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-30810_irnt/ukb-d-30810_irnt.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-30810_irnt/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 14:57:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30810_irnt/ukb-d-30810_irnt.vcf.gz ...
Read summary statistics for 13585253 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1069 (0.01)
Lambda GC: 1.3892
Mean Chi^2: 1.731
Intercept: 1.0785 (0.0132)
Ratio: 0.1074 (0.018)
Analysis finished at Mon Nov 25 14:59:23 2019
Total time elapsed: 2.0m:12.11s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.2497,
    "mean_EFFECT": 6.7994e-06,
    "n": 314658,
    "n_snps": 13585253,
    "n_clumped_hits": 162,
    "n_p_sig": 22626,
    "n_mono": 0,
    "n_ns": 1251740,
    "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": 568957,
    "n_est": 315881.6753,
    "ratio_se_n": 1.0019,
    "mean_diff": -8.749e-07,
    "ratio_diff": 0.8082,
    "sd_y_est1": 0.9685,
    "sd_y_est2": 0.9704,
    "r2_sum1": 0.045,
    "r2_sum2": 0.048,
    "r2_sum3": 0.0478,
    "r2_sum4": 0.0477,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.1069,
    "ldsc_observed_scale_h2_se": 0.01,
    "ldsc_intercept_beta": 1.0785,
    "ldsc_intercept_se": 0.0132,
    "ldsc_lambda_gc": 1.3892,
    "ldsc_mean_chisq": 1.731,
    "ldsc_ratio": 0.1074
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
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 1.0000000 3 94 0 13573206 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57080 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33335 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051268e+00 6.184974e+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 7.902543e+07 5.591517e+07 3.02000e+02 3.293043e+07 7.013909e+07 1.148604e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 6.800000e-06 1.480940e-02 -2.79300e-01 -4.345800e-03 6.900000e-06 4.378100e-03 2.091400e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.025690e-02 9.893700e-03 2.00480e-03 2.920800e-03 5.381600e-03 1.473800e-02 4.987100e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.625833e-01 2.994468e-01 0.00000e+00 1.939001e-01 4.508499e-01 7.219099e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.625828e-01 2.994471e-01 0.00000e+00 1.939008e-01 4.508472e-01 7.219126e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908205e-01 2.544080e-01 1.00000e-03 7.434300e-03 6.004500e-02 2.953300e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 568957 0.9581195 NA NA NA NA NA 1.963466e-01 2.471050e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.146580e+05 0.000000e+00 3.14658e+05 3.146580e+05 3.146580e+05 3.146580e+05 3.146580e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0096199 0.0042770 0.0245008 0.0244987 0.1104900 0.1894970 314658
1 693731 rs12238997 A G 0.0071276 0.0040400 0.0776873 0.0776886 0.1158100 0.1417730 314658
1 707522 rs371890604 G C 0.0057752 0.0045460 0.2039501 0.2039452 0.0971780 0.1293930 314658
1 717587 rs144155419 G A 0.0084027 0.0108260 0.4376501 0.4376550 0.0157030 0.0045926 314658
1 723329 rs189787166 A T 0.0399170 0.0319980 0.2122198 0.2122200 0.0017313 0.0003994 314658
1 730087 rs148120343 T C 0.0108470 0.0056274 0.0539150 0.0539132 0.0564700 0.0127796 314658
1 731718 rs142557973 T C 0.0064768 0.0038323 0.0910207 0.0910173 0.1216900 0.1543530 314658
1 732032 rs61770163 A C 0.0064097 0.0040898 0.1170601 0.1170585 0.1210400 0.1555510 314658
1 734349 rs141242758 T C 0.0066200 0.0038344 0.0842597 0.0842618 0.1209100 0.1525560 314658
1 740284 rs61770167 C T -0.0026131 0.0175980 0.8819600 0.8819573 0.0057414 0.0023962 314658
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0048205 0.0044246 0.2759402 0.2759436 0.056080 0.0309934 314658
23 154923374 rs111332691 T A -0.0048247 0.0048416 0.3190098 0.3190027 0.045003 0.0116556 314658
23 154925045 rs509981 C T -0.0039427 0.0023372 0.0916242 0.0916162 0.245790 0.3634440 314658
23 154925895 rs538470 C T -0.0036025 0.0023909 0.1318700 0.1318735 0.242080 0.3634440 314658
23 154927581 rs644138 G A -0.0023939 0.0021983 0.2761799 0.2761637 0.302250 0.4635760 314658
23 154929412 rs557132 C T -0.0041548 0.0023379 0.0755492 0.0755435 0.245640 0.3568210 314658
23 154929637 rs35185538 CT C -0.0024207 0.0024396 0.3210902 0.3210742 0.230030 0.3011920 314658
23 154929952 rs4012982 CAA C -0.0045842 0.0024587 0.0622573 0.0622542 0.239560 0.3165560 314658
23 154930230 rs781880 A G -0.0041478 0.0023377 0.0760064 0.0760122 0.246010 0.3618540 314658
23 154930487 rs781879 T A -0.0035573 0.0080346 0.6579502 0.6579483 0.019470 0.1263580 314658

