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-5832_1/ukb-d-5832_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-5832_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 16:52:52 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5832_1/ukb-d-5832_1.vcf.gz ...
Read summary statistics for 9491153 SNPs.
Dropped 7031 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, 1272855 SNPs remain.
After merging with regression SNP LD, 1272855 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0682 (0.0273)
Lambda GC: 1.0105
Mean Chi^2: 1.0111
Intercept: 0.9906 (0.0055)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:54:25 2019
Total time elapsed: 1.0m:33.87s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9388,
    "inflation_factor": 1.0107,
    "mean_EFFECT": 0,
    "n": 15090,
    "n_snps": 9491153,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1050076,
    "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": 189956,
    "n_est": 15105.0084,
    "ratio_se_n": 1.0005,
    "mean_diff": 0.0001,
    "ratio_diff": 26.3186,
    "sd_y_est1": 0.2636,
    "sd_y_est2": 0.2637,
    "r2_sum1": 0.0002,
    "r2_sum2": 0.0023,
    "r2_sum3": 0.0023,
    "r2_sum4": 0.0022,
    "ldsc_nsnp_merge_refpanel_ld": 1272855,
    "ldsc_nsnp_merge_regression_ld": 1272855,
    "ldsc_observed_scale_h2_beta": 0.0682,
    "ldsc_observed_scale_h2_se": 0.0273,
    "ldsc_intercept_beta": 0.9906,
    "ldsc_intercept_se": 0.0055,
    "ldsc_lambda_gc": 1.0105,
    "ldsc_mean_chisq": 1.0111,
    "ldsc_ratio": -0.8468
}

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 9484658 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 98 0 46353 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 29412 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.079882e+00 6.174407e+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 7.871428e+07 5.611231e+07 3.02000e+02 3.241989e+07 6.958893e+07 1.147393e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 2.690000e-05 6.543300e-03 -5.90116e-02 -3.249300e-03 -5.000000e-06 3.224100e-03 6.956360e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 5.735600e-03 3.132400e-03 2.51660e-03 3.309400e-03 4.358300e-03 7.289900e-03 1.755870e-02 ▇▂▂▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.979836e-01 2.891719e-01 0.00000e+00 2.466658e-01 4.977245e-01 7.481867e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.979730e-01 2.891782e-01 0.00000e+00 2.466472e-01 4.977146e-01 7.481815e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 2.667401e-01 2.626874e-01 1.11014e-02 4.825320e-02 1.667820e-01 4.237530e-01 9.888990e-01 ▇▂▂▁▁
numeric AF_reference 189956 0.979986 NA NA NA NA NA 2.660756e-01 2.534982e-01 0.00000e+00 5.531150e-02 1.813100e-01 4.187300e-01 1.000000e+00 ▇▃▂▂▁
numeric N 0 1.000000 NA NA NA NA NA 1.509000e+04 0.000000e+00 1.50900e+04 1.509000e+04 1.509000e+04 1.509000e+04 1.509000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0096376 0.0051966 0.0636708 0.0636514 0.1141820 0.1894970 15090
1 693731 rs12238997 A G -0.0109916 0.0049704 0.0270228 0.0270086 0.1191660 0.1417730 15090
1 707522 rs371890604 G C -0.0131880 0.0055663 0.0178361 0.0178234 0.1002410 0.1293930 15090
1 717587 rs144155419 G A -0.0098964 0.0133184 0.4574567 0.4574449 0.0160220 0.0045926 15090
1 730087 rs148120343 T C -0.0209427 0.0068872 0.0023636 0.0023595 0.0583691 0.0127796 15090
1 731718 rs142557973 T C -0.0108394 0.0047096 0.0213722 0.0213595 0.1251690 0.1543530 15090
1 732032 rs61770163 A C -0.0089440 0.0050197 0.0748066 0.0747864 0.1249330 0.1555510 15090
1 734349 rs141242758 T C -0.0107436 0.0047136 0.0226642 0.0226497 0.1244210 0.1525560 15090
1 749963 rs529266287 T TAA 0.0090382 0.0046340 0.0511458 0.0511268 0.8658230 0.7641770 15090
