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-680_4/ukb-d-680_4.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-680_4/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 17:17:09 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-680_4/ukb-d-680_4.vcf.gz ...
Read summary statistics for 13168687 SNPs.
Dropped 12117 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, 1283433 SNPs remain.
After merging with regression SNP LD, 1283433 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0065 (0.0013)
Lambda GC: 1.0495
Mean Chi^2: 1.0488
Intercept: 1.0034 (0.0064)
Ratio: 0.069 (0.1318)
Analysis finished at Mon Nov 25 17:19:26 2019
Total time elapsed: 2.0m:17.0s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9514,
    "inflation_factor": 1.0335,
    "mean_EFFECT": 0,
    "n": 356340,
    "n_snps": 13168687,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1236169,
    "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": 467199,
    "n_est": 357827.3816,
    "ratio_se_n": 1.0021,
    "mean_diff": 0.0001,
    "ratio_diff": 97.7319,
    "sd_y_est1": 0.1608,
    "sd_y_est2": 0.1611,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283433,
    "ldsc_nsnp_merge_regression_ld": 1283433,
    "ldsc_observed_scale_h2_beta": 0.0065,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0034,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.0495,
    "ldsc_mean_chisq": 1.0488,
    "ldsc_ratio": 0.0697
}

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 1.000000 3 94 0 13157228 0 NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 100 0 56217 0 NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 342 0 33075 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA 9.056704e+00 6.185657e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.000000 NA NA NA NA NA 7.898815e+07 5.592920e+07 3.02000e+02 3.286653e+07 7.007317e+07 1.148167e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA 1.470000e-05 2.006700e-03 -2.72529e-02 -5.706000e-04 1.700000e-06 5.754000e-04 2.843740e-02 ▁▁▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA 1.466400e-03 1.365300e-03 3.13400e-04 4.511000e-04 7.970000e-04 2.088800e-03 7.311700e-03 ▇▂▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA 4.950315e-01 2.903154e-01 0.00000e+00 2.427789e-01 4.929025e-01 7.467522e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA 4.950310e-01 2.903156e-01 0.00000e+00 2.427785e-01 4.929025e-01 7.467520e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.000000 NA NA NA NA NA 1.965145e-01 2.557575e-01 1.32230e-03 8.978300e-03 6.735050e-02 3.066840e-01 9.986780e-01 ▇▂▁▁▁
numeric AF_reference 467199 0.964522 NA NA NA NA NA 2.006707e-01 2.480476e-01 0.00000e+00 6.589500e-03 9.025560e-02 3.162940e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.000000 NA NA NA NA NA 3.563400e+05 0.000000e+00 3.56340e+05 3.563400e+05 3.563400e+05 3.563400e+05 3.563400e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0014066 0.0006675 0.0351051 0.0351041 0.1106480 0.1894970 356340
1 693731 rs12238997 A G -0.0012405 0.0006309 0.0492595 0.0492583 0.1157970 0.1417730 356340
1 707522 rs371890604 G C -0.0017026 0.0007092 0.0163614 0.0163612 0.0972849 0.1293930 356340
1 717587 rs144155419 G A -0.0004670 0.0016922 0.7825841 0.7825832 0.0156800 0.0045926 356340
1 723329 rs189787166 A T 0.0038940 0.0049730 0.4336107 0.4336098 0.0017455 0.0003994 356340
1 730087 rs148120343 T C -0.0005560 0.0008788 0.5269131 0.5269123 0.0564590 0.0127796 356340
1 731718 rs142557973 T C -0.0011035 0.0005983 0.0651058 0.0651042 0.1217310 0.1543530 356340
1 732032 rs61770163 A C -0.0013476 0.0006382 0.0347136 0.0347128 0.1211470 0.1555510 356340
1 734349 rs141242758 T C -0.0010939 0.0005986 0.0676285 0.0676261 0.1209580 0.1525560 356340
1 740284 rs61770167 C T -0.0006903 0.0027328 0.8005810 0.8005808 0.0058056 0.0023962 356340
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0005487 0.0006907 0.4270021 0.4270005 0.0562156 0.0309934 356340
23 154923374 rs111332691 T A -0.0008267 0.0007595 0.2764089 0.2764084 0.0448027 0.0116556 356340
23 154925045 rs509981 C T 0.0007468 0.0003656 0.0410610 0.0410602 0.2454610 0.3634440 356340
23 154925895 rs538470 C T 0.0006812 0.0003739 0.0685204 0.0685194 0.2417790 0.3634440 356340
23 154927581 rs644138 G A 0.0007895 0.0003437 0.0216342 0.0216337 0.3020610 0.4635760 356340
23 154929412 rs557132 C T 0.0007508 0.0003657 0.0400350 0.0400344 0.2453120 0.3568210 356340
23 154929637 rs35185538 CT C 0.0008673 0.0003816 0.0230431 0.0230421 0.2295890 0.3011920 356340
23 154929952 rs4012982 CAA C 0.0005963 0.0003846 0.1210060 0.1210055 0.2392680 0.3165560 356340
23 154930230 rs781880 A G 0.0007156 0.0003656 0.0503176 0.0503170 0.2457230 0.3618540 356340
23 154930487 rs781879 T A -0.0011340 0.0012548 0.3661373 0.3661358 0.0195351 0.1263580 356340

