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-30890_raw/ukb-d-30890_raw.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-30890_raw/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 16:43:25 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30890_raw/ukb-d-30890_raw.vcf.gz ...
Read summary statistics for 13585762 SNPs.
Dropped 12709 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: 0.0996 (0.0225)
Lambda GC: 1.349
Mean Chi^2: 1.6922
Intercept: 1.0423 (0.0114)
Ratio: 0.0611 (0.0164)
Analysis finished at Mon Nov 25 16:45:27 2019
Total time elapsed: 2.0m:1.72s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.2248,
    "mean_EFFECT": -0.0009,
    "n": 329247,
    "n_snps": 13585762,
    "n_clumped_hits": 64,
    "n_p_sig": 11540,
    "n_mono": 0,
    "n_ns": 1251771,
    "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": 569068,
    "n_est": 330549.2523,
    "ratio_se_n": 1.002,
    "mean_diff": 0.0008,
    "ratio_diff": 876.0456,
    "sd_y_est1": 20.9222,
    "sd_y_est2": 20.9636,
    "r2_sum1": 12.5397,
    "r2_sum2": 0.0286,
    "r2_sum3": 0.0285,
    "r2_sum4": 0.0286,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0996,
    "ldsc_observed_scale_h2_se": 0.0225,
    "ldsc_intercept_beta": 1.0423,
    "ldsc_intercept_se": 0.0114,
    "ldsc_lambda_gc": 1.349,
    "ldsc_mean_chisq": 1.6922,
    "ldsc_ratio": 0.0611
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n FALSE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio FALSE
ldsc_intercept_beta FALSE
n_clumped_hits FALSE
r2_sum1 TRUE
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 13573717 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57081 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051247e+00 6.184965e+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 7.902599e+07 5.591538e+07 3.02000e+02 3.293141e+07 7.013940e+07 1.148610e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -8.680000e-04 3.122079e-01 -9.84070e+00 -9.136070e-02 -6.756000e-04 8.927000e-02 8.120300e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.166424e-01 2.089805e-01 4.22910e-02 6.168500e-02 1.136600e-01 3.113000e-01 1.053800e+00 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.668577e-01 2.980499e-01 0.00000e+00 2.006800e-01 4.553800e-01 7.250701e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.668572e-01 2.980502e-01 0.00000e+00 2.006795e-01 4.553785e-01 7.250687e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908129e-01 2.544054e-01 1.00000e-03 7.433300e-03 6.004200e-02 2.953200e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569068 0.9581129 NA NA NA NA NA 1.963414e-01 2.471033e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.292470e+05 0.000000e+00 3.29247e+05 3.292470e+05 3.292470e+05 3.292470e+05 3.292470e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.055736 0.090356 0.5373398 0.5373344 0.1104400 0.1894970 329247
1 693731 rs12238997 A G 0.051219 0.085309 0.5482404 0.5482438 0.1157500 0.1417730 329247
1 707522 rs371890604 G C 0.061253 0.095969 0.5233100 0.5233056 0.0971850 0.1293930 329247
1 717587 rs144155419 G A 0.467470 0.229120 0.0413285 0.0413220 0.0156580 0.0045926 329247
1 723329 rs189787166 A T -0.831320 0.673210 0.2168797 0.2168827 0.0017415 0.0003994 329247
1 730087 rs148120343 T C 0.038189 0.118970 0.7482195 0.7482127 0.0563460 0.0127796 329247
1 731718 rs142557973 T C 0.057657 0.080918 0.4761305 0.4761328 0.1216300 0.1543530 329247
1 732032 rs61770163 A C 0.059382 0.086345 0.4916205 0.4916232 0.1210400 0.1555510 329247
1 734349 rs141242758 T C 0.063772 0.080963 0.4308896 0.4308907 0.1208500 0.1525560 329247
1 740284 rs61770167 C T -0.523650 0.370910 0.1580102 0.1580094 0.0057707 0.0023962 329247
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.058106 0.093344 0.5336199 0.5336177 0.056102 0.0309934 329247
23 154923374 rs111332691 T A 0.040365 0.102370 0.6933699 0.6933559 0.044857 0.0116556 329247
23 154925045 rs509981 C T 0.085079 0.049315 0.0844890 0.0844887 0.245590 0.3634440 329247
23 154925895 rs538470 C T 0.093793 0.050443 0.0629724 0.0629725 0.241930 0.3634440 329247
23 154927581 rs644138 G A 0.088845 0.046379 0.0554141 0.0554122 0.302080 0.4635760 329247
23 154929412 rs557132 C T 0.082969 0.049329 0.0925806 0.0925782 0.245450 0.3568210 329247
23 154929637 rs35185538 CT C 0.128520 0.051485 0.0125531 0.0125510 0.229780 0.3011920 329247
23 154929952 rs4012982 CAA C 0.082680 0.051878 0.1110000 0.1109945 0.239460 0.3165560 329247
23 154930230 rs781880 A G 0.085267 0.049321 0.0838436 0.0838418 0.245860 0.3618540 329247
23 154930487 rs781879 T A 0.092507 0.169270 0.5847201 0.5847185 0.019536 0.1263580 329247

