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-3942/ukb-d-3942.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-3942/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 17:19:52 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-3942/ukb-d-3942.vcf.gz ...
Read summary statistics for 9421414 SNPs.
Dropped 6953 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, 1271594 SNPs remain.
After merging with regression SNP LD, 1271594 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.018 (0.1145)
Lambda GC: 0.9963
Mean Chi^2: 1.0002
Intercept: 1.0015 (0.0059)
Ratio: 9.64 (37.4113)
Analysis finished at Mon Nov 25 17:21:24 2019
Total time elapsed: 1.0m:31.74s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9383,
    "inflation_factor": 0.9968,
    "mean_EFFECT": 0,
    "n": 3812,
    "n_snps": 9421414,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1045432,
    "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": 188921,
    "n_est": 3828.0497,
    "ratio_se_n": 1.0021,
    "mean_diff": 0.0001,
    "ratio_diff": 63.2579,
    "sd_y_est1": 0.3795,
    "sd_y_est2": 0.3803,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1271594,
    "ldsc_nsnp_merge_regression_ld": 1271594,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0015,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 0.9963,
    "ldsc_mean_chisq": 1.0002,
    "ldsc_ratio": 7.5
}
 

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
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 9415004 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 98 0 46091 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 29282 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.080184e+00 6.174689e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.870323e+07 5.611217e+07 302.0000000 3.241314e+07 6.957643e+07 1.147100e+08 2.492297e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 4.220000e-05 1.842260e-02 -0.1763830 -9.147700e-03 -3.910000e-05 9.106800e-03 1.904510e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.624640e-02 8.738600e-03 0.0070362 9.474000e-03 1.242000e-02 2.058530e-02 5.074650e-02 ▇▂▂▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.007111e-01 2.889820e-01 0.0000002 2.503831e-01 5.006774e-01 7.510918e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 5.006691e-01 2.890073e-01 0.0000002 2.503102e-01 5.006357e-01 7.510739e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.684840e-01 2.626085e-01 0.0115960 4.980300e-02 1.692250e-01 4.263080e-01 9.884030e-01 ▇▂▂▁▁
numeric AF_reference 188921 0.9799477 NA NA NA NA NA 2.677494e-01 2.534153e-01 0.0000000 5.710860e-02 1.837060e-01 4.209270e-01 1.000000e+00 ▇▃▂▂▁
numeric N 0 1.0000000 NA NA NA NA NA 3.812000e+03 0.000000e+00 3812.0000000 3.812000e+03 3.812000e+03 3.812000e+03 3.812000e+03 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0178783 0.0153533 0.2443110 0.2442377 0.1109350 0.1894970 3812
1 693731 rs12238997 A G -0.0090359 0.0143464 0.5288384 0.5288000 0.1160390 0.1417730 3812
1 707522 rs371890604 G C -0.0199183 0.0158224 0.2081579 0.2080783 0.0993395 0.1293930 3812
1 717587 rs144155419 G A -0.0210197 0.0408432 0.6068313 0.6068019 0.0144667 0.0045926 3812
1 730087 rs148120343 T C -0.0152597 0.0195374 0.4348205 0.4347727 0.0581806 0.0127796 3812
1 731718 rs142557973 T C -0.0147280 0.0136121 0.2793303 0.2792621 0.1220400 0.1543530 3812
1 732032 rs61770163 A C -0.0204212 0.0144546 0.1578000 0.1577198 0.1222580 0.1555510 3812
1 734349 rs141242758 T C -0.0133847 0.0136181 0.3257399 0.3256758 0.1211950 0.1525560 3812
1 749963 rs529266287 T TAA 0.0203048 0.0133912 0.1295341 0.1294487 0.8703790 0.7641770 3812
