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-6020_33/ukb-d-6020_33.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-6020_33/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 16:31:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-6020_33/ukb-d-6020_33.vcf.gz ...
Read summary statistics for 11106900 SNPs.
Dropped 9206 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, 1282112 SNPs remain.
After merging with regression SNP LD, 1282112 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0238 (0.0095)
Lambda GC: 1.0244
Mean Chi^2: 1.0297
Intercept: 1.0044 (0.0062)
Ratio: 0.147 (0.2085)
Analysis finished at Mon Nov 25 16:33:02 2019
Total time elapsed: 1.0m:51.2s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9463,
    "inflation_factor": 1.0171,
    "mean_EFFECT": -1.8745e-06,
    "n": 54007,
    "n_snps": 11106900,
    "n_clumped_hits": 3,
    "n_p_sig": 8,
    "n_mono": 0,
    "n_ns": 1143333,
    "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": 224549,
    "n_est": 54150.5659,
    "ratio_se_n": 1.0013,
    "mean_diff": -9.1951e-06,
    "ratio_diff": 3.3213,
    "sd_y_est1": 0.2255,
    "sd_y_est2": 0.2258,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0018,
    "r2_sum3": 0.0018,
    "r2_sum4": 0.0018,
    "ldsc_nsnp_merge_refpanel_ld": 1282112,
    "ldsc_nsnp_merge_regression_ld": 1282112,
    "ldsc_observed_scale_h2_beta": 0.0238,
    "ldsc_observed_scale_h2_se": 0.0095,
    "ldsc_intercept_beta": 1.0044,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0244,
    "ldsc_mean_chisq": 1.0297,
    "ldsc_ratio": 0.1481
}
 

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 1.0000000 3 94 0 11098287 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 51359 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 31404 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.074380e+00 6.181310e+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 7.882323e+07 5.601887e+07 3.02000e+02 3.260311e+07 6.980549e+07 1.147405e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.900000e-06 4.328100e-03 -4.85617e-02 -1.719100e-03 -1.980000e-05 1.669100e-03 6.695750e-02 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.476700e-03 2.554300e-03 1.12690e-03 1.546600e-03 2.278600e-03 4.665400e-03 1.526490e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.975594e-01 2.895736e-01 0.00000e+00 2.458957e-01 4.963523e-01 7.487744e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.975564e-01 2.895754e-01 0.00000e+00 2.458911e-01 4.963493e-01 7.487736e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.309915e-01 2.616034e-01 4.27650e-03 2.320910e-02 1.156190e-01 3.695180e-01 9.957230e-01 ▇▂▂▁▁
numeric AF_reference 224549 0.9797829 NA NA NA NA NA 2.312936e-01 2.527331e-01 0.00000e+00 2.156550e-02 1.333870e-01 3.682110e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.400700e+04 0.000000e+00 5.40070e+04 5.400700e+04 5.400700e+04 5.400700e+04 5.400700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0013081 0.0023923 0.5845397 0.5845367 0.1121030 0.1894970 54007
1 693731 rs12238997 A G 0.0018944 0.0022682 0.4036036 0.4036003 0.1170180 0.1417730 54007
1 707522 rs371890604 G C 0.0065960 0.0025445 0.0095356 0.0095330 0.0983620 0.1293930 54007
1 717587 rs144155419 G A -0.0060685 0.0061728 0.3255622 0.3255574 0.0154496 0.0045926 54007
1 730087 rs148120343 T C 0.0035112 0.0031592 0.2663931 0.2663881 0.0570868 0.0127796 54007
1 731718 rs142557973 T C 0.0024428 0.0021520 0.2563209 0.2563167 0.1229180 0.1543530 54007
1 732032 rs61770163 A C 0.0034132 0.0022915 0.1363490 0.1363431 0.1226450 0.1555510 54007
1 734349 rs141242758 T C 0.0023198 0.0021542 0.2815237 0.2815199 0.1220820 0.1525560 54007
1 740284 rs61770167 C T -0.0163556 0.0091800 0.0748118 0.0748066 0.0066240 0.0023962 54007
1 749963 rs529266287 T TAA -0.0016137 0.0021227 0.4471343 0.4471314 0.8684610 0.7641770 54007
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0011745 0.0025263 0.6419985 0.6419948 0.0543009 0.0309934 54007
23 154923374 rs111332691 T A -0.0004833 0.0027427 0.8601169 0.8601163 0.0443554 0.0116556 54007
23 154925045 rs509981 C T -0.0010206 0.0013200 0.4394151 0.4394099 0.2425480 0.3634440 54007
23 154925895 rs538470 C T -0.0009902 0.0013495 0.4630725 0.4630692 0.2390400 0.3634440 54007
23 154927581 rs644138 G A -0.0005390 0.0012412 0.6640916 0.6640881 0.2972530 0.4635760 54007
23 154929412 rs557132 C T -0.0010250 0.0013204 0.4375876 0.4375877 0.2423940 0.3568210 54007
23 154929637 rs35185538 CT C -0.0018235 0.0013784 0.1858938 0.1858883 0.2266820 0.3011920 54007
23 154929952 rs4012982 CAA C -0.0012186 0.0013872 0.3796767 0.3796749 0.2367690 0.3165560 54007
23 154930230 rs781880 A G -0.0011033 0.0013201 0.4032849 0.4032828 0.2428410 0.3618540 54007
23 154930487 rs781879 T A -0.0009455 0.0046105 0.8375169 0.8375168 0.0187227 0.1263580 54007

