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-20118_5/ukb-d-20118_5.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-20118_5/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 16:38:22 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20118_5/ukb-d-20118_5.vcf.gz ...
Read summary statistics for 13586469 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: 0.0061 (0.0014)
Lambda GC: 1.1657
Mean Chi^2: 1.1611
Intercept: 1.1188 (0.0066)
Ratio: 0.7375 (0.0407)
Analysis finished at Mon Nov 25 16:40:28 2019
Total time elapsed: 2.0m:5.6s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1472,
    "mean_EFFECT": 0,
    "n": 357712,
    "n_snps": 13586469,
    "n_clumped_hits": 0,
    "n_p_sig": 4,
    "n_mono": 0,
    "n_ns": 1251794,
    "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": 569258,
    "n_est": 359074.6673,
    "ratio_se_n": 1.0019,
    "mean_diff": 0.0001,
    "ratio_diff": 24.9888,
    "sd_y_est1": 0.3995,
    "sd_y_est2": 0.4003,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0061,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.1188,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.1657,
    "ldsc_mean_chisq": 1.1611,
    "ldsc_ratio": 0.7374
}

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 13574422 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57081 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33336 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051325e+00 6.184990e+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 7.902516e+07 5.591490e+07 3.02000e+02 3.293090e+07 7.013866e+07 1.148591e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.300000e-05 5.883800e-03 -8.00288e-02 -1.524500e-03 2.280000e-05 1.593300e-03 7.526720e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.969500e-03 3.829000e-03 7.76800e-04 1.130100e-03 2.082500e-03 5.704500e-03 1.927960e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.781182e-01 2.939714e-01 0.00000e+00 2.177790e-01 4.700337e-01 7.326238e-01 1.000000e+00 ▇▇▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.781178e-01 2.939716e-01 0.00000e+00 2.177781e-01 4.700330e-01 7.326238e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908033e-01 2.544027e-01 1.00000e-03 7.429500e-03 6.003180e-02 2.953090e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569258 0.9581011 NA NA NA NA NA 1.963342e-01 2.471010e-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 3.577120e+05 0.000000e+00 3.57712e+05 3.577120e+05 3.577120e+05 3.577120e+05 3.577120e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0003358 0.0016537 0.8390681 0.8390680 0.1107240 0.1894970 357712
1 693731 rs12238997 A G 0.0011206 0.0015627 0.4733125 0.4733093 0.1158980 0.1417730 357712
1 707522 rs371890604 G C 0.0004368 0.0017568 0.8036199 0.8036200 0.0973675 0.1293930 357712
1 717587 rs144155419 G A 0.0028545 0.0041936 0.4960815 0.4960816 0.0156859 0.0045926 357712
1 723329 rs189787166 A T 0.0309577 0.0123463 0.0121607 0.0121607 0.0017396 0.0003994 357712
1 730087 rs148120343 T C 0.0012148 0.0021765 0.5767306 0.5767298 0.0565115 0.0127796 357712
1 731718 rs142557973 T C 0.0008098 0.0014821 0.5848116 0.5848100 0.1218030 0.1543530 357712
1 732032 rs61770163 A C 0.0004875 0.0015810 0.7578007 0.7578003 0.1212390 0.1555510 357712
1 734349 rs141242758 T C 0.0008024 0.0014829 0.5884465 0.5884455 0.1210310 0.1525560 357712
1 740284 rs61770167 C T 0.0025647 0.0067725 0.7049105 0.7049113 0.0058047 0.0023962 357712
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0003032 0.0017128 0.8595030 0.8595032 0.0561556 0.0309934 357712
23 154923374 rs111332691 T A -0.0022774 0.0018832 0.2265458 0.2265434 0.0447734 0.0116556 357712
23 154925045 rs509981 C T 0.0007408 0.0009058 0.4134195 0.4134196 0.2456140 0.3634440 357712
23 154925895 rs538470 C T 0.0009018 0.0009265 0.3303901 0.3303901 0.2419220 0.3634440 357712
23 154927581 rs644138 G A 0.0006362 0.0008518 0.4551033 0.4551020 0.3021610 0.4635760 357712
23 154929412 rs557132 C T 0.0007090 0.0009060 0.4338654 0.4338640 0.2454660 0.3568210 357712
23 154929637 rs35185538 CT C 0.0001296 0.0009456 0.8909881 0.8909879 0.2296840 0.3011920 357712
23 154929952 rs4012982 CAA C 0.0005530 0.0009529 0.5617150 0.5617152 0.2394310 0.3165560 357712
23 154930230 rs781880 A G 0.0006055 0.0009059 0.5038625 0.5038617 0.2458740 0.3618540 357712
23 154930487 rs781879 T A -0.0005555 0.0031084 0.8581741 0.8581738 0.0195614 0.1263580 357712

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110724 ES:SE:LP:AF:SS:ID   0.000335849:0.00165373:0.0762028:0.110724:357712:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115898 ES:SE:LP:AF:SS:ID   0.00112062:0.0015627:0.324852:0.115898:357712:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973675    ES:SE:LP:AF:SS:ID   0.000436847:0.00175677:0.0949493:0.0973675:357712:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156859    ES:SE:LP:AF:SS:ID   0.00285447:0.00419363:0.304447:0.0156859:357712:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173965   ES:SE:LP:AF:SS:ID   0.0309577:0.0123463:1.91504:0.00173965:357712:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0565115    ES:SE:LP:AF:SS:ID   0.00121483:0.00217646:0.239027:0.0565115:357712:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121803 ES:SE:LP:AF:SS:ID   0.000809773:0.00148209:0.232984:0.121803:357712:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121239 ES:SE:LP:AF:SS:ID   