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11049  ES:SE:LP:AF:SS:ID   0.0096199:0.004277:1.61082:0.11049:314658:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11581  ES:SE:LP:AF:SS:ID   0.0071276:0.00404:1.10965:0.11581:314658:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097178 ES:SE:LP:AF:SS:ID   0.0057752:0.004546:0.690476:0.097178:314658:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015703 ES:SE:LP:AF:SS:ID   0.0084027:0.010826:0.358873:0.015703:314658:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017313    ES:SE:LP:AF:SS:ID   0.039917:0.031998:0.673214:0.0017313:314658:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.05647  ES:SE:LP:AF:SS:ID   0.010847:0.0056274:1.26829:0.05647:314658:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12169  ES:SE:LP:AF:SS:ID   0.0064768:0.0038323:1.04086:0.12169:314658:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12104  ES:SE:LP:AF:SS:ID   0.0064097:0.0040898:0.931591:0.12104:314658:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12091  ES:SE:LP:AF:SS:ID   0.00662:0.0038344:1.07438:0.12091:314658:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057414    ES:SE:LP:AF:SS:ID   -0.0026131:0.017598:0.0545511:0.0057414:314658:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018554    ES:SE:LP:AF:SS:ID   0.011089:0.033376:0.130944:0.0018554:314658:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86978  ES:SE:LP:AF:SS:ID   -0.0069225:0.0037801:1.17356:0.86978:314658:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015107    ES:SE:LP:AF:SS:ID   -0.043188:0.034448:0.677905:0.0015107:314658:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12287  ES:SE:LP:AF:SS:ID   0.0067972:0.003744:1.15831:0.12287:314658:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14268  ES:SE:LP:AF:SS:ID   0.0074729:0.0037:1.36238:0.14268:314658:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12299  ES:SE:LP:AF:SS:ID   0.0066757:0.0037388:1.12972:0.12299:314658:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87101  ES:SE:LP:AF:SS:ID   -0.0068419:0.0036442:1.21858:0.87101:314658:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87554  ES:SE:LP:AF:SS:ID   -0.0068282:0.0037037:1.18549:0.87554:314658:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12854  ES:SE:LP:AF:SS:ID   0.0072572:0.0036529:1.32827:0.12854:314658:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036328 ES:SE:LP:AF:SS:ID   -0.010182:0.0066273:0.90497:0.036328:314658:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8706   ES:SE:LP:AF:SS:ID   -0.0071198:0.0036402:1.29685:0.8706:314658:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87071  ES:SE:LP:AF:SS:ID   -0.0069256:0.003642:1.24239:0.87071:314658:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.8706   ES:SE:LP:AF:SS:ID   -0.0071087:0.0036401:1.29384:0.8706:314658:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050258    ES:SE:LP:AF:SS:ID   -0.0033892:0.018697:0.0674451:0.0050258:314658:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0049925    ES:SE:LP:AF:SS:ID   -0.0028375:0.018748:0.0556654:0.0049925:314658:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055162    ES:SE:LP:AF:SS:ID   0.0090324:0.018204:0.207769:0.0055162:314658:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87069  ES:SE:LP:AF:SS:ID   -0.0067778:0.0036341:1.20641:0.87069:314658:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12588  ES:SE:LP:AF:SS:ID   0.0070572:0.0037075:1.24429:0.12588:314658:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87026  ES:SE:LP:AF:SS:ID   -0.0067327:0.0036254:1.1986:0.87026:314658:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86954  ES:SE:LP:AF:SS:ID   -0.007168:0.0036221:1.32039:0.86954:314658:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87041  ES:SE:LP:AF:SS:ID   -0.0069777:0.0036285:1.26381:0.87041:314658:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87041  ES:SE:LP:AF:SS:ID   -0.0069773:0.0036287:1.26356:0.87041:314658:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87042  ES:SE:LP:AF:SS:ID   -0.0070078:0.0036288:1.27192:0.87042:314658:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87087  ES:SE:LP:AF:SS:ID   -0.0069097:0.003638:1.24011:0.87087:314658:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098764 ES:SE:LP:AF:SS:ID   0.0085534:0.0042284:1.36564:0.098764:314658:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0063964    ES:SE:LP:AF:SS:ID   0.00061101:0.016453:0.0130582:0.0063964:314658:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87471  ES:SE:LP:AF:SS:ID   -0.0072909:0.0036914:1.31645:0.87471:314658:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86414  ES:SE:LP:AF:SS:ID   -0.0068872:0.003621:1.24283:0.86414:314658:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86954  ES:SE:LP:AF:SS:ID   -0.0076133:0.0036554:1.42856:0.86954:314658:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86649  ES:SE:LP:AF:SS:ID   -0.0074469:0.0036562:1.38013:0.86649:314658:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098748 ES:SE:LP:AF:SS:ID   0.0074191:0.0043759:1.04581:0.098748:314658:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87165  ES:SE:LP:AF:SS:ID   -0.0070574:0.0036977:1.24938:0.87165:314658:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87165  ES:SE:LP:AF:SS:ID   -0.0070572:0.0036977:1.24933:0.87165:314658:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87165  ES:SE:LP:AF:SS:ID   -0.0070637:0.0036978:1.25105:0.87165:314658:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87201  ES:SE:LP:AF:SS:ID   -0.0069849:0.0036998:1.22887:0.87201:314658:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12549  ES:SE:LP:AF:SS:ID   0.0071212:0.0037024:1.26412:0.12549:314658:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10534  ES:SE:LP:AF:SS:ID   0.0076598:0.0040328:1.24023:0.10534:314658:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85548  ES:SE:LP:AF:SS:ID   -0.0067027:0.0036194:1.19354:0.85548:314658:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016488    ES:SE:LP:AF:SS:ID   0.041984:0.032087:0.719581:0.0016488:314658:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83826  ES:SE:LP:AF:SS:ID   -0.0020995:0.00356:0.255425:0.83826:314658:rs376645387