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110648 ES:SE:LP:AF:SS:ID   -0.00140656:0.000667516:1.45463:0.110648:356340:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115797 ES:SE:LP:AF:SS:ID   -0.00124054:0.000630885:1.30751:0.115797:356340:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972849    ES:SE:LP:AF:SS:ID   -0.00170261:0.000709197:1.78618:0.0972849:356340:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.01568  ES:SE:LP:AF:SS:ID   -0.000466978:0.00169223:0.106469:0.01568:356340:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00174548   ES:SE:LP:AF:SS:ID   0.00389399:0.00497298:0.3629:0.00174548:356340:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056459 ES:SE:LP:AF:SS:ID   -0.000556035:0.000878792:0.278261:0.056459:356340:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121731 ES:SE:LP:AF:SS:ID   -0.00110351:0.000598257:1.18638:0.121731:356340:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121147 ES:SE:LP:AF:SS:ID   -0.00134764:0.00063818:1.4595:0.121147:356340:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120958 ES:SE:LP:AF:SS:ID   -0.00109391:0.000598586:1.16987:0.120958:356340:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0058056    ES:SE:LP:AF:SS:ID   -0.000690298:0.00273282:0.0965947:0.0058056:356340:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187615   ES:SE:LP:AF:SS:ID   -0.00626656:0.00517363:0.646274:0.00187615:356340:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869751 ES:SE:LP:AF:SS:ID   0.00102875:0.000590132:1.08996:0.869751:356340:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00152269   ES:SE:LP:AF:SS:ID   -0.003934:0.00535593:0.33476:0.00152269:356340:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122921 ES:SE:LP:AF:SS:ID   -0.000870763:0.000584404:0.865743:0.122921:356340:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142704 ES:SE:LP:AF:SS:ID   -0.000890491:0.000577664:0.909435:0.142704:356340:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123036 ES:SE:LP:AF:SS:ID   -0.000878831:0.000583592:0.879117:0.123036:356340:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870892 ES:SE:LP:AF:SS:ID   0.000854879:0.000568687:0.876884:0.870892:356340:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875468 ES:SE:LP:AF:SS:ID   0.000833367:0.00057812:0.82553:0.875468:356340:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128631 ES:SE:LP:AF:SS:ID   -0.000898375:0.000570104:0.939034:0.128631:356340:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363599    ES:SE:LP:AF:SS:ID   -0.00148913:0.00103418:0.824219:0.0363599:356340:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870484 ES:SE:LP:AF:SS:ID   0.000871376:0.000568092:0.902868:0.870484:356340:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870586 ES:SE:LP:AF:SS:ID   0.000866168:0.000568341:0.89448:0.870586:356340:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870482 ES:SE:LP:AF:SS:ID   0.000866749:0.000568071:0.895967:0.870482:356340:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504061   ES:SE:LP:AF:SS:ID   0.00344116:0.00291717:0.623148:0.00504061:356340:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500754   ES:SE:LP:AF:SS:ID   0.00350642:0.00292499:0.637112:0.00500754:356340:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00555675   ES:SE:LP:AF:SS:ID   4.73886e-05:0.00283228:0.00583644:0.00555675:356340:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870565 ES:SE:LP:AF:SS:ID   0.000866584:0.00056707:0.898016:0.870565:356340:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125983 ES:SE:LP:AF:SS:ID   -0.000967406:0.000578635:1.02434:0.125983:356340:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870131 ES:SE:LP:AF:SS:ID   0.000903387:0.000565714:0.957468:0.870131:356340:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869417 ES:SE:LP:AF:SS:ID   0.000923039:0.000565191:0.98953:0.869417:356340:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870287 ES:SE:LP:AF:SS:ID   0.000874762:0.000566204:0.912371:0.870287:356340:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870293 ES:SE:LP:AF:SS:ID   0.000875156:0.000566245:0.912875:0.870293:356340:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870301 ES:SE:LP:AF:SS:ID   0.000873931:0.000566263:0.910975:0.870301:356340:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870742 ES:SE:LP:AF:SS:ID   0.000860365:0.000567696:0.887271:0.870742:356340:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988331    ES:SE:LP:AF:SS:ID   -0.00142116:0.000659757:1.50535:0.0988331:356340:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00645051   ES:SE:LP:AF:SS:ID   -0.000927587:0.002557:0.144613:0.00645051:356340:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87464  ES:SE:LP:AF:SS:ID   0.000853383:0.000576179:0.858303:0.87464:356340:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864041 ES:SE:LP:AF:SS:ID   0.00108651:0.000565019:1.26371:0.864041:356340:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869434 ES:SE:LP:AF:SS:ID   0.000856014:0.000570518:0.874496:0.869434:356340:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.866374 ES:SE:LP:AF:SS:ID   0.000667715:0.000570619:0.616296:0.866374:356340:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098777 ES:SE:LP:AF:SS:ID   -0.000815135:0.000683209:0.632957:0.098777:356340:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.000758184:0.000577134:0.723662:0.87156:356340:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.000758199:0.000577134:0.723683:0.87156:356340:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87156  ES:SE:LP:AF:SS:ID   0.000757434:0.000577145:0.722638:0.87156:356340:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871936 ES:SE:LP:AF:SS:ID   0.000707634:0.000577474:0.656735:0.871936:356340:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12556  ES:SE:LP:AF:SS:ID   -0.000894926:0.000577916:0.915449:0.12556:356340:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10543  ES:SE:LP:AF:SS:ID   -0.00130855:0.000629129:1.4256:0.10543:356340:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855374 ES:SE:LP:AF:SS:ID   0.00100846:0.000564785:1.12977:0.855374:356340:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00166613   ES:SE:LP:AF:SS:ID   0.00479722:0.00498364:0.473981:0.00166613:356340:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838431 ES:SE:LP:AF:SS:ID   0.000269024:0.000556534:0.201475:0.838431:356340:rs376645387