0.000487534:0.001581:0.120445:0.121239:357712:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121031 ES:SE:LP:AF:SS:ID   0.000802377:0.00148289:0.230293:0.121031:357712:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00580468   ES:SE:LP:AF:SS:ID   0.00256474:0.0067725:0.151866:0.00580468:357712:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187759   ES:SE:LP:AF:SS:ID   0.00531148:0.0128136:0.168454:0.00187759:357712:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869658 ES:SE:LP:AF:SS:ID   -0.00153145:0.00146185:0.530445:0.869658:357712:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00152205   ES:SE:LP:AF:SS:ID   -0.000783904:0.0132795:0.0209404:0.00152205:357712:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123001 ES:SE:LP:AF:SS:ID   0.000753367:0.00144775:0.219822:0.123001:357712:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142797 ES:SE:LP:AF:SS:ID   0.00151275:0.001431:0.536923:0.142797:357712:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123117 ES:SE:LP:AF:SS:ID   0.000628971:0.00144574:0.178143:0.123117:357712:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870799 ES:SE:LP:AF:SS:ID   -0.000800389:0.00140881:0.244166:0.870799:357712:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875387 ES:SE:LP:AF:SS:ID   -0.000361013:0.0014322:0.096374:0.875387:357712:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128727 ES:SE:LP:AF:SS:ID   0.000898714:0.00141231:0.280211:0.128727:357712:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363491    ES:SE:LP:AF:SS:ID   0.00136074:0.0025634:0.225093:0.0363491:357712:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87039  ES:SE:LP:AF:SS:ID   -0.000862459:0.00140734:0.267615:0.87039:357712:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870496 ES:SE:LP:AF:SS:ID   -0.000810223:0.00140799:0.24796:0.870496:357712:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870389 ES:SE:LP:AF:SS:ID   -0.00086705:0.00140729:0.269363:0.870389:357712:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00505015   ES:SE:LP:AF:SS:ID   -0.00767422:0.00722208:0.540665:0.00505015:357712:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501698   ES:SE:LP:AF:SS:ID   -0.00758288:0.00724139:0.530138:0.00501698:357712:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558678   ES:SE:LP:AF:SS:ID   0.000195744:0.00699877:0.00980016:0.00558678:357712:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870472 ES:SE:LP:AF:SS:ID   -0.00070614:0.00140483:0.210977:0.870472:357712:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126072 ES:SE:LP:AF:SS:ID   0.000633825:0.00143345:0.181531:0.126072:357712:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870038 ES:SE:LP:AF:SS:ID   -0.000597915:0.00140147:0.174155:0.870038:357712:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869322 ES:SE:LP:AF:SS:ID   -0.000697626:0.00140015:0.208795:0.869322:357712:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87019  ES:SE:LP:AF:SS:ID   -0.000650809:0.00140265:0.192019:0.87019:357712:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870196 ES:SE:LP:AF:SS:ID   -0.000651735:0.00140275:0.192323:0.870196:357712:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870205 ES:SE:LP:AF:SS:ID   -0.000652981:0.0014028:0.192746:0.870205:357712:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870648 ES:SE:LP:AF:SS:ID   -0.000728479:0.00140636:0.218629:0.870648:357712:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0989131    ES:SE:LP:AF:SS:ID   0.000475384:0.00163427:0.112867:0.0989131:357712:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00648077   ES:SE:LP:AF:SS:ID   -0.00545482:0.00632171:0.410934:0.00648077:357712:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874551 ES:SE:LP:AF:SS:ID   -0.00065508:0.00142736:0.189584:0.874551:357712:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863924 ES:SE:LP:AF:SS:ID   -0.000915165:0.00139967:0.289702:0.863924:357712:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869335 ES:SE:LP:AF:SS:ID   -0.000618027:0.0014133:0.179208:0.869335:357712:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866284 ES:SE:LP:AF:SS:ID   -0.00102869:0.00141357:0.330886:0.866284:357712:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0988419    ES:SE:LP:AF:SS:ID   0.00129967:0.00169252:0.354035:0.0988419:357712:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871475 ES:SE:LP:AF:SS:ID   -0.000979817:0.00142969:0.307036:0.871475:357712:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871475 ES:SE:LP:AF:SS:ID   -0.000979642:0.00142969:0.306968:0.871475:357712:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871474 ES:SE:LP:AF:SS:ID   -0.000977685:0.00142972:0.306201:0.871474:357712:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871846 ES:SE:LP:AF:SS:ID   -0.000883435:0.00143053:0.270132:0.871846:357712:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125652 ES:SE:LP:AF:SS:ID   0.000658153:0.00143165:0.189956:0.125652:357712:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10551  ES:SE:LP:AF:SS:ID   0.000398262:0.00155841:0.0978377:0.10551:357712:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855281 ES:SE:LP:AF:SS:ID   -0.000859463:0.00139917:0.268378:0.855281:357712:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00166014   ES:SE:LP:AF:SS:ID   0.0303353:0.0123728:1.84723:0.00166014:357712:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838262 ES:SE:LP:AF:SS:ID   -0.00125085:0.00137866:0.438598:0.838262:357712:rs376645387