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-30690_raw/ukb-d-30690_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-30690_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 16:43:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30690_raw/ukb-d-30690_raw.vcf.gz ...
Read summary statistics for 13586044 SNPs.
Dropped 12711 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: 0.1203 (0.0168)
Lambda GC: 1.3393
Mean Chi^2: 1.8742
Intercept: 1.082 (0.0175)
Ratio: 0.0938 (0.02)
Analysis finished at Mon Nov 25 16:45:48 2019
Total time elapsed: 2.0m:42.52s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.214,
    "mean_EFFECT": 0,
    "n": 344278,
    "n_snps": 13586044,
    "n_clumped_hits": 182,
    "n_p_sig": 41953,
    "n_mono": 0,
    "n_ns": 1251780,
    "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": 569179,
    "n_est": 345601.4786,
    "ratio_se_n": 1.0019,
    "mean_diff": -2.0273e-06,
    "ratio_diff": 6.4228,
    "sd_y_est1": 1.1021,
    "sd_y_est2": 1.1042,
    "r2_sum1": 0.0947,
    "r2_sum2": 0.0779,
    "r2_sum3": 0.0776,
    "r2_sum4": 0.0776,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1203,
    "ldsc_observed_scale_h2_se": 0.0168,
    "ldsc_intercept_beta": 1.082,
    "ldsc_intercept_se": 0.0175,
    "ldsc_lambda_gc": 1.3393,
    "ldsc_mean_chisq": 1.8742,
    "ldsc_ratio": 0.0938
}

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 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 13573997 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 9.051225e+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 7.902580e+07 5.591525e+07 3.02000e+02 3.293107e+07 7.013957e+07 1.148605e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.810000e-05 1.623400e-02 -4.16660e-01 -4.622800e-03 1.290000e-05 4.655800e-03 3.124400e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.116080e-02 1.076590e-02 2.18360e-03 3.177700e-03 5.855600e-03 1.603900e-02 5.438200e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.672855e-01 2.987490e-01 0.00000e+00 2.011602e-01 4.573798e-01 7.259304e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.672850e-01 2.987492e-01 0.00000e+00 2.011605e-01 4.573804e-01 7.259285e-01 9.999998e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908092e-01 2.544043e-01 1.00000e-03 7.431300e-03 6.004000e-02 2.953200e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569179 0.9581056 NA NA NA NA NA 1.963388e-01 2.471026e-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 3.442780e+05 0.000000e+00 3.44278e+05 3.442780e+05 3.442780e+05 3.442780e+05 3.442780e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0052190 0.0046524 0.2619498 0.2619532 0.1105200 0.1894970 344278
1 693731 rs12238997 A G -0.0046395 0.0043941 0.2910402 0.2910378 0.1157900 0.1417730 344278
1 707522 rs371890604 G C -0.0060313 0.0049426 0.2223699 0.2223630 0.0972310 0.1293930 344278
1 717587 rs144155419 G A -0.0093062 0.0117970 0.4301996 0.4301929 0.0156640 0.0045926 344278
1 723329 rs189787166 A T -0.0054093 0.0347550 0.8763200 0.8763161 0.0017358 0.0003994 344278
1 730087 rs148120343 T C -0.0037545 0.0061236 0.5398001 0.5397972 0.0564280 0.0127796 344278
1 731718 rs142557973 T C -0.0054963 0.0041676 0.1872298 0.1872304 0.1216800 0.1543530 344278
1 732032 rs61770163 A C -0.0054821 0.0044471 0.2176702 0.2176743 0.1210900 0.1555510 344278
1 734349 rs141242758 T C -0.0052517 0.0041698 0.2078600 0.2078639 0.1209100 0.1525560 344278
1 740284 rs61770167 C T 0.0145060 0.0191330 0.4483498 0.4483513 0.0057521 0.0023962 344278
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0044747 0.0048154 0.3527597 0.3527607 0.056192 0.0309934 344278
23 154923374 rs111332691 T A 0.0006903 0.0052857 0.8961000 0.8960996 0.044877 0.0116556 344278
23 154925045 rs509981 C T 0.0038576 0.0025461 0.1297499 0.1297467 0.245690 0.3634440 344278
23 154925895 rs538470 C T 0.0039450 0.0026045 0.1298599 0.1298519 0.242020 0.3634440 344278
23 154927581 rs644138 G A 0.0021524 0.0023946 0.3687203 0.3687295 0.302270 0.4635760 344278
23 154929412 rs557132 C T 0.0038299 0.0025468 0.1326301 0.1326306 0.245550 0.3568210 344278
23 154929637 rs35185538 CT C 0.0027559 0.0026582 0.2998500 0.2998504 0.229800 0.3011920 344278
23 154929952 rs4012982 CAA C 0.0040951 0.0026785 0.1262999 0.1262947 0.239520 0.3165560 344278
23 154930230 rs781880 A G 0.0036348 0.0025464 0.1534599 0.1534569 0.245950 0.3618540 344278
23 154930487 rs781879 T A 0.0010962 0.0087285 0.9000601 0.9000576 0.019566 0.1263580 344278

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11052  ES:SE:LP:AF:SS:ID   -0.005219:0.0046524:0.581782:0.11052:344278:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11579  ES:SE:LP:AF:SS:ID   -0.0046395:0.0043941:0.536047:0.11579:344278:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097231 ES:SE:LP:AF:SS:ID   -0.0060313:0.0049426:0.652924:0.097231:344278:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015664 ES:SE:LP:AF:SS:ID   -0.0093062:0.011797:0.36633:0.015664:344278:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017358    ES:SE:LP:AF:SS:ID   -0.0054093:0.034755:0.0573373:0.0017358:344278:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056428 ES:SE:LP:AF:SS:ID   -0.0037545:0.0061236:0.267767:0.056428:344278:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12168  