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-20540/ukb-d-20540.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-20540/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 17:18:00 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20540/ukb-d-20540.vcf.gz ...
Read summary statistics for 13542329 SNPs.
Dropped 12659 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, 1283495 SNPs remain.
After merging with regression SNP LD, 1283495 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.023 (0.0124)
Lambda GC: 1.0118
Mean Chi^2: 1.0125
Intercept: 0.9968 (0.0059)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:19:57 2019
Total time elapsed: 1.0m:56.99s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0059,
    "mean_EFFECT": 0,
    "n": 35038,
    "n_snps": 13542329,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1250240,
    "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": 557695,
    "n_est": 35152.4573,
    "ratio_se_n": 1.0016,
    "mean_diff": 0,
    "ratio_diff": 6.1606,
    "sd_y_est1": 0.429,
    "sd_y_est2": 0.4297,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283495,
    "ldsc_nsnp_merge_regression_ld": 1283495,
    "ldsc_observed_scale_h2_beta": 0.023,
    "ldsc_observed_scale_h2_se": 0.0124,
    "ldsc_intercept_beta": 0.9968,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0118,
    "ldsc_mean_chisq": 1.0125,
    "ldsc_ratio": -0.256
}

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 13530334 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57004 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33313 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051547e+00 6.185035e+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 7.902285e+07 5.591469e+07 3.02000e+02 3.292461e+07 7.013970e+07 1.148532e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.150000e-05 1.874970e-02 -2.73347e-01 -4.924800e-03 3.640000e-05 5.038900e-03 2.100870e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.350400e-02 1.299880e-02 2.75330e-03 3.871700e-03 7.102700e-03 1.937140e-02 7.042680e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.989043e-01 2.891312e-01 0.00000e+00 2.478780e-01 4.987432e-01 7.493695e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.988998e-01 2.891339e-01 0.00000e+00 2.478699e-01 4.987382e-01 7.493680e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.913894e-01 2.545454e-01 1.00000e-03 7.584300e-03 6.071300e-02 2.965350e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 557695 0.9588184 NA NA NA NA NA 1.967609e-01 2.471950e-01 0.00000e+00 5.790700e-03 8.486420e-02 3.089060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.503800e+04 0.000000e+00 3.50380e+04 3.503800e+04 3.503800e+04 3.503800e+04 3.503800e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0059822 0.0056370 0.2885918 0.2885843 0.1122080 0.1894970 35038
1 693731 rs12238997 A G -0.0029672 0.0053208 0.5770760 0.5770724 0.1174890 0.1417730 35038
1 707522 rs371890604 G C -0.0047314 0.0059742 0.4283759 0.4283709 0.0990852 0.1293930 35038
1 717587 rs144155419 G A -0.0033426 0.0140254 0.8116321 0.8116303 0.0164023 0.0045926 35038
1 723329 rs189787166 A T -0.0598654 0.0416394 0.1505251 0.1505162 0.0018030 0.0003994 35038
1 730087 rs148120343 T C -0.0139639 0.0073851 0.0586557 0.0586469 0.0572581 0.0127796 35038
1 731718 rs142557973 T C -0.0054442 0.0050432 0.2803709 0.2803637 0.1239910 0.1543530 35038
1 732032 rs61770163 A C -0.0042083 0.0053744 0.4336137 0.4336091 0.1234660 0.1555510 35038
1 734349 rs141242758 T C -0.0052780 0.0050473 0.2957011 0.2956941 0.1231720 0.1525560 35038
1 740284 rs61770167 C T 0.0244949 0.0238077 0.3035519 0.3035433 0.0055561 0.0023962 35038
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0037020 0.0060617 0.5413959 0.5413922 0.0564580 0.0309934 35038
23 154923374 rs111332691 T A 0.0001355 0.0067301 0.9839370 0.9839366 0.0442948 0.0116556 35038
23 154925045 rs509981 C T -0.0037532 0.0032269 0.2447902 0.2447836 0.2431680 0.3634440 35038
23 154925895 rs538470 C T -0.0035474 0.0032998 0.2823703 0.2823617 0.2395430 0.3634440 35038
23 154927581 rs644138 G A -0.0043874 0.0030274 0.1472760 0.1472666 0.3000600 0.4635760 35038
23 154929412 rs557132 C T -0.0038438 0.0032279 0.2337362 0.2337279 0.2430000 0.3568210 35038
23 154929637 rs35185538 CT C -0.0024490 0.0033709 0.4675198 0.4675159 0.2274750 0.3011920 35038
23 154929952 rs4012982 CAA C -0.0032533 0.0033988 0.3384738 0.3384668 0.2374040 0.3165560 35038
23 154930230 rs781880 A G -0.0039298 0.0032274 0.2233588 0.2233517 0.2432690 0.3618540 35038
23 154930487 rs781879 T A -0.0193160 0.0106978 0.0709888 0.0709801 0.0202232 0.1263580 35038

