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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    "FORMAT.1": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
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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-20536_3/ukb-d-20536_3.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-20536_3/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 16:31:24 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20536_3/ukb-d-20536_3.vcf.gz ...
Read summary statistics for 11452359 SNPs.
Dropped 9696 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, 1282562 SNPs remain.
After merging with regression SNP LD, 1282562 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0123 (0.0079)
Lambda GC: 1.0102
Mean Chi^2: 1.0126
Intercept: 0.9988 (0.006)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 16:33:08 2019
Total time elapsed: 1.0m:43.76s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9474,
    "inflation_factor": 1.0091,
    "mean_EFFECT": 0,
    "n": 56571,
    "n_snps": 11452359,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1159654,
    "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": 240944,
    "n_est": 56614.6015,
    "ratio_se_n": 1.0004,
    "mean_diff": 0,
    "ratio_diff": 21.913,
    "sd_y_est1": 0.244,
    "sd_y_est2": 0.2441,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1282562,
    "ldsc_nsnp_merge_regression_ld": 1282562,
    "ldsc_observed_scale_h2_beta": 0.0123,
    "ldsc_observed_scale_h2_se": 0.0079,
    "ldsc_intercept_beta": 0.9988,
    "ldsc_intercept_se": 0.006,
    "ldsc_lambda_gc": 1.0102,
    "ldsc_mean_chisq": 1.0126,
    "ldsc_ratio": -0.0952
}
 

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 11443264 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 52158 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 31686 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.073226e+00 6.183350e+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 7.884909e+07 5.600050e+07 3.02000e+02 3.263587e+07 6.985566e+07 1.147360e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.040000e-05 4.966800e-03 -5.06242e-02 -1.851400e-03 -1.290000e-05 1.830500e-03 6.598290e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 3.932700e-03 3.033000e-03 1.23740e-03 1.647000e-03 2.495700e-03 5.338200e-03 1.776650e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.984632e-01 2.885720e-01 0.00000e+00 2.481561e-01 4.980627e-01 7.481109e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.984604e-01 2.885737e-01 0.00000e+00 2.481509e-01 4.980601e-01 7.481101e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.243999e-01 2.608323e-01 3.50240e-03 1.975620e-02 1.062600e-01 3.585180e-01 9.964970e-01 ▇▂▁▁▁
numeric AF_reference 240944 0.9789612 NA NA NA NA NA 2.250255e-01 2.520662e-01 0.00000e+00 1.717250e-02 1.246010e-01 3.582270e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.657100e+04 0.000000e+00 5.65710e+04 5.657100e+04 5.657100e+04 5.657100e+04 5.657100e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0035916 0.0025252 0.1549519 0.1549471 0.1120070 0.1894970 56571
1 693731 rs12238997 A G 0.0023933 0.0023887 0.3163647 0.3163612 0.1168710 0.1417730 56571
1 707522 rs371890604 G C 0.0041769 0.0026823 0.1194271 0.1194223 0.0983231 0.1293930 56571
1 717587 rs144155419 G A 0.0038480 0.0063988 0.5475994 0.5475978 0.0158084 0.0045926 56571
1 730087 rs148120343 T C -0.0002745 0.0033264 0.9342231 0.9342225 0.0569925 0.0127796 56571
1 731718 rs142557973 T C 0.0028953 0.0022664 0.2014332 0.2014281 0.1228370 0.1543530 56571
1 732032 rs61770163 A C 0.0037963 0.0024145 0.1158980 0.1158917 0.1222970 0.1555510 56571
1 734349 rs141242758 T C 0.0029628 0.0022674 0.1913128 0.1913069 0.1221100 0.1525560 56571
1 740284 rs61770167 C T 0.0116375 0.0101515 0.2516431 0.2516370 0.0060746 0.0023962 56571
1 749963 rs529266287 T TAA -0.0034610 0.0022351 0.1215061 0.1215010 0.8690340 0.7641770 56571
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0019243 0.0027473 0.4836576 0.4836562 0.0559256 0.0309934 56571
23 154923374 rs111332691 T A 0.0000910 0.0030385 0.9761029 0.9761030 0.0437061 0.0116556 56571
23 154925045 rs509981 C T -0.0000089 0.0014440 0.9951010 0.9951011 0.2456330 0.3634440 56571
23 154925895 rs538470 C T 0.0003028 0.0014766 0.8374980 0.8374975 0.2420240 0.3634440 56571
23 154927581 rs644138 G A -0.0005354 0.0013581 0.6934003 0.6933996 0.3019940 0.4635760 56571
23 154929412 rs557132 C T -0.0000174 0.0014444 0.9904060 0.9904056 0.2455120 0.3568210 56571
23 154929637 rs35185538 CT C -0.0006104 0.0015097 0.6859635 0.6859623 0.2288990 0.3011920 56571
23 154929952 rs4012982 CAA C 0.0002318 0.0015223 0.8789770 0.8789764 0.2391570 0.3165560 56571
23 154930230 rs781880 A G 0.0000254 0.0014441 0.9859470 0.9859467 0.2458300 0.3618540 56571
23 154930487 rs781879 T A -0.0005864 0.0049280 0.9052889 0.9052890 0.0194161 0.1263580 56571