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11044  ES:SE:LP:AF:SS:ID   0.055736:0.090356:0.269751:0.11044:329247:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11575  ES:SE:LP:AF:SS:ID   0.051219:0.085309:0.261029:0.11575:329247:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097185 ES:SE:LP:AF:SS:ID   0.061253:0.095969:0.281241:0.097185:329247:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015658 ES:SE:LP:AF:SS:ID   0.46747:0.22912:1.38375:0.015658:329247:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017415    ES:SE:LP:AF:SS:ID   -0.83132:0.67321:0.663781:0.0017415:329247:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056346 ES:SE:LP:AF:SS:ID   0.038189:0.11897:0.125971:0.056346:329247:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12163  ES:SE:LP:AF:SS:ID   0.057657:0.080918:0.322274:0.12163:329247:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12104  ES:SE:LP:AF:SS:ID   0.059382:0.086345:0.30837:0.12104:329247:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12085  ES:SE:LP:AF:SS:ID   0.063772:0.080963:0.365634:0.12085:329247:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057707    ES:SE:LP:AF:SS:ID   -0.52365:0.37091:0.801315:0.0057707:329247:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018587    ES:SE:LP:AF:SS:ID   -0.053866:0.70432:0.0273159:0.0018587:329247:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86989  ES:SE:LP:AF:SS:ID   -0.067791:0.079812:0.402667:0.86989:329247:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015138    ES:SE:LP:AF:SS:ID   0.047015:0.72669:0.0230039:0.0015138:329247:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12281  ES:SE:LP:AF:SS:ID   0.033913:0.079042:0.175302:0.12281:329247:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14261  ES:SE:LP:AF:SS:ID   0.051549:0.078108:0.293052:0.14261:329247:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12292  ES:SE:LP:AF:SS:ID   0.033016:0.078932:0.17022:0.12292:329247:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87103  ES:SE:LP:AF:SS:ID   -0.046971:0.076923:0.26645:0.87103:329247:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87559  ES:SE:LP:AF:SS:ID   -0.029075:0.078191:0.148736:0.87559:329247:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12851  ES:SE:LP:AF:SS:ID   0.047639:0.077111:0.27026:0.12851:329247:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036306 ES:SE:LP:AF:SS:ID   0.18496:0.14001:0.729414:0.036306:329247:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87062  ES:SE:LP:AF:SS:ID   -0.047085:0.076843:0.267574:0.87062:329247:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87072  ES:SE:LP:AF:SS:ID   -0.047976:0.076879:0.273599:0.87072:329247:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87062  ES:SE:LP:AF:SS:ID   -0.047332:0.07684:0.26929:0.87062:329247:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005051 ES:SE:LP:AF:SS:ID   0.14195:0.39399:0.143489:0.005051:329247:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050177    ES:SE:LP:AF:SS:ID   0.14047:0.39505:0.141367:0.0050177:329247:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055379    ES:SE:LP:AF:SS:ID   -0.07466:0.38371:0.0727683:0.0055379:329247:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.8707   ES:SE:LP:AF:SS:ID   -0.045271:0.076707:0.255652:0.8707:329247:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12585  ES:SE:LP:AF:SS:ID   0.043586:0.078265:0.23838:0.12585:329247:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87027  ES:SE:LP:AF:SS:ID   -0.046391:0.076525:0.264106:0.87027:329247:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86955  ES:SE:LP:AF:SS:ID   -0.046652:0.076452:0.266225:0.86955:329247:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87042  ES:SE:LP:AF:SS:ID   -0.04766:0.076588:0.272662:0.87042:329247:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87042  ES:SE:LP:AF:SS:ID   -0.047643:0.076593:0.272516:0.87042:329247:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87043  ES:SE:LP:AF:SS:ID   -0.048083:0.076596:0.275585:0.87043:329247:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87088  ES:SE:LP:AF:SS:ID   -0.047645:0.07679:0.271679:0.87088:329247:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098742 ES:SE:LP:AF:SS:ID   -0.0044948:0.089251:0.0178057:0.098742:329247:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064205    ES:SE:LP:AF:SS:ID   -0.28039:0.34682:0.377962:0.0064205:329247:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87477  ES:SE:LP:AF:SS:ID   -0.042371:0.077932:0.231614:0.87477:329247:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86419  ES:SE:LP:AF:SS:ID   -0.053874:0.076437:0.317918:0.86419:329247:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86956  ES:SE:LP:AF:SS:ID   -0.068782:0.077168:0.428582:0.86956:329247:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86647  ES:SE:LP:AF:SS:ID   -0.03678:0.077178:0.19813:0.86647:329247:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098673 ES:SE:LP:AF:SS:ID   0.0011877:0.092392:0.00447888:0.098673:329247:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87167  ES:SE:LP:AF:SS:ID   -0.036853:0.078065:0.195949:0.87167:329247:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87167  ES:SE:LP:AF:SS:ID   -0.036862:0.078065:0.196004:0.87167:329247:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87167  ES:SE:LP:AF:SS:ID   -0.036837:0.078067:0.195847:0.87167:329247:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87205  ES:SE:LP:AF:SS:ID   -0.041534:0.07811:0.225549:0.87205:329247:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12545  ES:SE:LP:AF:SS:ID   0.053222:0.078164:0.30458:0.12545:329247:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10533  ES:SE:LP:AF:SS:ID   -0.021319:0.085118:0.0957011:0.10533:329247:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85555  ES:SE:LP:AF:SS:ID   -0.05452:0.076401:0.322868:0.85555:329247:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00166  ES:SE:LP:AF:SS:ID   -0.81313:0.67513:0.641247:0.00166:329247:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83831  ES:SE:LP:AF:SS:ID   -0.042064:0.075228:0.239532:0.83831:329247:rs376645387