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-30620_irnt/ukb-d-30620_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-30620_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 15:34:46 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30620_irnt/ukb-d-30620_irnt.vcf.gz ...
Read summary statistics for 13585999 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: 0.1163 (0.0078)
Lambda GC: 1.4749
Mean Chi^2: 1.9163
Intercept: 1.0916 (0.0143)
Ratio: 0.1 (0.0156)
Analysis finished at Mon Nov 25 15:37:03 2019
Total time elapsed: 2.0m:16.7s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.2906,
    "mean_EFFECT": 9.4684e-06,
    "n": 344136,
    "n_snps": 13585999,
    "n_clumped_hits": 207,
    "n_p_sig": 31646,
    "n_mono": 0,
    "n_ns": 1251779,
    "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": 569168,
    "n_est": 345462.8355,
    "ratio_se_n": 1.0019,
    "mean_diff": -1.6269e-07,
    "ratio_diff": 0.1897,
    "sd_y_est1": 0.9299,
    "sd_y_est2": 0.9316,
    "r2_sum1": 0.0429,
    "r2_sum2": 0.0496,
    "r2_sum3": 0.0494,
    "r2_sum4": 0.0493,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1163,
    "ldsc_observed_scale_h2_se": 0.0078,
    "ldsc_intercept_beta": 1.0916,
    "ldsc_intercept_se": 0.0143,
    "ldsc_lambda_gc": 1.4749,
    "ldsc_mean_chisq": 1.9163,
    "ldsc_ratio": 0.1
}

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 13573952 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 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051235e+00 6.184968e+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 7.902581e+07 5.591512e+07 3.02000e+02 3.293112e+07 7.013976e+07 1.148604e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 9.500000e-06 1.367680e-02 -1.22420e+00 -4.093400e-03 2.300000e-06 4.094100e-03 2.867700e-01 ▁▁▁▁▇
numeric SE 0 1.0000000 NA NA NA NA NA 9.418300e-03 9.085000e-03 1.84280e-03 2.681500e-03 4.941400e-03 1.353500e-02 4.588200e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.574523e-01 3.012845e-01 0.00000e+00 1.853600e-01 4.435300e-01 7.185202e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.574518e-01 3.012847e-01 0.00000e+00 1.853595e-01 4.435275e-01 7.185241e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908098e-01 2.544045e-01 1.00000e-03 7.431400e-03 6.004000e-02 2.953200e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569168 0.9581063 NA NA NA NA NA 1.963393e-01 2.471026e-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 3.441360e+05 0.000000e+00 3.44136e+05 3.441360e+05 3.441360e+05 3.441360e+05 3.441360e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0043653 0.0039254 0.2661099 0.2661102 0.1105400 0.1894970 344136
1 693731 rs12238997 A G -0.0010756 0.0037076 0.7717400 0.7717345 0.1158200 0.1417730 344136
1 707522 rs371890604 G C 0.0000472 0.0041702 0.9909700 0.9909742 0.0972600 0.1293930 344136
1 717587 rs144155419 G A -0.0130360 0.0099548 0.1903501 0.1903586 0.0156650 0.0045926 344136
1 723329 rs189787166 A T -0.0388590 0.0293220 0.1850900 0.1850880 0.0017369 0.0003994 344136
1 730087 rs148120343 T C -0.0000917 0.0051673 0.9858400 0.9858418 0.0564320 0.0127796 344136
1 731718 rs142557973 T C -0.0012498 0.0035166 0.7222907 0.7222899 0.1217100 0.1543530 344136
1 732032 rs61770163 A C 0.0001049 0.0037523 0.9776900 0.9776950 0.1211200 0.1555510 344136
1 734349 rs141242758 T C -0.0010473 0.0035184 0.7659598 0.7659598 0.1209400 0.1525560 344136
1 740284 rs61770167 C T -0.0067048 0.0161360 0.6777695 0.6777627 0.0057580 0.0023962 344136
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0012056 0.0040637 0.7667098 0.7667143 0.056197 0.0309934 344136
23 154923374 rs111332691 T A 0.0065110 0.0044604 0.1443600 0.1443630 0.044883 0.0116556 344136
23 154925045 rs509981 C T -0.0083291 0.0021487 0.0001061 0.0001060 0.245650 0.3634440 344136
23 154925895 rs538470 C T -0.0088450 0.0021980 0.0000572 0.0000572 0.241990 0.3634440 344136
23 154927581 rs644138 G A -0.0070578 0.0020208 0.0004785 0.0004784 0.302240 0.4635760 344136
23 154929412 rs557132 C T -0.0082585 0.0021494 0.0001219 0.0001219 0.245510 0.3568210 344136
23 154929637 rs35185538 CT C -0.0081360 0.0022434 0.0002871 0.0002871 0.229760 0.3011920 344136
23 154929952 rs4012982 CAA C -0.0088271 0.0022605 0.0000943 0.0000943 0.239490 0.3165560 344136
23 154930230 rs781880 A G -0.0086577 0.0021490 0.0000561 0.0000561 0.245910 0.3618540 344136
23 154930487 rs781879 T A -0.0141860 0.0073671 0.0541552 0.0541558 0.019560 0.1263580 344136

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11054  ES:SE:LP:AF:SS:ID   -0.0043653:0.0039254:0.574939:0.11054:344136:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11582  ES:SE:LP:AF:SS:ID   -0.0010756:0.0037076:0.112529:0.11582:344136:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.09726  ES:SE:LP:AF:SS:ID   4.7175e-05:0.0041702:0.00393949:0.09726:344136:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015665 ES:SE:LP:AF:SS:ID   -0.013036:0.0099548:0.720447:0.015665:344136:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017369    ES:SE:LP:AF:SS:ID   -0.038859:0.029322:0.732617:0.0017369:344136:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056432 ES:SE:LP:AF:SS:ID   -9.1697e-05:0.0051673:0.00619356:0.056432:344136:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12171  ES:SE:LP:AF:SS:ID   -0.0012498:0.0035166:0.141288:0.12171:344136:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12112  ES:SE:LP:AF:SS:ID   0.00010491:0.0037523:0.00979883:0.12112:344136:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12094  ES:SE:LP:AF:SS:ID   -0.0010473:0.0035184:0.115794:0.12094:344136:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.005758 ES:SE:LP:AF:SS:ID   -0.0067048:0.016136:0.168918:0.005758:344136:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018606    ES:SE:LP:AF:SS:ID   -0.028738:0.030604:0.458783:0.0018606:344136:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86979  ES:SE:LP:AF:SS:ID   0.0023188:0.0034688:0.297716:0.86979:344136:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015222    ES:SE:LP:AF:SS:ID   0.02276:0.031499:0.327948:0.0015222:344136:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12289  ES:SE:LP:AF:SS:ID   -0.0016148:0.0034351:0.194975:0.12289:344136:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14271  ES:SE:LP:AF:SS:ID   -0.0018773:0.003395:0.236362:0.14271:344136:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12301  ES:SE:LP:AF:SS:ID   -0.0015247:0.0034303:0.182633:0.12301:344136:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87095  ES:SE:LP:AF:SS:ID   0.001563:0.0033432:0.193725:0.87095:344136:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87551  ES:SE:LP:AF:SS:ID   0.0012437:0.0033982:0.146071:0.87551:344136:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12859  ES:SE:LP:AF:SS:ID   -0.0016369:0.0033515:0.203932:0.12859:344136:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.03631  ES:SE:LP:AF:SS:ID   0.0036866:0.0060858:0.263867:0.03631:344136:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   0.0017604:0.0033398:0.223219:0.87054:344136:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   0.0017013:0.0033413:0.214215:0.87064:344136:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   0.0017339:0.0033396:0.219229:0.87054:344136:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050484    ES:SE:LP:AF:SS:ID   -0.005785:0.017132:0.133352:0.0050484:344136:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050154    ES:SE:LP:AF:SS:ID   -0.0054876:0.017177:0.125304:0.0050154:344136:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.005547 ES:SE:LP:AF:SS:ID   0.0077912:0.016669:0.193684:0.005547:344136:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87063  ES:SE:LP:AF:SS:ID   0.0016396:0.0033339:0.205603:0.87063:344136:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12593  ES:SE:LP:AF:SS:ID   -0.0017803:0.0034015:0.221335:0.12593:344136:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.8702   ES:SE:LP:AF:SS:ID   0.0018254:0.003326:0.234242:0.8702:344136:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86947  ES:SE:LP:AF:SS:ID   0.0018617:0.0033229:0.240106:0.86947:344136:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87034  ES:SE:LP:AF:SS:ID   0.0017689:0.0033287:0.225381:0.87034:344136:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87035  ES:SE:LP:AF:SS:ID   0.0017599:0.003329:0.223997:0.87035:344136:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   0.0017859:0.0033291:0.227942:0.87036:344136:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8708   ES:SE:LP:AF:SS:ID   0.001725:0.0033375:0.218058:0.8708:344136:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098801 ES:SE:LP:AF:SS:ID   -8.9718e-05:0.0038788:0.00808757:0.098801:344136:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064331    ES:SE:LP:AF:SS:ID   0.0026635:0.015059:0.0656985:0.0064331:344136:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87469  ES:SE:LP:AF:SS:ID   0.002086:0.003387:0.26925:0.87469:344136:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.8641   ES:SE:LP:AF:SS:ID   0.002145:0.0033221:0.28526:0.8641:344136:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86948  ES:SE:LP:AF:SS:ID   0.0015436:0.0033538:0.190225:0.86948:344136:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86642  ES:SE:LP:AF:SS:ID   0.0028015:0.0033544:0.394017:0.86642:344136:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098755 ES:SE:LP:AF:SS:ID   -0.00065357:0.0040156:0.0601265:0.098755:344136:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.8716   ES:SE:LP:AF:SS:ID   0.0028674:0.0033928:0.400084:0.8716:344136:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.8716   ES:SE:LP:AF:SS:ID   0.0028673:0.0033928:0.400073:0.8716:344136:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.8716   ES:SE:LP:AF:SS:ID   0.0028669:0.0033928:0.399997:0.8716:344136:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87197  ES:SE:LP:AF:SS:ID   0.0026999:0.0033947:0.370162:0.87197:344136:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12553  ES:SE:LP:AF:SS:ID   -0.0016989:0.0033971:0.209722:0.12553:344136:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.1054   ES:SE:LP:AF:SS:ID   -0.00045578:0.0036991:0.0448224:0.1054:344136:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85544  ES:SE:LP:AF:SS:ID   0.0024537:0.0033207:0.33728:0.85544:344136:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016557    ES:SE:LP:AF:SS:ID   -0.039419:0.029396:0.744921:0.0016557:344136:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83825  ES:SE:LP:AF:SS:ID   0.0013844:0.0032699:0.172618:0.83825:344136:rs376645387