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-20541/ukb-d-20541.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-20541/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 17:13:57 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20541/ukb-d-20541.vcf.gz ...
Read summary statistics for 13542675 SNPs.
Dropped 12658 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, 1283493 SNPs remain.
After merging with regression SNP LD, 1283493 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.031 (0.0124)
Lambda GC: 1.0116
Mean Chi^2: 1.0187
Intercept: 0.9968 (0.0059)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:16:15 2019
Total time elapsed: 2.0m:18.12s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0091,
    "mean_EFFECT": -9.3999e-06,
    "n": 35523,
    "n_snps": 13542675,
    "n_clumped_hits": 1,
    "n_p_sig": 20,
    "n_mono": 0,
    "n_ns": 1250259,
    "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": 557765,
    "n_est": 35638.4755,
    "ratio_se_n": 1.0016,
    "mean_diff": -0,
    "ratio_diff": 60.9907,
    "sd_y_est1": 0.2343,
    "sd_y_est2": 0.2346,
    "r2_sum1": 0,
    "r2_sum2": 0.0009,
    "r2_sum3": 0.0009,
    "r2_sum4": 0.0009,
    "ldsc_nsnp_merge_refpanel_ld": 1283493,
    "ldsc_nsnp_merge_regression_ld": 1283493,
    "ldsc_observed_scale_h2_beta": 0.031,
    "ldsc_observed_scale_h2_se": 0.0124,
    "ldsc_intercept_beta": 0.9968,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0116,
    "ldsc_mean_chisq": 1.0187,
    "ldsc_ratio": -0.1711
}

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 13530681 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57003 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33314 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051573e+00 6.185138e+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 7.902392e+07 5.591568e+07 3.02000e+02 3.292529e+07 7.013903e+07 1.148574e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -9.400000e-06 1.016620e-02 -1.49056e-01 -2.629600e-03 5.070000e-05 2.794700e-03 1.277670e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 7.324500e-03 7.050600e-03 1.49450e-03 2.099900e-03 3.852600e-03 1.050810e-02 3.852790e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.983211e-01 2.892997e-01 0.00000e+00 2.470279e-01 4.980650e-01 7.490624e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.983166e-01 2.893024e-01 0.00000e+00 2.470203e-01 4.980607e-01 7.490613e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.913828e-01 2.545421e-01 1.00000e-03 7.581100e-03 6.070260e-02 2.965140e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 557765 0.9588143 NA NA NA NA NA 1.967567e-01 2.471924e-01 0.00000e+00 5.790700e-03 8.486420e-02 3.089060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.552300e+04 0.000000e+00 3.55230e+04 3.552300e+04 3.552300e+04 3.552300e+04 3.552300e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0009194 0.0030512 0.7631677 0.7631656 0.1128590 0.1894970 35523
1 693731 rs12238997 A G -0.0007795 0.0028805 0.7866816 0.7866797 0.1180610 0.1417730 35523
1 707522 rs371890604 G C -0.0023799 0.0032373 0.4622607 0.4622563 0.0994655 0.1293930 35523
1 717587 rs144155419 G A 0.0004684 0.0075855 0.9507580 0.9507577 0.0164936 0.0045926 35523
1 723329 rs189787166 A T 0.0033760 0.0224233 0.8803270 0.8803257 0.0018331 0.0003994 35523
1 730087 rs148120343 T C 0.0011860 0.0039974 0.7667062 0.7667056 0.0575976 0.0127796 35523
1 731718 rs142557973 T C -0.0007013 0.0027311 0.7973561 0.7973552 0.1246270 0.1543530 35523
1 732032 rs61770163 A C -0.0013154 0.0029124 0.6515279 0.6515258 0.1240240 0.1555510 35523
1 734349 rs141242758 T C -0.0006295 0.0027333 0.8178619 0.8178601 0.1238150 0.1525560 35523
1 740284 rs61770167 C T -0.0031464 0.0128285 0.8062540 0.8062532 0.0056331 0.0023962 35523
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0064787 0.0032967 0.0493981 0.0493906 0.0563406 0.0309934 35523
23 154923374 rs111332691 T A 0.0028470 0.0036644 0.4372139 0.4372099 0.0440700 0.0116556 35523
23 154925045 rs509981 C T 0.0016385 0.0017511 0.3494331 0.3494260 0.2431470 0.3634440 35523
23 154925895 rs538470 C T 0.0015223 0.0017906 0.3952428 0.3952358 0.2395030 0.3634440 35523
23 154927581 rs644138 G A -0.0001311 0.0016436 0.9364041 0.9364030 0.2999590 0.4635760 35523
23 154929412 rs557132 C T 0.0016059 0.0017516 0.3592634 0.3592545 0.2429820 0.3568210 35523
23 154929637 rs35185538 CT C 0.0035272 0.0018294 0.0538493 0.0538419 0.2273570 0.3011920 35523
23 154929952 rs4012982 CAA C 0.0013890 0.0018442 0.4513454 0.4513408 0.2374180 0.3165560 35523
23 154930230 rs781880 A G 0.0014444 0.0017513 0.4095293 0.4095210 0.2432870 0.3618540 35523
23 154930487 rs781879 T A 0.0050054 0.0058380 0.3912452 0.3912395 0.0201123 0.1263580 35523

