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-30710_irnt/ukb-d-30710_irnt.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-30710_irnt/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 15:00:30 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30710_irnt/ukb-d-30710_irnt.vcf.gz ...
Read summary statistics for 13586003 SNPs.
Dropped 12710 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: 0.1878 (0.0276)
Lambda GC: 1.646
Mean Chi^2: 2.3633
Intercept: 1.1065 (0.0163)
Ratio: 0.0782 (0.0119)
Analysis finished at Mon Nov 25 15:02:48 2019
Total time elapsed: 2.0m:18.09s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3907,
    "mean_EFFECT": 0.0001,
    "n": 343524,
    "n_snps": 13586003,
    "n_clumped_hits": 214,
    "n_p_sig": 42985,
    "n_mono": 0,
    "n_ns": 1251783,
    "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": 569171,
    "n_est": 344842.39,
    "ratio_se_n": 1.0019,
    "mean_diff": 1.0149e-06,
    "ratio_diff": 1.522,
    "sd_y_est1": 0.9937,
    "sd_y_est2": 0.9956,
    "r2_sum1": 0.0693,
    "r2_sum2": 0.0701,
    "r2_sum3": 0.0699,
    "r2_sum4": 0.0699,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1878,
    "ldsc_observed_scale_h2_se": 0.0276,
    "ldsc_intercept_beta": 1.1065,
    "ldsc_intercept_se": 0.0163,
    "ldsc_lambda_gc": 1.646,
    "ldsc_mean_chisq": 2.3633,
    "ldsc_ratio": 0.0781
}

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 13573957 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57080 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 9.051260e+00 6.184973e+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 7.902562e+07 5.591505e+07 3.02000e+02 3.293113e+07 7.013954e+07 1.148598e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 7.850000e-05 1.493310e-02 -7.47670e-01 -4.501900e-03 3.520000e-05 4.655400e-03 3.883500e-01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.007370e-02 9.717200e-03 1.97100e-03 2.868100e-03 5.285300e-03 1.447600e-02 4.905200e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.457984e-01 3.038831e-01 0.00000e+00 1.690098e-01 4.263802e-01 7.093197e-01 1.000000e+00 ▇▆▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.457979e-01 3.038834e-01 0.00000e+00 1.690112e-01 4.263808e-01 7.093190e-01 1.000000e+00 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908097e-01 2.544045e-01 1.00000e-03 7.431400e-03 6.004100e-02 2.953200e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569171 0.9581061 NA NA NA NA NA 1.963392e-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 3.435240e+05 0.000000e+00 3.43524e+05 3.435240e+05 3.435240e+05 3.435240e+05 3.435240e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0055908 0.0041988 0.1830202 0.1830169 0.1105200 0.1894970 343524
1 693731 rs12238997 A G -0.0039610 0.0039657 0.3178901 0.3178844 0.1158100 0.1417730 343524
1 707522 rs371890604 G C -0.0034973 0.0044609 0.4330400 0.4330461 0.0972460 0.1293930 343524
1 717587 rs144155419 G A -0.0071773 0.0106450 0.5001601 0.5001578 0.0156700 0.0045926 343524
1 723329 rs189787166 A T -0.0848400 0.0313200 0.0067523 0.0067525 0.0017408 0.0003994 343524
1 730087 rs148120343 T C -0.0129240 0.0055273 0.0193718 0.0193762 0.0564200 0.0127796 343524
1 731718 rs142557973 T C -0.0047560 0.0037613 0.2060701 0.2060662 0.1217000 0.1543530 343524
1 732032 rs61770163 A C -0.0032733 0.0040137 0.4147697 0.4147680 0.1211100 0.1555510 343524
1 734349 rs141242758 T C -0.0047290 0.0037633 0.2088998 0.2088949 0.1209300 0.1525560 343524
1 740284 rs61770167 C T 0.0338250 0.0172530 0.0499321 0.0499340 0.0057617 0.0023962 343524
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0038328 0.0043471 0.3779401 0.3779438 0.056186 0.0309934 343524
23 154923374 rs111332691 T A 0.0041154 0.0047708 0.3883399 0.3883450 0.044872 0.0116556 343524
23 154925045 rs509981 C T -0.0012119 0.0022986 0.5980300 0.5980311 0.245620 0.3634440 343524
23 154925895 rs538470 C T -0.0007134 0.0023513 0.7615808 0.7615735 0.241950 0.3634440 343524
23 154927581 rs644138 G A -0.0000230 0.0021617 0.9915000 0.9915042 0.302190 0.4635760 343524
23 154929412 rs557132 C T -0.0011705 0.0022992 0.6106804 0.6106891 0.245480 0.3568210 343524
23 154929637 rs35185538 CT C -0.0012468 0.0023998 0.6033801 0.6033819 0.229730 0.3011920 343524
23 154929952 rs4012982 CAA C -0.0017501 0.0024181 0.4692302 0.4692192 0.239450 0.3165560 343524
23 154930230 rs781880 A G -0.0008606 0.0022989 0.7081594 0.7081579 0.245870 0.3618540 343524
23 154930487 rs781879 T A 0.0047808 0.0078813 0.5441204 0.5441161 0.019560 0.1263580 343524