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112103 ES:SE:LP:AF:SS:ID   0.00130806:0.00239234:0.233186:0.112103:54007:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117018 ES:SE:LP:AF:SS:ID   0.00189442:0.0022682:0.394045:0.117018:54007:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098362 ES:SE:LP:AF:SS:ID   0.00659604:0.00254445:2.02065:0.098362:54007:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0154496    ES:SE:LP:AF:SS:ID   -0.00606847:0.00617278:0.487366:0.0154496:54007:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0570868    ES:SE:LP:AF:SS:ID   0.00351115:0.00315916:0.574477:0.0570868:54007:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122918 ES:SE:LP:AF:SS:ID   0.00244281:0.00215199:0.591216:0.122918:54007:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122645 ES:SE:LP:AF:SS:ID   0.00341324:0.00229146:0.865348:0.122645:54007:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122082 ES:SE:LP:AF:SS:ID   0.00231985:0.00215417:0.550485:0.122082:54007:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00662398   ES:SE:LP:AF:SS:ID   -0.0163556:0.00918004:1.12603:0.00662398:54007:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.868461 ES:SE:LP:AF:SS:ID   -0.00161372:0.00212274:0.349562:0.868461:54007:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.124098 ES:SE:LP:AF:SS:ID   0.00254374:0.00210261:0.645198:0.124098:54007:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143405 ES:SE:LP:AF:SS:ID   0.00224069:0.00208596:0.548602:0.143405:54007:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.124231 ES:SE:LP:AF:SS:ID   0.00254142:0.00209923:0.645822:0.124231:54007:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869563 ES:SE:LP:AF:SS:ID   -0.00220999:0.0020447:0.553194:0.869563:54007:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874342 ES:SE:LP:AF:SS:ID   -0.00228137:0.00207902:0.56463:0.874342:54007:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12998  ES:SE:LP:AF:SS:ID   0.00242087:0.00204938:0.624336:0.12998:54007:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0364212    ES:SE:LP:AF:SS:ID   0.000705526:0.00372396:0.070716:0.0364212:54007:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8692   ES:SE:LP:AF:SS:ID   -0.00227287:0.002043:0.575246:0.8692:54007:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869321 ES:SE:LP:AF:SS:ID   -0.00233215:0.00204429:0.595247:0.869321:54007:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869211 ES:SE:LP:AF:SS:ID   -0.00227493:0.00204293:0.57598:0.869211:54007:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00522899   ES:SE:LP:AF:SS:ID   0.0175689:0.010345:1.04839:0.00522899:54007:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00519954   ES:SE:LP:AF:SS:ID   0.017772:0.0103721:1.0623:0.00519954:54007:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00560715   ES:SE:LP:AF:SS:ID   -0.0232763:0.0101653:1.65683:0.00560715:54007:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869334 ES:SE:LP:AF:SS:ID   -0.00220494:0.00203975:0.553297:0.869334:54007:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127255 ES:SE:LP:AF:SS:ID   0.00250103:0.00208096:0.639365:0.127255:54007:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868934 ES:SE:LP:AF:SS:ID   -0.00226408:0.00203517:0.57522:0.868934:54007:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86804  ES:SE:LP:AF:SS:ID   -0.00237886:0.00203217:0.616608:0.86804:54007:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869085 ES:SE:LP:AF:SS:ID   -0.00223718:0.00203674:0.565382:0.869085:54007:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869091 ES:SE:LP:AF:SS:ID   -0.00223957:0.00203688:0.56615:0.869091:54007:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.8691   ES:SE:LP:AF:SS:ID   -0.00223813:0.00203695:0.565628:0.8691:54007:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869495 ES:SE:LP:AF:SS:ID   -0.00223238:0.00204199:0.561785:0.869495:54007:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0998575    ES:SE:LP:AF:SS:ID   0.00340315:0.00237076:0.820563:0.0998575:54007:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00638995   ES:SE:LP:AF:SS:ID   -0.0169805:0.00922977:1.18171:0.00638995:54007:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87353  ES:SE:LP:AF:SS:ID   -0.00231171:0.00207296:0.577113:0.87353:54007:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862691 ES:SE:LP:AF:SS:ID   -0.00280549:0.0020322:0.776156:0.862691:54007:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868349 ES:SE:LP:AF:SS:ID   -0.00226728:0.00205354:0.569341:0.868349:54007:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.864973 ES:SE:LP:AF:SS:ID   -0.0020717:0.00205172:0.504975:0.864973:54007:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997018    ES:SE:LP:AF:SS:ID   0.00138756:0.00245677:0.242438:0.0997018:54007:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870319 ES:SE:LP:AF:SS:ID   -0.00254088:0.0020755:0.655855:0.870319:54007:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870319 ES:SE:LP:AF:SS:ID   -0.00254085:0.0020755:0.655846:0.870319:54007:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870316 ES:SE:LP:AF:SS:ID   -0.00254073:0.00207551:0.6558:0.870316:54007:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870734 ES:SE:LP:AF:SS:ID   -0.00250465:0.00207695:0.642345:0.870734:54007:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.1267   ES:SE:LP:AF:SS:ID   0.00262414:0.00207847:0.684527:0.1267:54007:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106448 ES:SE:LP:AF:SS:ID   0.00305243:0.00226158:0.75173:0.106448:54007:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854048 ES:SE:LP:AF:SS:ID   -0.00197306:0.0020335:0.478978:0.854048:54007:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836519 ES:SE:LP:AF:SS:ID   -0.000843994:0.00199526:0.172438:0.836519:54007:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.760857 ES:SE:LP:AF:SS:ID   -0.00132662:0.00160577:0.388577:0.760857:54007:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.107079 ES:SE:LP:AF:SS:ID   -0.000557803:0.00220692:0.0966598:0.107079:54007:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00743713   ES:SE:LP:AF:SS:ID   0.00107503:0.00845974:0.0462983:0.00743713:54007:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.130059 ES:SE:LP:AF:SS:ID   0.00256504:0.00204943:0.67628:0.130059:54007:rs762168062