1 751343 rs28544273 T A -0.0095482 0.0045936 0.0376721 0.0376559 0.1264000 0.2426120 15090
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0043548 0.0059086 0.4611190 0.4611071 0.0505719 0.0309934 15090
23 154923374 rs111332691 T A 0.0146816 0.0061531 0.0170432 0.0170306 0.0447647 0.0116556 15090
23 154925045 rs509981 C T -0.0034571 0.0029298 0.2380192 0.2380016 0.2480630 0.3634440 15090
23 154925895 rs538470 C T -0.0030496 0.0029932 0.3083032 0.3082857 0.2443550 0.3634440 15090
23 154927581 rs644138 G A -0.0041859 0.0027758 0.1315770 0.1315551 0.2990900 0.4635760 15090
23 154929412 rs557132 C T -0.0034223 0.0029306 0.2429143 0.2428945 0.2479080 0.3568210 15090
23 154929637 rs35185538 CT C -0.0020329 0.0030516 0.5053241 0.5053124 0.2322830 0.3011920 15090
23 154929952 rs4012982 CAA C -0.0041776 0.0030887 0.1762191 0.1761974 0.2412620 0.3165560 15090
23 154930230 rs781880 A G -0.0033352 0.0029295 0.2549453 0.2549274 0.2483550 0.3618540 15090
23 154930487 rs781879 T A -0.0043183 0.0102906 0.6747579 0.6747525 0.0189192 0.1263580 15090

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.114182 ES:SE:LP:AF:SS:ID   -0.00963765:0.00519658:1.19606:0.114182:15090:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.119166 ES:SE:LP:AF:SS:ID   -0.0109916:0.00497044:1.56827:0.119166:15090:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.100241 ES:SE:LP:AF:SS:ID   -0.013188:0.00556628:1.7487:0.100241:15090:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.016022 ES:SE:LP:AF:SS:ID   -0.00989638:0.0133184:0.33965:0.016022:15090:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0583691    ES:SE:LP:AF:SS:ID   -0.0209427:0.00688724:2.62643:0.0583691:15090:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.125169 ES:SE:LP:AF:SS:ID   -0.0108394:0.00470957:1.67015:0.125169:15090:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.124933 ES:SE:LP:AF:SS:ID   -0.00894398:0.00501971:1.12606:0.124933:15090:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.124421 ES:SE:LP:AF:SS:ID   -0.0107436:0.00471357:1.64466:0.124421:15090:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.865823 ES:SE:LP:AF:SS:ID   0.0090382:0.00463399:1.29119:0.865823:15090:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.1264   ES:SE:LP:AF:SS:ID   -0.00954817:0.0045936:1.42398:0.1264:15090:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145816 ES:SE:LP:AF:SS:ID   -0.0102679:0.004557:1.6151:0.145816:15090:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12651  ES:SE:LP:AF:SS:ID   -0.00967743:0.0045854:1.45801:0.12651:15090:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.867093 ES:SE:LP:AF:SS:ID   0.00869649:0.00447024:1.28615:0.867093:15090:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.871738 ES:SE:LP:AF:SS:ID   0.00923178:0.00453512:1.37876:0.871738:15090:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.132054 ES:SE:LP:AF:SS:ID   -0.00933567:0.00448761:1.42582:0.132054:15090:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363486    ES:SE:LP:AF:SS:ID   0.00833504:0.00823277:0.506748:0.0363486:15090:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.866748 ES:SE:LP:AF:SS:ID   0.00888535:0.00446637:1.3309:0.866748:15090:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86685  ES:SE:LP:AF:SS:ID   0.00882985:0.0044689:1.31704:0.86685:15090:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.866753 ES:SE:LP:AF:SS:ID   0.00889446:0.00446612:1.33311:0.866753:15090:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.86685  ES:SE:LP:AF:SS:ID   0.00861287:0.00445907:1.27217:0.86685:15090:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.129382 ES:SE:LP:AF:SS:ID   -0.00969503:0.00455145:1.47913:0.129382:15090:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.866435 ES:SE:LP:AF:SS:ID   0.00880232:0.00444806:1.32017:0.866435:15090:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.865611 ES:SE:LP:AF:SS:ID   0.00889845:0.00444103:1.34562:0.865611:15090:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866618 ES:SE:LP:AF:SS:ID   0.00870012:0.0044535:1.29436:0.866618:15090:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866626 ES:SE:LP:AF:SS:ID   0.00869791:0.00445389:1.29369:0.866626:15090:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.866628 ES:SE:LP:AF:SS:ID   0.00869374:0.00445381:1.29278:0.866628:15090:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.866976 ES:SE:LP:AF:SS:ID   0.00860971:0.0044629:1.2698:0.866976:15090:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.101528 ES:SE:LP:AF:SS:ID   -0.00955545:0.00518562:1.18445:0.101528:15090:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.870911 ES:SE:LP:AF:SS:ID   0.00919654:0.0045246:1.37557:0.870911:15090:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860219 ES:SE:LP:AF:SS:ID   0.00846763:0.00444245:1.24673:0.860219:15090:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.865558 ES:SE:LP:AF:SS:ID   0.00912899:0.00448436:1.37889:0.865558:15090:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.861992 ES:SE:LP:AF:SS:ID   0.00850236:0.00448046:1.23837:0.861992:15090:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100985 ES:SE:LP:AF:SS:ID   -0.0114283:0.00540772:1.46106:0.100985:15090:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.867571 ES:SE:LP:AF:SS:ID   0.00937343:0.00453362:1.41228:0.867571:15090:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.867571 ES:SE:LP:AF:SS:ID   0.0093735:0.00453362:1.4123:0.867571:15090:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.867567 ES:SE:LP:AF:SS:ID   0.00936991:0.00453364:1.41145:0.867567:15090:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.868076 ES:SE:LP:AF:SS:ID   0.00935264:0.004537:1.40582:0.868076:15090:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.129005 ES:SE:LP:AF:SS:ID   -0.00952064:0.00454268:1.44232:0.129005:15090:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107962 ES:SE:LP:AF:SS:ID   -0.00946454:0.00495789:1.24962:0.107962:15090:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852157 ES:SE:LP:AF:SS:ID   0.00920848:0.00443902:1.41958:0.852157:15090:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837669 ES:SE:LP:AF:SS:ID   -0.00204082:0.00443934:0.189949:0.837669:15090:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.760109 ES:SE:LP:AF:SS:ID   0.00268036:0.00354595:0.347054:0.760109:15090:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105368 ES:SE:LP:AF:SS:ID   0.00557907:0.00490908:0.592144:0.105368:15090:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.132311 ES:SE:LP:AF:SS:ID   -0.00988664:0.00448423:1.56089:0.132311:15090:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.131976 ES:SE:LP:AF:SS:ID   -0.00956804:0.00448164:1.48437:0.131976:15090:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104429 ES:SE:LP:AF:SS:ID   0.00550355:0.00495839:0.573425:0.104429:15090:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.103545 ES:SE:LP:AF:SS:ID   0.00561829:0.00499641:0.583637:0.103545:15090:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.827683 ES:SE:LP:AF:SS:ID   0.00711893:0.00437261:0.984934:0.827683:15090:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.86651  ES:SE:LP:AF:SS:ID   0.00894983:0.0044581:1.3496:0.86651:15090:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.132021 ES:SE:LP:AF:SS:ID   -0.00955133:0.00448013:1.48111:0.132021:15090:rs59066358