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-20544_5/ukb-d-20544_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-20544_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 16:50:35 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20544_5/ukb-d-20544_5.vcf.gz ...
Read summary statistics for 10066166 SNPs.
Dropped 7804 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, 1278574 SNPs remain.
After merging with regression SNP LD, 1278574 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0016 (0.0034)
Lambda GC: 1.0051
Mean Chi^2: 1.0037
Intercept: 0.9999 (0.006)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:52:18 2019
Total time elapsed: 1.0m:42.61s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.942,
    "inflation_factor": 0.9986,
    "mean_EFFECT": -4.9528e-06,
    "n": 117706,
    "n_snps": 10066166,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1086947,
    "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": 198711,
    "n_est": 117726.525,
    "ratio_se_n": 1.0001,
    "mean_diff": -0,
    "ratio_diff": 51.9408,
    "sd_y_est1": 0.1157,
    "sd_y_est2": 0.1157,
    "r2_sum1": 3.9491e-06,
    "r2_sum2": 0.0003,
    "r2_sum3": 0.0003,
    "r2_sum4": 0.0003,
    "ldsc_nsnp_merge_refpanel_ld": 1278574,
    "ldsc_nsnp_merge_regression_ld": 1278574,
    "ldsc_observed_scale_h2_beta": 0.0016,
    "ldsc_observed_scale_h2_se": 0.0034,
    "ldsc_intercept_beta": 0.9999,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0051,
    "ldsc_mean_chisq": 1.0037,
    "ldsc_ratio": -0.027
}

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 10058916 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 48391 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 30222 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.080685e+00 6.177618e+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 7.876148e+07 5.608177e+07 3.02000e+02 3.248971e+07 6.966985e+07 1.147306e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -5.000000e-06 1.164100e-03 -1.07279e-02 -5.409000e-04 -9.900000e-06 5.197000e-04 1.372510e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.952000e-04 6.124000e-04 3.95100e-04 5.258000e-04 7.188000e-04 1.290400e-03 3.510400e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.001122e-01 2.886806e-01 0.00000e+00 2.496347e-01 5.002994e-01 7.500842e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.001108e-01 2.886814e-01 0.00000e+00 2.496320e-01 5.002979e-01 7.500842e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.530632e-01 2.629623e-01 7.85670e-03 3.734530e-02 1.472120e-01 4.038950e-01 9.921430e-01 ▇▂▂▁▁
numeric AF_reference 198711 0.9802595 NA NA NA NA NA 2.527443e-01 2.538058e-01 0.00000e+00 4.133390e-02 1.631390e-01 4.001600e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.177060e+05 0.000000e+00 1.17706e+05 1.177060e+05 1.177060e+05 1.177060e+05 1.177060e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0008327 0.0008311 0.3164259 0.3164245 0.1116930 0.1894970 117706
1 693731 rs12238997 A G -0.0004947 0.0007870 0.5295915 0.5295913 0.1167340 0.1417730 117706
1 707522 rs371890604 G C -0.0005147 0.0008828 0.5598736 0.5598727 0.0983981 0.1293930 117706
1 717587 rs144155419 G A -0.0005954 0.0021176 0.7785634 0.7785629 0.0157480 0.0045926 117706
1 730087 rs148120343 T C -0.0019548 0.0010949 0.0742027 0.0742001 0.0569246 0.0127796 117706
1 731718 rs142557973 T C -0.0003530 0.0007467 0.6364203 0.6364193 0.1226670 0.1543530 117706
1 732032 rs61770163 A C -0.0004858 0.0007959 0.5415717 0.5415707 0.1222730 0.1555510 117706
1 734349 rs141242758 T C -0.0003714 0.0007471 0.6190703 0.6190699 0.1219240 0.1525560 117706
1 749963 rs529266287 T TAA 0.0004353 0.0007362 0.5542823 0.5542811 0.8690160 0.7641770 117706
1 751343 rs28544273 T A -0.0004685 0.0007293 0.5206226 0.5206223 0.1237000 0.2426120 117706
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0008344 0.0008781 0.3419676 0.3419660 0.0554558 0.0309934 117706
23 154923374 rs111332691 T A 0.0018139 0.0009566 0.0579389 0.0579355 0.0447811 0.0116556 117706
23 154925045 rs509981 C T -0.0005921 0.0004609 0.1989170 0.1989144 0.2446510 0.3634440 117706
23 154925895 rs538470 C T -0.0006149 0.0004713 0.1920189 0.1920166 0.2410720 0.3634440 117706
23 154927581 rs644138 G A -0.0003264 0.0004336 0.4516157 0.4516137 0.3004720 0.4635760 117706
23 154929412 rs557132 C T -0.0005738 0.0004610 0.2132141 0.2132113 0.2445260 0.3568210 117706
23 154929637 rs35185538 CT C -0.0005195 0.0004815 0.2806422 0.2806401 0.2287970 0.3011920 117706
23 154929952 rs4012982 CAA C -0.0004259 0.0004852 0.3800389 0.3800374 0.2386280 0.3165560 117706
23 154930230 rs781880 A G -0.0005902 0.0004609 0.2003180 0.2003159 0.2449510 0.3618540 117706
23 154930487 rs781879 T A -0.0023334 0.0015666 0.1363559 0.1363525 0.0196769 0.1263580 117706

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111693 ES:SE:LP:AF:SS:ID   -0.000832659:0.000831136:0.499728:0.111693:117706:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116734 ES:SE:LP:AF:SS:ID   -0.000494701:0.000786951:0.276059:0.116734:117706:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0983981    ES:SE:LP:AF:SS:ID   -0.000514721:0.000882837:0.25191:0.0983981:117706:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015748 ES:SE:LP:AF:SS:ID   -0.00059545:0.00211759:0.108706:0.015748:117706:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569246    ES:SE:LP:AF:SS:ID   -0.00195481:0.0010949:1.12958:0.0569246:117706:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122667 ES:SE:LP:AF:SS:ID   -0.000352972:0.000746697:0.196256:0.122667:117706:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122273 ES:SE:LP:AF:SS:ID   -0.000485825:0.000795861:0.266344:0.122273:117706:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121924 ES:SE:LP:AF:SS:ID   -0.000371427:0.000747084:0.20826:0.121924:117706:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.869016 ES:SE:LP:AF:SS:ID   0.00043533:0.000736154:0.256269:0.869016:117706:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.1237   ES:SE:LP:AF:SS:ID   -0.000468513:0.000729332:0.283477:0.1237:117706:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143341 ES:SE:LP:AF:SS:ID   -0.00014672:0.000721301:0.0763338:0.143341:117706:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123822 ES:SE:LP:AF:SS:ID   -0.000453918:0.000728321:0.273168:0.123822:117706:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869774 ES:SE:LP:AF:SS:ID   0.000342433:0.00070929:0.201176:0.869774:117706:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874549 ES:SE:LP:AF:SS:ID   0.000508784:0.000721194:0.318291:0.874549:117706:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129687 ES:SE:LP:AF:SS:ID   -0.000296419:0.000711274:0.169497:0.129687:117706:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365232    ES:SE:LP:AF:SS:ID   -0.000942392:0.0012917:0.331938:0.0365232:117706:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869367 ES:SE:LP:AF:SS:ID   0.000323065:0.000708614:0.18812:0.869367:117706:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869439 ES:SE:LP:AF:SS:ID   0.00031399:0.000708878:0.1819:0.869439:117706:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869367 ES:SE:LP:AF:SS:ID   0.000321543:0.000708595:0.187093:0.869367:117706:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.869442 ES:SE:LP:AF:SS:ID   0.000303845:0.000707295:0.175551:0.869442:117706:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126965 ES:SE:LP:AF:SS:ID   -0.000219278:0.000721991:0.118417:0.126965:117706:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868962 ES:SE:LP:AF:SS:ID   0.00025005:0.000705436:0.140866:0.868962:117706:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868361 ES:SE:LP:AF:SS:ID   0.000213287:0.000705168:0.117874:0.868361:117706:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869152 ES:SE:LP:AF:SS:ID   0.000275601:0.000706139:0.157191:0.869152:117706:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869159 ES:SE:LP:AF:SS:ID   0.000277181:0.00070619:0.15821:0.869159:117706:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869161 ES:SE:LP:AF:SS:ID   0.000276667:0.000706193:0.157873:0.869161:117706:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869596 ES:SE:LP:AF:SS:ID   0.000312706:0.000707999:0.181297:0.869596:117706:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0996031    ES:SE:LP:AF:SS:ID   -0.00071636:0.000822936:0.415633:0.0996031:117706:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.873655 ES:SE:LP:AF:SS:ID   0.000371461:0.000718873:0.217995:0.873655:117706:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862936 ES:SE:LP:AF:SS:ID   0.000315063:0.000705006:0.183791:0.862936:117706:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868346 ES:SE:LP:AF:SS:ID   0.000388775:0.000711806:0.232887:0.868346:117706:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865358 ES:SE:LP:AF:SS:ID   0.000387658:0.000711916:0.232044:0.865358:117706:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997425    ES:SE:LP:AF:SS:ID   -0.00046139:0.000850684:0.230947:0.0997425:117706:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870648 ES:SE:LP:AF:SS:ID   0.000387792:0.000720323:0.228905:0.870648:117706:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870648 ES:SE:LP:AF:SS:ID   0.000387643:0.000720323:0.2288:0.870648:117706:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870647 ES:SE:LP:AF:SS:ID   0.000387228:0.000720324:0.228507:0.870647:117706:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870969 ES:SE:LP:AF:SS:ID   0.000403617:0.000720628:0.240017:0.870969:117706:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126556 ES:SE:LP:AF:SS:ID   -0.000307143:0.000721202:0.173796:0.126556:117706:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106336 ES:SE:LP:AF:SS:ID   -0.000355213:0.000783781:0.186818:0.106336:117706:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854391 ES:SE:LP:AF:SS:ID   0.000230105:0.000704841:0.128384:0.854391:117706:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839149 ES:SE:LP:AF:SS:ID   6.61882e-05:0.00069844:0.0340926:0.839149:117706:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.763043 ES:SE:LP:AF:SS:ID   0.000332392:0.00055975:0.257564:0.763043:117706:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105241 ES:SE:LP:AF:SS:ID   -0.000312138:0.000774264:0.163142:0.105241:117706:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.129962 ES:SE:LP:AF:SS:ID   -0.000296296:0.000710954:0.169504:0.129962:117706:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.129662 ES:SE:LP:AF:SS:ID   -0.000258409:0.000710094:0.145131:0.129662:117706:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.104493 ES:SE:LP:AF:SS:ID   -0.000331714:0.000780298:0.173435:0.104493:117706:rs7518545
1   770181  rs146076599 A   G   .   PASS    AF=0.00916679   ES:SE:LP:AF:SS:ID   -0.00238621:0.00273036:0.417772:0.00916679:117706:rs146076599
1   770886  rs371458725 G   A   .   PASS    AF=0.103535 ES:SE:LP:AF:SS:ID   -0.000357598:0.000786824:0.187433:0.103535:117706:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.829221 ES:SE:LP:AF:SS:ID   -1.25387e-05:0.000692737:0.00631737:0.829221:117706:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.869016 ES:SE:LP:AF:SS:ID   0.000313581:0.000706779:0.182252:0.869016:117706:rs2977605