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11052  ES:SE:LP:AF:SS:ID   -0.0055908:0.0041988:0.737501:0.11052:343524:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11581  ES:SE:LP:AF:SS:ID   -0.003961:0.0039657:0.497723:0.11581:343524:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097246 ES:SE:LP:AF:SS:ID   -0.0034973:0.0044609:0.363472:0.097246:343524:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.01567  ES:SE:LP:AF:SS:ID   -0.0071773:0.010645:0.300891:0.01567:343524:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017408    ES:SE:LP:AF:SS:ID   -0.08484:0.03132:2.17055:0.0017408:343524:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.05642  ES:SE:LP:AF:SS:ID   -0.012924:0.0055273:1.71283:0.05642:343524:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.1217   ES:SE:LP:AF:SS:ID   -0.004756:0.0037613:0.685985:0.1217:343524:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12111  ES:SE:LP:AF:SS:ID   -0.0032733:0.0040137:0.382193:0.12111:343524:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12093  ES:SE:LP:AF:SS:ID   -0.004729:0.0037633:0.680062:0.12093:343524:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057617    ES:SE:LP:AF:SS:ID   0.033825:0.017253:1.30162:0.0057617:343524:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018616    ES:SE:LP:AF:SS:ID   0.013491:0.032723:0.167402:0.0018616:343524:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.8698   ES:SE:LP:AF:SS:ID   0.0045832:0.0037104:0.664061:0.8698:343524:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015218    ES:SE:LP:AF:SS:ID   -0.010312:0.033691:0.119449:0.0015218:343524:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12288  ES:SE:LP:AF:SS:ID   -0.0038617:0.0036744:0.532718:0.12288:343524:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.1427   ES:SE:LP:AF:SS:ID   -0.0035301:0.0036314:0.480172:0.1427:343524:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12299  ES:SE:LP:AF:SS:ID   -0.0038835:0.0036693:0.537782:0.12299:343524:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87097  ES:SE:LP:AF:SS:ID   0.0041609:0.0035761:0.611508:0.87097:343524:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87553  ES:SE:LP:AF:SS:ID   0.0031103:0.003635:0.406492:0.87553:343524:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12857  ES:SE:LP:AF:SS:ID   -0.0047708:0.003585:0.736909:0.12857:343524:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036306 ES:SE:LP:AF:SS:ID   -0.0016453:0.0065099:0.0966549:0.036306:343524:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.0044811:0.0035725:0.67836:0.87056:343524:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   0.0044576:0.0035741:0.672989:0.87066:343524:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87056  ES:SE:LP:AF:SS:ID   0.0044645:0.0035723:0.674916:0.87056:343524:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050488    ES:SE:LP:AF:SS:ID   -0.006048:0.018323:0.129983:0.0050488:343524:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050158    ES:SE:LP:AF:SS:ID   -0.0066688:0.018371:0.144717:0.0050158:343524:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055461    ES:SE:LP:AF:SS:ID   0.014132:0.01783:0.368556:0.0055461:343524:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   0.0041523:0.0035661:0.61213:0.87064:343524:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12592  ES:SE:LP:AF:SS:ID   -0.0038072:0.0036385:0.529619:0.12592:343524:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87021  ES:SE:LP:AF:SS:ID   0.0039744:0.0035576:0.578511:0.87021:343524:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86949  ES:SE:LP:AF:SS:ID   0.0042808:0.0035544:0.641209:0.86949:343524:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   0.0040977:0.0035606:0.602408:0.87036:343524:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   0.0040946:0.0035609:0.60173:0.87037:343524:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87038  ES:SE:LP:AF:SS:ID   0.0041061:0.003561:0.604027:0.87038:343524:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87082  ES:SE:LP:AF:SS:ID   0.0042903:0.00357:0.639312:0.87082:343524:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098777 ES:SE:LP:AF:SS:ID   -0.0043592:0.0041493:0.532481:0.098777:343524:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064311    ES:SE:LP:AF:SS:ID   0.012239:0.01611:0.349265:0.0064311:343524:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87471  ES:SE:LP:AF:SS:ID   0.0038892:0.003623:0.548137:0.87471:343524:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86411  ES:SE:LP:AF:SS:ID   0.0050496:0.0035535:0.808773:0.86411:343524:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.8695   ES:SE:LP:AF:SS:ID   0.004157:0.0035874:0.608095:0.8695:343524:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86644  ES:SE:LP:AF:SS:ID   0.0040152:0.0035881:0.57983:0.86644:343524:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098735 ES:SE:LP:AF:SS:ID   -0.0034821:0.0042953:0.379292:0.098735:343524:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.0036707:0.0036292:0.506124:0.87162:343524:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.0036706:0.0036292:0.506096:0.87162:343524:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87162  ES:SE:LP:AF:SS:ID   0.003677:0.0036292:0.507254:0.87162:343524:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87199  ES:SE:LP:AF:SS:ID   0.0036887:0.0036313:0.509045:0.87199:343524:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12551  ES:SE:LP:AF:SS:ID   -0.0042913:0.0036338:0.624117:0.12551:343524:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10539  ES:SE:LP:AF:SS:ID   -0.0048462:0.0039568:0.656296:0.10539:343524:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85546  ES:SE:LP:AF:SS:ID   0.0033923:0.0035521:0.469071:0.85546:343524:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016595    ES:SE:LP:AF:SS:ID   -0.091365:0.031398:2.44174:0.0016595:343524:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83824  ES:SE:LP:AF:SS:ID   -0.010952:0.0034972:2.75983:0.83824:343524:rs376645387