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112007 ES:SE:LP:AF:SS:ID   0.00359158:0.00252524:0.809803:0.112007:56571:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116871 ES:SE:LP:AF:SS:ID   0.00239335:0.00238866:0.499812:0.116871:56571:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0983231    ES:SE:LP:AF:SS:ID   0.00417687:0.00268229:0.922897:0.0983231:56571:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0158084    ES:SE:LP:AF:SS:ID   0.003848:0.00639879:0.261537:0.0158084:56571:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0569925    ES:SE:LP:AF:SS:ID   -0.00027454:0.00332641:0.0295494:0.0569925:56571:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122837 ES:SE:LP:AF:SS:ID   0.00289526:0.00226636:0.695869:0.122837:56571:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122297 ES:SE:LP:AF:SS:ID   0.00379627:0.00241454:0.935924:0.122297:56571:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12211  ES:SE:LP:AF:SS:ID   0.00296285:0.00226739:0.718256:0.12211:56571:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00607462   ES:SE:LP:AF:SS:ID   0.0116375:0.0101515:0.599215:0.00607462:56571:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.869034 ES:SE:LP:AF:SS:ID   -0.00346103:0.00223508:0.915402:0.869034:56571:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.123945 ES:SE:LP:AF:SS:ID   0.00352196:0.00221331:0.952507:0.123945:56571:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143307 ES:SE:LP:AF:SS:ID   0.00194352:0.00219135:0.425816:0.143307:56571:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12403  ES:SE:LP:AF:SS:ID   0.00348084:0.00221047:0.938058:0.12403:56571:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869798 ES:SE:LP:AF:SS:ID   -0.0033201:0.00215543:0.908393:0.869798:56571:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874432 ES:SE:LP:AF:SS:ID   -0.00338876:0.0021899:0.914495:0.874432:56571:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129654 ES:SE:LP:AF:SS:ID   0.00354616:0.00216062:0.996772:0.129654:56571:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0366265    ES:SE:LP:AF:SS:ID   -0.00258532:0.00392236:0.292584:0.0366265:56571:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.8694   ES:SE:LP:AF:SS:ID   -0.00337411:0.00215303:0.931491:0.8694:56571:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86946  ES:SE:LP:AF:SS:ID   -0.00339677:0.00215349:0.940342:0.86946:56571:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869403 ES:SE:LP:AF:SS:ID   -0.0033826:0.00215296:0.934958:0.869403:56571:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00495789   ES:SE:LP:AF:SS:ID   0.0178551:0.0112216:0.952394:0.00495789:56571:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00492638   ES:SE:LP:AF:SS:ID   0.0180282:0.011246:0.962876:0.00492638:56571:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00576142   ES:SE:LP:AF:SS:ID   0.0112448:0.010597:0.539654:0.00576142:56571:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869451 ES:SE:LP:AF:SS:ID   -0.00331334:0.00214932:0.909453:0.869451:56571:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127054 ES:SE:LP:AF:SS:ID   0.00341421:0.00219246:0.922937:0.127054:56571:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868952 ES:SE:LP:AF:SS:ID   -0.00314208:0.00214356:0.845567:0.868952:56571:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868377 ES:SE:LP:AF:SS:ID   -0.00343462:0.00214228:0.963036:0.868377:56571:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.86916  ES:SE:LP:AF:SS:ID   -0.00327624:0.00214571:0.896894:0.86916:56571:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869166 ES:SE:LP:AF:SS:ID   -0.00327863:0.00214585:0.897752:0.869166:56571:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86917  ES:SE:LP:AF:SS:ID   -0.00327963:0.00214588:0.898136:0.86917:56571:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869567 ES:SE:LP:AF:SS:ID   -0.00337289:0.0021511:0.932219:0.869567:56571:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0998903    ES:SE:LP:AF:SS:ID   0.00393031:0.00249525:0.938412:0.0998903:56571:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00671909   ES:SE:LP:AF:SS:ID   0.00995185:0.00950644:0.529925:0.00671909:56571:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87357  ES:SE:LP:AF:SS:ID   -0.00342034:0.00218398:0.930587:0.87357:56571:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862977 ES:SE:LP:AF:SS:ID   -0.00365878:0.0021417:1.05761:0.862977:56571:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868296 ES:SE:LP:AF:SS:ID   -0.0031989:0.00216326:0.856317:0.868296:56571:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865477 ES:SE:LP:AF:SS:ID   -0.00335181:0.00216533:0.91492:0.865477:56571:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100288 ES:SE:LP:AF:SS:ID   0.00480329:0.00257857:1.20412:0.100288:56571:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870571 ES:SE:LP:AF:SS:ID   -0.00358468:0.00218876:0.993637:0.870571:56571:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870571 ES:SE:LP:AF:SS:ID   -0.00358465:0.00218876:0.993624:0.870571:56571:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870568 ES:SE:LP:AF:SS:ID   -0.00358525:0.00218876:0.993868:0.870568:56571:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870876 ES:SE:LP:AF:SS:ID   -0.00356854:0.00218939:0.98664:0.870876:56571:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126626 ES:SE:LP:AF:SS:ID   0.00356545:0.0021903:0.984787:0.126626:56571:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106451 ES:SE:LP:AF:SS:ID   0.0027711:0.00238165:0.611503:0.106451:56571:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85426  ES:SE:LP:AF:SS:ID   -0.00309231:0.00214093:0.827873:0.85426:56571:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837605 ES:SE:LP:AF:SS:ID   0.00219545:0.00211793:0.522986:0.837605:56571:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.761412 ES:SE:LP:AF:SS:ID   -0.00144565:0.00169971:0.403364:0.761412:56571:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106839 ES:SE:LP:AF:SS:ID   -0.00150347:0.00234291:0.28311:0.106839:56571:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00791884   ES:SE:LP:AF:SS:ID   0.00119849:0.0085841:0.0511163:0.00791884:56571:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.129967 ES:SE:LP:AF:SS:ID   0.0034921:0.0021596:0.975182:0.129967:56571:rs762168062