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112859 ES:SE:LP:AF:SS:ID   0.000919392:0.00305115:0.11738:0.112859:35523:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.118061 ES:SE:LP:AF:SS:ID   -0.00077954:0.00288052:0.104201:0.118061:35523:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0994655    ES:SE:LP:AF:SS:ID   -0.00237988:0.00323733:0.335113:0.0994655:35523:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0164936    ES:SE:LP:AF:SS:ID   0.000468447:0.00758554:0.02193:0.0164936:35523:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00183311   ES:SE:LP:AF:SS:ID   0.00337597:0.0224233:0.055356:0.00183311:35523:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0575976    ES:SE:LP:AF:SS:ID   0.00118597:0.00399738:0.115371:0.0575976:35523:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.124627 ES:SE:LP:AF:SS:ID   -0.000701266:0.00273109:0.0983477:0.124627:35523:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.124024 ES:SE:LP:AF:SS:ID   -0.00131538:0.00291243:0.186067:0.124024:35523:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.123815 ES:SE:LP:AF:SS:ID   -0.000629467:0.00273327:0.08732:0.123815:35523:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00563308   ES:SE:LP:AF:SS:ID   -0.00314635:0.0128285:0.0935281:0.00563308:35523:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00202332   ES:SE:LP:AF:SS:ID   0.0162588:0.0226028:0.326109:0.00202332:35523:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.866683 ES:SE:LP:AF:SS:ID   0.00134601:0.00268608:0.210207:0.866683:35523:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00146191   ES:SE:LP:AF:SS:ID   0.0258054:0.0252876:0.512144:0.00146191:35523:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.125835 ES:SE:LP:AF:SS:ID   -0.00139601:0.00266449:0.221609:0.125835:35523:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145708 ES:SE:LP:AF:SS:ID   -0.000770432:0.00263537:0.113495:0.145708:35523:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.125914 ES:SE:LP:AF:SS:ID   -0.00140517:0.00266102:0.22369:0.125914:35523:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.867426 ES:SE:LP:AF:SS:ID   0.00113944:0.00259527:0.18004:0.867426:35523:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.872425 ES:SE:LP:AF:SS:ID   0.00140498:0.00263632:0.226151:0.872425:35523:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.132002 ES:SE:LP:AF:SS:ID   -0.00125123:0.00260139:0.200294:0.132002:35523:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036399 ES:SE:LP:AF:SS:ID   -0.000617391:0.00476354:0.0472666:0.036399:35523:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.866982 ES:SE:LP:AF:SS:ID   0.0010963:0.00259172:0.172439:0.866982:35523:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867042 ES:SE:LP:AF:SS:ID   0.00111348:0.0025922:0.175532:0.867042:35523:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.866976 ES:SE:LP:AF:SS:ID   0.00109506:0.00259159:0.172224:0.866976:35523:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00549619   ES:SE:LP:AF:SS:ID   -0.0220181:0.0128111:1.0671:0.00549619:35523:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00547014   ES:SE:LP:AF:SS:ID   -0.0221395:0.012837:1.07265:0.00547014:35523:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00588318   ES:SE:LP:AF:SS:ID   -0.0100952:0.0125982:0.373709:0.00588318:35523:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.867099 ES:SE:LP:AF:SS:ID   0.00116764:0.00258831:0.185815:0.867099:35523:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.129282 ES:SE:LP:AF:SS:ID   -0.00146874:0.00263848:0.238251:0.129282:35523:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.866579 ES:SE:LP:AF:SS:ID   0.00125537:0.00258128:0.20292:0.866579:35523:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866017 ES:SE:LP:AF:SS:ID   0.00110812:0.00257922:0.175571:0.866017:35523:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86677  ES:SE:LP:AF:SS:ID   0.00124946:0.0025838:0.201563:0.86677:35523:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.866778 ES:SE:LP:AF:SS:ID   0.00125336:0.00258397:0.202288:0.866778:35523:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86678  ES:SE:LP:AF:SS:ID   0.00125441:0.00258398:0.202485:0.86678:35523:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.867235 ES:SE:LP:AF:SS:ID   0.00119122:0.00259067:0.190001:0.867235:35523:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.101002 ES:SE:LP:AF:SS:ID   -0.00124558:0.00300893:0.16819:0.101002:35523:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00679063   ES:SE:LP:AF:SS:ID   -0.00438083:0.0114369:0.153854:0.00679063:35523:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87149  ES:SE:LP:AF:SS:ID   0.00156523:0.00262895:0.258381:0.87149:35523:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860376 ES:SE:LP:AF:SS:ID   0.000968036:0.00257589:0.150542:0.860376:35523:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.866182 ES:SE:LP:AF:SS:ID   0.00117944:0.00260636:0.186489:0.866182:35523:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.863161 ES:SE:LP:AF:SS:ID   0.0013622:0.00260519:0.221081:0.863161:35523:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.101481 ES:SE:LP:AF:SS:ID   -0.0018807:0.0031071:0.263611:0.101481:35523:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.868373 ES:SE:LP:AF:SS:ID   0.00183321:0.00263271:0.313155:0.868373:35523:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.868373 ES:SE:LP:AF:SS:ID   0.00183316:0.00263271:0.313145:0.868373:35523:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.86837  ES:SE:LP:AF:SS:ID   0.00183295:0.00263272:0.313099:0.86837:35523:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.868772 ES:SE:LP:AF:SS:ID   0.00177485:0.00263435:0.300609:0.868772:35523:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.128698 ES:SE:LP:AF:SS:ID   -0.001543:0.00263771:0.252926:0.128698:35523:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10745  ES:SE:LP:AF:SS:ID   -0.00102322:0.00287517:0.141504:0.10745:35523:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852136 ES:SE:LP:AF:SS:ID   0.00133075:0.00257588:0.217939:0.852136:35523:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00175076   ES:SE:LP:AF:SS:ID   0.00114886:0.0225222:0.0180374:0.00175076:35523:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837382 ES:SE:LP:AF:SS:ID   -0.000356723:0.00256316:0.0509449:0.837382:35523:rs376645387