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_2/ukb-d-5832_2.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_2/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 16:53:02 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-5832_2/ukb-d-5832_2.vcf.gz ...
Read summary statistics for 9390074 SNPs.
Dropped 6891 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, 1271319 SNPs remain.
After merging with regression SNP LD, 1271319 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0102 (0.0314)
Lambda GC: 1.0069
Mean Chi^2: 1.0063
Intercept: 1.0032 (0.0065)
Ratio: 0.5083 (1.0353)
Analysis finished at Mon Nov 25 16:54:35 2019
Total time elapsed: 1.0m:32.54s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9382,
    "inflation_factor": 1.0103,
    "mean_EFFECT": 9.6162e-06,
    "n": 15090,
    "n_snps": 9390074,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1043092,
    "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": 188435,
    "n_est": 15111.5187,
    "ratio_se_n": 1.0007,
    "mean_diff": 0,
    "ratio_diff": 10.4693,
    "sd_y_est1": 0.2558,
    "sd_y_est2": 0.256,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0022,
    "r2_sum3": 0.0022,
    "r2_sum4": 0.002,
    "ldsc_nsnp_merge_refpanel_ld": 1271319,
    "ldsc_nsnp_merge_regression_ld": 1271319,
    "ldsc_observed_scale_h2_beta": 0.0102,
    "ldsc_observed_scale_h2_se": 0.0314,
    "ldsc_intercept_beta": 1.0032,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0069,
    "ldsc_mean_chisq": 1.0063,
    "ldsc_ratio": 0.5079
}

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 9383720 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 45975 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 29268 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.080971e+00 6.173983e+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 7.870010e+07 5.611520e+07 3.02000e+02 3.240930e+07 6.956693e+07 1.147262e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 9.600000e-06 6.221500e-03 -5.42379e-02 -3.118500e-03 -2.380000e-05 3.086600e-03 6.750090e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 5.476400e-03 2.923700e-03 2.44330e-03 3.207100e-03 4.196200e-03 6.932800e-03 1.643980e-02 ▇▂▂▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.984685e-01 2.887925e-01 0.00000e+00 2.477068e-01 4.978053e-01 7.486055e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.984579e-01 2.887989e-01 0.00000e+00 2.476889e-01 4.977948e-01 7.486016e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.692879e-01 2.625758e-01 1.18149e-02 5.042670e-02 1.704430e-01 4.274590e-01 9.881850e-01 ▇▃▂▁▁
numeric AF_reference 188435 0.9799325 NA NA NA NA NA 2.685575e-01 2.533845e-01 0.00000e+00 5.810700e-02 1.849040e-01 4.221250e-01 1.000000e+00 ▇▃▂▂▁
numeric N 0 1.0000000 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 0.0016994 0.0050458 0.7362834 0.7362774 0.1141820 0.1894970 15090
1 693731 rs12238997 A G 0.0025252 0.0048264 0.6008375 0.6008311 0.1191660 0.1417730 15090
1 707522 rs371890604 G C 0.0034541 0.0054051 0.5228017 0.5227924 0.1002410 0.1293930 15090
1 717587 rs144155419 G A -0.0061341 0.0129306 0.6352300 0.6352222 0.0160220 0.0045926 15090
1 730087 rs148120343 T C -0.0023477 0.0066887 0.7255995 0.7255950 0.0583691 0.0127796 15090
1 731718 rs142557973 T C 0.0032277 0.0045731 0.4803204 0.4803086 0.1251690 0.1543530 15090
1 732032 rs61770163 A C 0.0041770 0.0048739 0.3914470 0.3914328 0.1249330 0.1555510 15090
1 734349 rs141242758 T C 0.0032797 0.0045770 0.4736516 0.4736413 0.1244210 0.1525560 15090
1 749963 rs529266287 T TAA -0.0018947 0.0044996 0.6736914 0.6736854 0.8658230 0.7641770 15090
1 751343 rs28544273 T A 0.0034082 0.0044604 0.4448064 0.4447948 0.1264000 0.2426120 15090
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0055341 0.0057364 0.3346933 0.3346773 0.0505719 0.0309934 15090
23 154923374 rs111332691 T A 0.0055860 0.0059748 0.3498461 0.3498302 0.0447647 0.0116556 15090
23 154925045 rs509981 C T 0.0011038 0.0028446 0.6979832 0.6979784 0.2480630 0.3634440 15090
23 154925895 rs538470 C T 0.0011272 0.0029061 0.6981215 0.6981175 0.2443550 0.3634440 15090
23 154927581 rs644138 G A 0.0021196 0.0026951 0.4316095 0.4315977 0.2990900 0.4635760 15090
23 154929412 rs557132 C T 0.0010116 0.0028453 0.7221842 0.7221804 0.2479080 0.3568210 15090
23 154929637 rs35185538 CT C 0.0033919 0.0029627 0.2522830 0.2522649 0.2322830 0.3011920 15090
23 154929952 rs4012982 CAA C 0.0013652 0.0029989 0.6489496 0.6489427 0.2412620 0.3165560 15090
23 154930230 rs781880 A G 0.0010535 0.0028443 0.7110940 0.7110903 0.2483550 0.3618540 15090
23 154930487 rs781879 T A 0.0071764 0.0099907 0.4725775 0.4725664 0.0189192 0.1263580 15090

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.114182 ES:SE:LP:AF:SS:ID   0.00169935:0.00504577:0.132955:0.114182:15090:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.119166 ES:SE:LP:AF:SS:ID   0.0025252:0.0048264:0.221243:0.119166:15090:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.100241 ES:SE:LP:AF:SS:ID   0.0034541:0.00540508:0.281663:0.100241:15090:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.016022 ES:SE:LP:AF:SS:ID   -0.00613414:0.0129306:0.197069:0.016022:15090:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0583691    ES:SE:LP:AF:SS:ID   -0.00234766:0.00668866:0.139303:0.0583691:15090:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.125169 ES:SE:LP:AF:SS:ID   0.00322773:0.00457311:0.318469:0.125169:15090:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.124933 ES:SE:LP:AF:SS:ID   