ES:SE:LP:AF:SS:ID   -0.0054963:0.0041676:0.727625:0.12168:344278:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12109  ES:SE:LP:AF:SS:ID   -0.0054821:0.0044471:0.662201:0.12109:344278:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12091  ES:SE:LP:AF:SS:ID   -0.0052517:0.0041698:0.682229:0.12091:344278:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057521    ES:SE:LP:AF:SS:ID   0.014506:0.019133:0.348383:0.0057521:344278:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018605    ES:SE:LP:AF:SS:ID   0.065029:0.036271:1.13668:0.0018605:344278:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86982  ES:SE:LP:AF:SS:ID   0.0034415:0.004111:0.395223:0.86982:344278:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015219    ES:SE:LP:AF:SS:ID   -0.02108:0.037334:0.242361:0.0015219:344278:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12287  ES:SE:LP:AF:SS:ID   -0.0043147:0.004071:0.538787:0.12287:344278:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14269  ES:SE:LP:AF:SS:ID   -0.004332:0.0040235:0.550321:0.14269:344278:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12298  ES:SE:LP:AF:SS:ID   -0.0040904:0.0040653:0.5026:0.12298:344278:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87097  ES:SE:LP:AF:SS:ID   0.0032336:0.0039621:0.382549:0.87097:344278:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87554  ES:SE:LP:AF:SS:ID   0.003225:0.0040273:0.373403:0.87554:344278:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12857  ES:SE:LP:AF:SS:ID   -0.0044074:0.0039718:0.573261:0.12857:344278:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036311 ES:SE:LP:AF:SS:ID   -0.0018541:0.0072116:0.0984872:0.036311:344278:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.0035855:0.003958:0.437707:0.87056:344278:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87067  ES:SE:LP:AF:SS:ID   0.0035712:0.0039598:0.43518:0.87067:344278:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.0036217:0.0039578:0.443517:0.87056:344278:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050518    ES:SE:LP:AF:SS:ID   -0.00071818:0.020294:0.0124365:0.0050518:344278:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050187    ES:SE:LP:AF:SS:ID   6.2952e-06:0.020348:0.000108587:0.0050187:344278:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055463    ES:SE:LP:AF:SS:ID   0.036888:0.019754:1.2087:0.0055463:344278:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87065  ES:SE:LP:AF:SS:ID   0.0032308:0.003951:0.383503:0.87065:344278:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12591  ES:SE:LP:AF:SS:ID   -0.004055:0.0040312:0.502421:0.12591:344278:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87022  ES:SE:LP:AF:SS:ID   0.0032696:0.0039416:0.390608:0.87022:344278:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   0.004037:0.003938:0.515273:0.8695:344278:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   0.0033354:0.0039449:0.400302:0.87037:344278:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   0.0033265:0.0039451:0.398886:0.87037:344278:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87038  ES:SE:LP:AF:SS:ID   0.0033504:0.0039453:0.402568:0.87038:344278:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87082  ES:SE:LP:AF:SS:ID   0.0032909:0.0039552:0.392127:0.87082:344278:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098774 ES:SE:LP:AF:SS:ID   -0.0044933:0.0045971:0.483637:0.098774:344278:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064334    ES:SE:LP:AF:SS:ID   0.024562:0.017845:0.772911:0.0064334:344278:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87471  ES:SE:LP:AF:SS:ID   0.0032524:0.004014:0.379042:0.87471:344278:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86412  ES:SE:LP:AF:SS:ID   0.0038136:0.003937:0.477921:0.86412:344278:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   0.0037487:0.0039746:0.461439:0.8695:344278:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86644  ES:SE:LP:AF:SS:ID   0.0034298:0.0039754:0.410866:0.86644:344278:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098735 ES:SE:LP:AF:SS:ID   -0.004925:0.0047588:0.521867:0.098735:344278:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87163  ES:SE:LP:AF:SS:ID   0.0032347:0.0040208:0.375594:0.87163:344278:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87163  ES:SE:LP:AF:SS:ID   0.0032352:0.0040208:0.375666:0.87163:344278:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.0032348:0.0040209:0.375594:0.87162:344278:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.872    ES:SE:LP:AF:SS:ID   0.0031778:0.0040232:0.366946:0.872:344278:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.1255   ES:SE:LP:AF:SS:ID   -0.0044273:0.004026:0.566278:0.1255:344278:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10538  ES:SE:LP:AF:SS:ID   -0.0040616:0.004384:0.450751:0.10538:344278:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85547  ES:SE:LP:AF:SS:ID   0.0029031:0.0039354:0.336582:0.85547:344278:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016546    ES:SE:LP:AF:SS:ID   0.0057036:0.034843:0.0604957:0.0016546:344278:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83826  ES:SE:LP:AF:SS:ID   0.0014831:0.0038749:0.153719:0.83826:344278:rs376645387