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-22608_0/ukb-d-22608_0.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-22608_0/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 16:37:30 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22608_0/ukb-d-22608_0.vcf.gz ...
Read summary statistics for 13566901 SNPs.
Dropped 12683 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0321 (0.0058)
Lambda GC: 1.0549
Mean Chi^2: 1.0629
Intercept: 1.0067 (0.0062)
Ratio: 0.1072 (0.0981)
Analysis finished at Mon Nov 25 16:39:51 2019
Total time elapsed: 2.0m:21.16s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0415,
    "mean_EFFECT": -0,
    "n": 90105,
    "n_snps": 13566901,
    "n_clumped_hits": 2,
    "n_p_sig": 10,
    "n_mono": 0,
    "n_ns": 1251233,
    "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": 563196,
    "n_est": 90429.9187,
    "ratio_se_n": 1.0018,
    "mean_diff": -0,
    "ratio_diff": 12.7466,
    "sd_y_est1": 0.4302,
    "sd_y_est2": 0.431,
    "r2_sum1": 0.0001,
    "r2_sum2": 0.0007,
    "r2_sum3": 0.0007,
    "r2_sum4": 0.0007,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0321,
    "ldsc_observed_scale_h2_se": 0.0058,
    "ldsc_intercept_beta": 1.0067,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0549,
    "ldsc_mean_chisq": 1.0629,
    "ldsc_ratio": 0.1065
}

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 13554882 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57050 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33332 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051286e+00 6.184940e+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 7.902476e+07 5.591704e+07 3.02000e+02 3.292734e+07 7.013401e+07 1.148629e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.600000e-05 1.185320e-02 -1.56801e-01 -3.173600e-03 2.460000e-05 3.205500e-03 1.342820e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.481400e-03 8.173700e-03 1.67160e-03 2.423200e-03 4.457300e-03 1.217940e-02 4.108060e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.933617e-01 2.905895e-01 0.00000e+00 2.403820e-01 4.912313e-01 7.451454e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.933599e-01 2.905906e-01 0.00000e+00 2.403789e-01 4.912295e-01 7.451438e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.910654e-01 2.544720e-01 1.00000e-03 7.499200e-03 6.029680e-02 2.957660e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 563196 0.9584875 NA NA NA NA NA 1.965221e-01 2.471439e-01 0.00000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 9.010500e+04 0.000000e+00 9.01050e+04 9.010500e+04 9.010500e+04 9.010500e+04 9.010500e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0009732 0.0035400 0.7833737 0.7833719 0.1113430 0.1894970 90105
1 693731 rs12238997 A G 0.0010546 0.0033522 0.7530746 0.7530740 0.1163310 0.1417730 90105
1 707522 rs371890604 G C 0.0026029 0.0037678 0.4896694 0.4896696 0.0977618 0.1293930 90105
1 717587 rs144155419 G A 0.0087540 0.0089782 0.3295490 0.3295467 0.0157787 0.0045926 90105
1 723329 rs189787166 A T 0.0277742 0.0262588 0.2901890 0.2901876 0.0017681 0.0003994 90105
1 730087 rs148120343 T C 0.0010402 0.0046505 0.8230050 0.8230055 0.0568517 0.0127796 90105
1 731718 rs142557973 T C 0.0012292 0.0031812 0.6992138 0.6992133 0.1222030 0.1543530 90105
1 732032 rs61770163 A C 0.0032343 0.0033918 0.3403134 0.3403115 0.1219220 0.1555510 90105
1 734349 rs141242758 T C 0.0012432 0.0031837 0.6961663 0.6961662 0.1214330 0.1525560 90105
1 740284 rs61770167 C T 0.0207633 0.0145840 0.1545351 0.1545322 0.0057643 0.0023962 90105
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0082440 0.0037208 0.0267159 0.0267133 0.0552866 0.0309934 90105
23 154923374 rs111332691 T A -0.0016859 0.0040453 0.6768571 0.6768564 0.0449254 0.0116556 90105
23 154925045 rs509981 C T 0.0027663 0.0019506 0.1561511 0.1561470 0.2445960 0.3634440 90105
23 154925895 rs538470 C T 0.0027500 0.0019942 0.1678951 0.1678898 0.2410980 0.3634440 90105
23 154927581 rs644138 G A 0.0044102 0.0018349 0.0162405 0.0162386 0.3002880 0.4635760 90105
23 154929412 rs557132 C T 0.0027654 0.0019512 0.1564041 0.1564003 0.2444530 0.3568210 90105
23 154929637 rs35185538 CT C 0.0025995 0.0020374 0.2020040 0.2020003 0.2288420 0.3011920 90105
23 154929952 rs4012982 CAA C 0.0024876 0.0020539 0.2258338 0.2258306 0.2383240 0.3165560 90105
23 154930230 rs781880 A G 0.0027552 0.0019506 0.1578080 0.1578052 0.2449110 0.3618540 90105
23 154930487 rs781879 T A -0.0103039 0.0066178 0.1194711 0.1194688 0.0196486 0.1263580 90105

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111343 ES:SE:LP:AF:SS:ID   -0.000973238:0.00353998:0.106031:0.111343:90105:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116331 ES:SE:LP:AF:SS:ID   0.00105458:0.00335225:0.123162:0.116331:90105:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0977618    ES:SE:LP:AF:SS:ID   0.00260294:0.00376782:0.310097:0.0977618:90105:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157787    ES:SE:LP:AF:SS:ID   0.00875398:0.00897819:0.48208:0.0157787:90105:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00176813   ES:SE:LP:AF:SS:ID   0.0277742:0.0262588:0.537319:0.00176813:90105:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0568517    ES:SE:LP:AF:SS:ID   0.00104022:0.00465046:0.0845975:0.0568517:90105:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122203 ES:SE:LP:AF:SS:ID   0.00122918:0.00318125:0.15539:0.122203:90105:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121922 