0.00417703:0.00487389:0.407327:0.124933:15090:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.124421 ES:SE:LP:AF:SS:ID   0.00327972:0.00457699:0.324541:0.124421:15090:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.865823 ES:SE:LP:AF:SS:ID   -0.00189474:0.00449955:0.171539:0.865823:15090:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.1264   ES:SE:LP:AF:SS:ID   0.00340825:0.00446035:0.351829:0.1264:15090:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145816 ES:SE:LP:AF:SS:ID   0.00223391:0.00442497:0.212059:0.145816:15090:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12651  ES:SE:LP:AF:SS:ID   0.00327668:0.00445241:0.335563:0.12651:15090:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.867093 ES:SE:LP:AF:SS:ID   -0.0026964:0.00434052:0.272078:0.867093:15090:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.871738 ES:SE:LP:AF:SS:ID   -0.00302211:0.00440356:0.307557:0.871738:15090:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.132054 ES:SE:LP:AF:SS:ID   0.00301613:0.00435745:0.310837:0.132054:15090:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363486    ES:SE:LP:AF:SS:ID   0.00649116:0.00799306:0.380126:0.0363486:15090:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.866748 ES:SE:LP:AF:SS:ID   -0.00278744:0.00433678:0.283663:0.866748:15090:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86685  ES:SE:LP:AF:SS:ID   -0.00258149:0.00433924:0.258134:0.86685:15090:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.866753 ES:SE:LP:AF:SS:ID   -0.00277581:0.00433655:0.28223:0.866753:15090:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.86685  ES:SE:LP:AF:SS:ID   -0.00246808:0.00432968:0.245147:0.86685:15090:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.129382 ES:SE:LP:AF:SS:ID   0.00256528:0.00441949:0.250556:0.129382:15090:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.866435 ES:SE:LP:AF:SS:ID   -0.00240164:0.00431902:0.237939:0.866435:15090:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.865611 ES:SE:LP:AF:SS:ID   -0.00223366:0.0043122:0.21862:0.865611:15090:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.866618 ES:SE:LP:AF:SS:ID   -0.00248886:0.00432428:0.248009:0.866618:15090:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866626 ES:SE:LP:AF:SS:ID   -0.00247343:0.00432466:0.246131:0.866626:15090:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.866628 ES:SE:LP:AF:SS:ID   -0.00248048:0.00432458:0.246983:0.866628:15090:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.866976 ES:SE:LP:AF:SS:ID   -0.00233048:0.0043334:0.228613:0.866976:15090:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.101528 ES:SE:LP:AF:SS:ID   0.0032611:0.00503507:0.286338:0.101528:15090:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.870911 ES:SE:LP:AF:SS:ID   -0.00244387:0.00439336:0.238043:0.870911:15090:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860219 ES:SE:LP:AF:SS:ID   -0.00212853:0.00431353:0.206421:0.860219:15090:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.865558 ES:SE:LP:AF:SS:ID   -0.00268531:0.00435428:0.269672:0.865558:15090:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.861992 ES:SE:LP:AF:SS:ID   -0.00272832:0.00435041:0.275252:0.861992:15090:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100985 ES:SE:LP:AF:SS:ID   0.00352737:0.00525091:0.299518:0.100985:15090:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.867571 ES:SE:LP:AF:SS:ID   -0.00271359:0.00440213:0.269522:0.867571:15090:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.867571 ES:SE:LP:AF:SS:ID   -0.00271348:0.00440213:0.26951:0.867571:15090:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.867567 ES:SE:LP:AF:SS:ID   -0.00271374:0.00440215:0.269539:0.867567:15090:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.868076 ES:SE:LP:AF:SS:ID   -0.00301885:0.0044054:0.306987:0.868076:15090:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.129005 ES:SE:LP:AF:SS:ID   0.00289909:0.00441094:0.291553:0.129005:15090:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.107962 ES:SE:LP:AF:SS:ID   0.00396898:0.00481395:0.387552:0.107962:15090:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852157 ES:SE:LP:AF:SS:ID   -0.000750678:0.00431033:0.0646217:0.852157:15090:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837669 ES:SE:LP:AF:SS:ID   0.00396788:0.00430994:0.44702:0.837669:15090:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.760109 ES:SE:LP:AF:SS:ID   -0.000277772:0.00344272:0.0288657:0.760109:15090:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105368 ES:SE:LP:AF:SS:ID   -0.00135776:0.00476628:0.110279:0.105368:15090:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.132311 ES:SE:LP:AF:SS:ID   0.00258247:0.00435427:0.257172:0.132311:15090:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.131976 ES:SE:LP:AF:SS:ID   0.00234038:0.00435172:0.228619:0.131976:15090:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104429 ES:SE:LP:AF:SS:ID   -0.00156814:0.00481414:0.128061:0.104429:15090:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.103545 ES:SE:LP:AF:SS:ID   -0.00171649:0.00485106:0.140582:0.103545:15090:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.827683 ES:SE:LP:AF:SS:ID   -0.00122898:0.00424561:0.112256:0.827683:15090:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.86651  ES:SE:LP:AF:SS:ID   -0.00212417:0.00432879:0.205066:0.86651:15090:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.132021 ES:SE:LP:AF:SS:ID   0.00242523:0.00435025:0.238674:0.132021:15090:rs59066358