1 751343 rs28544273 T A -0.0200419 0.0132227 0.1296731 0.1295904 0.1238970 0.2426120 3812
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0165063 0.0147580 0.2634390 0.2633686 0.0622827 0.0309934 3812
23 154923374 rs111332691 T A 0.0253687 0.0177640 0.1533458 0.1532642 0.0426285 0.0116556 3812
23 154925045 rs509981 C T 0.0148895 0.0083143 0.0733990 0.0733205 0.2455680 0.3634440 3812
23 154925895 rs538470 C T 0.0157580 0.0085134 0.0642510 0.0641734 0.2416960 0.3634440 3812
23 154927581 rs644138 G A 0.0084830 0.0077516 0.2738729 0.2738035 0.3083830 0.4635760 3812
23 154929412 rs557132 C T 0.0151717 0.0083189 0.0682669 0.0681879 0.2453380 0.3568210 3812
23 154929637 rs35185538 CT C 0.0172739 0.0086592 0.0461296 0.0460580 0.2306410 0.3011920 3812
23 154929952 rs4012982 CAA C 0.0175772 0.0087469 0.0445513 0.0444804 0.2381120 0.3165560 3812
23 154930230 rs781880 A G 0.0154490 0.0083219 0.0634702 0.0633921 0.2450720 0.3618540 3812
23 154930487 rs781879 T A -0.0546851 0.0298533 0.0670610 0.0669821 0.0196222 0.1263580 3812

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110935 ES:SE:LP:AF:SS:ID   -0.0178783:0.0153533:0.612057:0.110935:3812:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116039 ES:SE:LP:AF:SS:ID   -0.00903592:0.0143464:0.276677:0.116039:3812:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0993395    ES:SE:LP:AF:SS:ID   -0.0199183:0.0158224:0.681607:0.0993395:3812:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0144667    ES:SE:LP:AF:SS:ID   -0.0210197:0.0408432:0.216932:0.0144667:3812:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0581806    ES:SE:LP:AF:SS:ID   -0.0152597:0.0195374:0.36169:0.0581806:3812:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12204  ES:SE:LP:AF:SS:ID   -0.014728:0.0136121:0.553882:0.12204:3812:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122258 ES:SE:LP:AF:SS:ID   -0.0204212:0.0144546:0.801893:0.122258:3812:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121195 ES:SE:LP:AF:SS:ID   -0.0133847:0.0136181:0.487129:0.121195:3812:rs141242758
1   749963  rs529266287 T   TAA .   PASS    AF=0.870379 ES:SE:LP:AF:SS:ID   0.0203048:0.0133912:0.887616:0.870379:3812:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123897 ES:SE:LP:AF:SS:ID   -0.0200419:0.0132227:0.88715:0.123897:3812:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.144056 ES:SE:LP:AF:SS:ID   -0.0105941:0.0131073:0.377795:0.144056:3812:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123985 ES:SE:LP:AF:SS:ID   -0.0199207:0.0132024:0.881348:0.123985:3812:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.8712   ES:SE:LP:AF:SS:ID   0.0160548:0.012905:0.670502:0.8712:3812:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874362 ES:SE:LP:AF:SS:ID   0.0159797:0.0130622:0.655079:0.874362:3812:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128211 ES:SE:LP:AF:SS:ID   -0.0171215:0.0129477:0.730184:0.128211:3812:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0346275    ES:SE:LP:AF:SS:ID   -0.00950629:0.0241179:0.158962:0.0346275:3812:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870886 ES:SE:LP:AF:SS:ID   0.0162774:0.0128988:0.683923:0.870886:3812:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.871147 ES:SE:LP:AF:SS:ID   0.0149292:0.0129217:0.605519:0.871147:3812:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.871006 ES:SE:LP:AF:SS:ID   0.0160843:0.0129015:0.672469:0.871006:3812:rs3131967