ES:SE:LP:AF:SS:ID   0.00323426:0.00339181:0.468121:0.121922:90105:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121433 ES:SE:LP:AF:SS:ID   0.00124323:0.00318368:0.157287:0.121433:90105:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00576432   ES:SE:LP:AF:SS:ID   0.0207633:0.014584:0.810973:0.00576432:90105:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00181475   ES:SE:LP:AF:SS:ID   0.0121611:0.0279971:0.177818:0.00181475:90105:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869063 ES:SE:LP:AF:SS:ID   -0.0013474:0.0031318:0.175857:0.869063:90105:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015992    ES:SE:LP:AF:SS:ID   -0.00168071:0.0276823:0.0215515:0.0015992:90105:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123555 ES:SE:LP:AF:SS:ID   0.00219904:0.00310482:0.319864:0.123555:90105:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14307  ES:SE:LP:AF:SS:ID   0.00207033:0.00307349:0.300542:0.14307:90105:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123692 ES:SE:LP:AF:SS:ID   0.00234374:0.00310031:0.347106:0.123692:90105:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87006  ES:SE:LP:AF:SS:ID   -0.00158917:0.00302101:0.222674:0.87006:90105:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874709 ES:SE:LP:AF:SS:ID   -0.00222861:0.00307011:0.329848:0.874709:90105:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12937  ES:SE:LP:AF:SS:ID   0.00169654:0.00303039:0.239887:0.12937:90105:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0358637    ES:SE:LP:AF:SS:ID   0.0001707:0.00553166:0.0108253:0.0358637:90105:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869707 ES:SE:LP:AF:SS:ID   -0.00155574:0.00301849:0.217332:0.869707:90105:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869785 ES:SE:LP:AF:SS:ID   -0.00164628:0.00301983:0.232364:0.869785:90105:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869704 ES:SE:LP:AF:SS:ID   -0.00155813:0.00301837:0.217739:0.869704:90105:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00533145   ES:SE:LP:AF:SS:ID   0.00944455:0.015046:0.275566:0.00533145:90105:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00529672   ES:SE:LP:AF:SS:ID   0.00940078:0.0150833:0.273177:0.00529672:90105:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00566082   ES:SE:LP:AF:SS:ID   -0.00251268:0.0148532:0.0626501:0.00566082:90105:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869689 ES:SE:LP:AF:SS:ID   -0.00162957:0.00301219:0.230242:0.869689:90105:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126763 ES:SE:LP:AF:SS:ID   0.0016422:0.00307467:0.226748:0.126763:90105:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869214 ES:SE:LP:AF:SS:ID   -0.00149682:0.00300435:0.208778:0.869214:90105:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868604 ES:SE:LP:AF:SS:ID   -0.00177446:0.00300242:0.256087:0.868604:90105:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869367 ES:SE:LP:AF:SS:ID   -0.00162321:0.00300709:0.229634:0.869367:90105:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869373 ES:SE:LP:AF:SS:ID   -0.00162661:0.00300729:0.23019:0.869373:90105:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869375 ES:SE:LP:AF:SS:ID   -0.00161957:0.00300731:0.228999:0.869375:90105:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869858 ES:SE:LP:AF:SS:ID   -0.00171961:0.0030154:0.245276:0.869858:90105:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0990209    ES:SE:LP:AF:SS:ID   0.00170993:0.00350983:0.203335:0.0990209:90105:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00649969   ES:SE:LP:AF:SS:ID   -0.00139546:0.0135321:0.0372207:0.00649969:90105:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873849 ES:SE:LP:AF:SS:ID   -0.00207246:0.00306009:0.302556:0.873849:90105:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86323  ES:SE:LP:AF:SS:ID   -0.0017579:0.00300163:0.253279:0.86323:90105:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868645 ES:SE:LP:AF:SS:ID   -0.0016549:0.00303135:0.232757:0.868645:90105:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865535 ES:SE:LP:AF:SS:ID   -0.00137755:0.00303175:0.187381:0.865535:90105:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0994347    ES:SE:LP:AF:SS:ID   0.00221127:0.00362818:0.265829:0.0994347:90105:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870818 ES:SE:LP:AF:SS:ID   -0.0014228:0.00306648:0.192018:0.870818:90105:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870818 ES:SE:LP:AF:SS:ID   -0.00142272:0.00306648:0.192005:0.870818:90105:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870815 ES:SE:LP:AF:SS:ID   -0.00142238:0.00306649:0.191951:0.870815:90105:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871183 ES:SE:LP:AF:SS:ID   -0.00135182:0.00306794:0.180796:0.871183:90105:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126356 ES:SE:LP:AF:SS:ID   0.00190254:0.00307129:0.271147:0.126356:90105:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10589  ES:SE:LP:AF:SS:ID   -0.000150703:0.00333897:0.015923:0.10589:90105:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854591 ES:SE:LP:AF:SS:ID   -0.00150262:0.00300086:0.210023:0.854591:90105:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00167824   ES:SE:LP:AF:SS:ID   0.0307451:0.0263517:0.613813:0.00167824:90105:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839278 ES:SE:LP:AF:SS:ID   0.00258205:0.00296441:0.415954:0.839278:90105:rs376645387