293930 360806
1 717587 rs144155419 G A -0.0046614 0.0025482 0.0673581 0.0673578 0.0156910 0.0045926 360806
1 723329 rs189787166 A T 0.0032996 0.0075184 0.6607528 0.6607526 0.0017340 0.0003994 360806
1 730087 rs148120343 T C -0.0000657 0.0013235 0.9604231 0.9604231 0.0564560 0.0127796 360806
1 731718 rs142557973 T C -0.0014555 0.0009009 0.1061989 0.1061970 0.1217420 0.1543530 360806
1 732032 rs61770163 A C -0.0019354 0.0009610 0.0440170 0.0440168 0.1211750 0.1555510 360806
1 734349 rs141242758 T C -0.0014840 0.0009014 0.0996919 0.0996916 0.1209690 0.1525560 360806
1 740284 rs61770167 C T -0.0022415 0.0041240 0.5867674 0.5867673 0.0057852 0.0023962 360806
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0019447 0.0010410 0.0617433 0.0617421 0.0561637 0.0309934 360806
23 154923374 rs111332691 T A 0.0001359 0.0011440 0.9054419 0.9054421 0.0447817 0.0116556 360806
23 154925045 rs509981 C T -0.0008632 0.0005504 0.1168240 0.1168238 0.2456180 0.3634440 360806
23 154925895 rs538470 C T -0.0009551 0.0005631 0.0898463 0.0898456 0.2419280 0.3634440 360806
23 154927581 rs644138 G A -0.0012542 0.0005176 0.0154000 0.0153998 0.3021690 0.4635760 360806
23 154929412 rs557132 C T -0.0008942 0.0005506 0.1043701 0.1043692 0.2454700 0.3568210 360806
23 154929637 rs35185538 CT C -0.0010730 0.0005746 0.0618458 0.0618460 0.2297070 0.3011920 360806
23 154929952 rs4012982 CAA C -0.0010719 0.0005791 0.0641682 0.0641665 0.2394320 0.3165560 360806
23 154930230 rs781880 A G -0.0009190 0.0005505 0.0950473 0.0950462 0.2458800 0.3618540 360806
23 154930487 rs781879 T A -0.0075949 0.0018882 0.0000577 0.0000576 0.0195658 0.1263580 360806

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11064  ES:SE:LP:AF:SS:ID   -0.00178159:0.00100541:1.11693:0.11064:360806:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115836 ES:SE:LP:AF:SS:ID   -0.00127343:0.000949945:0.744551:0.115836:360806:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973005    ES:SE:LP:AF:SS:ID   -0.00131793:0.00106799:0.663154:0.0973005:360806:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015691 ES:SE:LP:AF:SS:ID   -0.00466135:0.00254819:1.17161:0.015691:360806:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173396   ES:SE:LP:AF:SS:ID   0.00329962:0.00751837:0.179961:0.00173396:360806:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056456 ES:SE:LP:AF:SS:ID   -6.56755e-05:0.0013235:0.0175374:0.056456:360806:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121742 ES:SE:LP:AF:SS:ID   -0.00145548:0.000900933:0.97388:0.121742:360806:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121175 ES:SE:LP:AF:SS:ID   -0.00193544:0.000961026:1.35638:0.121175:360806:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120969 ES:SE:LP:AF:SS:ID   -0.00148405:0.000901418:1.00134:0.120969:360806:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578523   ES:SE:LP:AF:SS:ID   -0.00224152:0.00412403:0.231534:0.00578523:360806:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187907   ES:SE:LP:AF:SS:ID   0.0082102:0.00778522:0.535192:0.00187907:360806:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869735 ES:SE:LP:AF:SS:ID   0.00183273:0.000888652:1.40701:0.869735:360806:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00152775   ES:SE:LP:AF:SS:ID   2.86197e-05:0.00805348:0.00123297:0.00152775:360806:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122925 ES:SE:LP:AF:SS:ID   -0.00158563:0.000880094:1.14509:0.122925:360806:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14272  ES:SE:LP:AF:SS:ID   -0.00182223:0.000869905:1.44135:0.14272:360806:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123041 ES:SE:LP:AF:SS:ID   -0.00161518:0.000878867:1.17985:0.123041:360806:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87088  ES:SE:LP:AF:SS:ID   0.00141335:0.000856433:1.00485:0.87088:360806:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875464 ES:SE:LP:AF:SS:ID   0.0015158:0.000870632:1.08789:0.875464:360806:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128641 ES:SE:LP:AF:SS:ID   -0.00143575:0.00085857:1.02469:0.128641:360806:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.03637  ES:SE:LP:AF:SS:ID   0.00220487:0.00155753:0.804407:0.03637:360806:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870473 ES:SE:LP:AF:SS:ID   0.00141185:0.000855542:1.00482:0.870473:360806:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870579 ES:SE:LP:AF:SS:ID   0.00139802:0.000855933:0.989692:0.870579:360806:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87047  ES:SE:LP:AF:SS:ID   0.00141272:0.000855511:1.0058:0.87047:360806:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504757   ES:SE:LP:AF:SS:ID   -0.00201971:0.00439045:0.190104:0.00504757:360806:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501451   ES:SE:LP:AF:SS:ID   -0.00184756:0.0044022:0.170882:0.00501451:360806:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558365   ES:SE:LP:AF:SS:ID   -0.00201947:0.00425479:0.197193:0.00558365:360806:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870553 ES:SE:LP:AF:SS:ID   0.00145021:0.000854004:1.04826:0.870553:360806:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125995 ES:SE:LP:AF:SS:ID   -0.00158098:0.00087139:1.1572:0.125995:360806:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870116 ES:SE:LP:AF:SS:ID   0.00149552:0.000851947:1.10134:0.870116:360806:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869403 ES:SE:LP:AF:SS:ID   0.00143748:0.00085117:1.03975:0.869403:360806:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87027  ES:SE:LP:AF:SS:ID   0.00145884:0.000852681:1.05997:0.87027:360806:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870276 ES:SE:LP:AF:SS:ID   0.00145696:0.000852742:1.05782:0.870276:360806:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870285 ES:SE:LP:AF:SS:ID   0.00145443:0.000852769:1.05505:0.870285:360806:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870728 ES:SE:LP:AF:SS:ID   0.00143256:0.000854941:1.02774:0.870728:360806:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988444    ES:SE:LP:AF:SS:ID   -0.00131178:0.000993524:0.728798:0.0988444:360806:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647302   ES:SE:LP:AF:SS:ID   -0.002201:0.0038438:0.246486:0.00647302:360806:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874626 ES:SE:LP:AF:SS:ID   0.00154192:0.000867689:1.1217:0.874626:360806:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864015 ES:SE:LP:AF:SS:ID   0.0012329:0.000850891:0.831638:0.864015:360806:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869416 ES:SE:LP:AF:SS:ID   0.0014988:0.000859153:1.09113:0.869416:360806:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86636  ES:SE:LP:AF:SS:ID   0.00144269:0.000859327:1.03068:0.86636:360806:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987861    ES:SE:LP:AF:SS:ID   -0.00168314:0.0010288:0.992103:0.0987861:360806:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871547 ES:SE:LP:AF:SS:ID   0.00147026:0.000869122:1.04234:0.871547:360806:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871547 ES:SE:LP:AF:SS:ID   0.0014704:0.000869122:1.04248:0.871547:360806:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871546 ES:SE:LP:AF:SS:ID   0.00148117:0.000869139:1.05381:0.871546:360806:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87192  ES:SE:LP:AF:SS:ID   0.00153769:0.000869635:1.11335:0.87192:360806:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125571 ES:SE:LP:AF:SS:ID   -0.00157238:0.00087031:1.14989:0.125571:360806:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105431 ES:SE:LP:AF:SS:ID   -0.00118048:0.000947484:0.672035:0.105431:360806:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855365 ES:SE:LP:AF:SS:ID   0.001363:0.000850566:0.962362:0.855365:360806:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00165469   ES:SE:LP:AF:SS:ID   0.00150108:0.00753455:0.0746436:0.00165469:360806:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838366 ES:SE:LP:AF:SS:ID   0.00032423:0.000838022:0.155628:0.838366:360806:rs376645387