1   755890  rs3115858   A   T   .   PASS    AF=0.870663 ES:SE:LP:AF:SS:ID   0.0162645:0.0128607:0.685985:0.870663:3812:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125944 ES:SE:LP:AF:SS:ID   -0.0192595:0.0131194:0.847149:0.125944:3812:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870409 ES:SE:LP:AF:SS:ID   0.0164088:0.0128317:0.696687:0.870409:3812:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869894 ES:SE:LP:AF:SS:ID   0.0151884:0.0128256:0.62636:0.869894:3812:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870492 ES:SE:LP:AF:SS:ID   0.0164156:0.0128466:0.695953:0.870492:3812:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870515 ES:SE:LP:AF:SS:ID   0.0163718:0.0128493:0.693159:0.870515:3812:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870524 ES:SE:LP:AF:SS:ID   0.016361:0.0128493:0.69253:0.870524:3812:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870726 ES:SE:LP:AF:SS:ID   0.0163694:0.0128696:0.691495:0.870726:3812:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100286 ES:SE:LP:AF:SS:ID   -0.0188632:0.0147869:0.694324:0.100286:3812:rs10157329
1   759837  rs3115851   T   A   .   PASS    AF=0.874242 ES:SE:LP:AF:SS:ID   0.0186232:0.0130479:0.813668:0.874242:3812:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863959 ES:SE:LP:AF:SS:ID   0.0154385:0.0128298:0.640311:0.863959:3812:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868787 ES:SE:LP:AF:SS:ID   0.0184052:0.0129394:0.809702:0.868787:3812:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866426 ES:SE:LP:AF:SS:ID   0.0199349:0.0129352:0.908798:0.866426:3812:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0983288    ES:SE:LP:AF:SS:ID   -0.023211:0.0156595:0.858983:0.0983288:3812:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871622 ES:SE:LP:AF:SS:ID   0.0190178:0.0130986:0.83383:0.871622:3812:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871621 ES:SE:LP:AF:SS:ID   0.0190207:0.0130985:0.834014:0.871621:3812:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871617 ES:SE:LP:AF:SS:ID   0.0190165:0.0130986:0.833748:0.871617:3812:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871816 ES:SE:LP:AF:SS:ID   0.018958:0.0130968:0.830232:0.871816:3812:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125924 ES:SE:LP:AF:SS:ID   -0.0203676:0.0130997:0.920551:0.125924:3812:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106492 ES:SE:LP:AF:SS:ID   -0.0161259:0.0141779:0.592708:0.106492:3812:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855804 ES:SE:LP:AF:SS:ID   0.0174102:0.0128518:0.755485:0.855804:3812:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.835157 ES:SE:LP:AF:SS:ID   -0.0154248:0.0126019:0.655551:0.835157:3812:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.758674 ES:SE:LP:AF:SS:ID   -0.00210108:0.0101187:0.0780431:0.758674:3812:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.11031  ES:SE:LP:AF:SS:ID   0.0229958:0.0139114:1.00696:0.11031:3812:rs12562034
1   769138  rs59306077  CAT C   .   PASS    AF=0.12921  ES:SE:LP:AF:SS:ID   -0.0185557:0.0129288:0.820144:0.12921:3812:rs762168062
1   769223  rs60320384  C   G   .   PASS    AF=0.12847  ES:SE:LP:AF:SS:ID   -0.0180465:0.0129316:0.787983:0.12847:3812:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.109808 ES:SE:LP:AF:SS:ID   0.0230367:0.0139935:1.00088:0.109808:3812:rs7518545
1   770886  rs371458725 G   A   .   PASS    AF=0.109288 ES:SE:LP:AF:SS:ID   0.0216487:0.0140752:0.906176:0.109288:3812:rs371458725
1   771410  rs2519006   C   T   .   PASS    AF=0.828198 ES:SE:LP:AF:SS:ID   0.0168799:0.0126408:0.740301:0.828198:3812:rs2519006
1   771823  rs2977605   T   C   .   PASS    AF=0.870107 ES:SE:LP:AF:SS:ID   0.0161267:0.0128699:0.677239:0.870107:3812:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.128549 ES:SE:LP:AF:SS:ID   -0.0184086:0.0129291:0.810833:0.128549:3812:rs59066358