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.112208 ES:SE:LP:AF:SS:ID   -0.00598221:0.00563704:0.539716:0.112208:35038:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.117489 ES:SE:LP:AF:SS:ID   -0.00296723:0.0053208:0.238767:0.117489:35038:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0990852    ES:SE:LP:AF:SS:ID   -0.00473143:0.00597416:0.368175:0.0990852:35038:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0164023    ES:SE:LP:AF:SS:ID   -0.00334258:0.0140254:0.0906408:0.0164023:35038:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00180303   ES:SE:LP:AF:SS:ID   -0.0598654:0.0416394:0.822391:0.00180303:35038:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0572581    ES:SE:LP:AF:SS:ID   -0.0139639:0.00738506:1.23169:0.0572581:35038:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.123991 ES:SE:LP:AF:SS:ID   -0.00544418:0.00504323:0.552267:0.123991:35038:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.123466 ES:SE:LP:AF:SS:ID   -0.00420832:0.0053744:0.362897:0.123466:35038:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.123172 ES:SE:LP:AF:SS:ID   -0.00527798:0.00504726:0.529147:0.123172:35038:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0055561    ES:SE:LP:AF:SS:ID   0.0244949:0.0238077:0.517767:0.0055561:35038:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00198843   ES:SE:LP:AF:SS:ID   0.0308268:0.0421472:0.332982:0.00198843:35038:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.867316 ES:SE:LP:AF:SS:ID   0.00646188:0.00496053:0.715118:0.867316:35038:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00147045   ES:SE:LP:AF:SS:ID   0.0793205:0.0463865:1.0591:0.00147045:35038:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.125272 ES:SE:LP:AF:SS:ID   -0.00529656:0.00491771:0.550565:0.125272:35038:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.145142 ES:SE:LP:AF:SS:ID   -0.00573208:0.00486346:0.622393:0.145142:35038:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12535  ES:SE:LP:AF:SS:ID   -0.00514335:0.00491127:0.530194:0.12535:35038:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.868003 ES:SE:LP:AF:SS:ID   0.00359463:0.00478778:0.344111:0.868003:35038:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.873037 ES:SE:LP:AF:SS:ID   0.0042851:0.00486549:0.421958:0.873037:35038:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.131434 ES:SE:LP:AF:SS:ID   -0.00426096:0.00479912:0.426409:0.131434:35038:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363605    ES:SE:LP:AF:SS:ID   0.0175098:0.00878666:1.33447:0.0363605:35038:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.867554 ES:SE:LP:AF:SS:ID   0.00377336:0.00478116:0.36654:0.867554:35038:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.867629 ES:SE:LP:AF:SS:ID   0.00352873:0.00478219:0.336688:0.867629:35038:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867549 ES:SE:LP:AF:SS:ID   0.00377499:0.00478094:0.366762:0.867549:35038:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00550159   ES:SE:LP:AF:SS:ID   0.00436337:0.0236111:0.0688545:0.00550159:35038:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00547546   ES:SE:LP:AF:SS:ID   0.00464978:0.0236594:0.0735562:0.00547546:35038:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0059377    ES:SE:LP:AF:SS:ID   0.00202651:0.0231269:0.0314353:0.0059377:35038:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.86765  ES:SE:LP:AF:SS:ID   0.00339145:0.00477472:0.321002:0.86765:35038:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12873  ES:SE:LP:AF:SS:ID   -0.00423329:0.00486849:0.415031:0.12873:35038:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86713  ES:SE:LP:AF:SS:ID   0.00346766:0.00476187:0.33116:0.86713:35038:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866594 ES:SE:LP:AF:SS:ID   0.00362146:0.00475886:0.350018:0.866594:35038:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867326 ES:SE:LP:AF:SS:ID   0.00338959:0.00476674:0.321452:0.867326:35038:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867334 ES:SE:LP:AF:SS:ID   0.00339273:0.00476706:0.321798:0.867334:35038:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867336 ES:SE:LP:AF:SS:ID   0.00338053:0.00476708:0.320353:0.867336:35038:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.867787 ES:SE:LP:AF:SS:ID   0.00337461:0.00477911:0.31865:0.867787:35038:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100494 ES:SE:LP:AF:SS:ID   -0.00541587:0.00555699:0.481799:0.100494:35038:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00686504   ES:SE:LP:AF:SS:ID   0.00644724:0.0209644:0.120079:0.00686504:35038:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.872091 ES:SE:LP:AF:SS:ID   0.00454765:0.00485187:0.457658:0.872091:35038:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.860995 ES:SE:LP:AF:SS:ID   0.00264635:0.00475314:0.238301:0.860995:35038:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.866693 ES:SE:LP:AF:SS:ID   0.00323674:0.00480761:0.300344:0.866693:35038:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.863685 ES:SE:LP:AF:SS:ID   0.00273334:0.00480539:0.244514:0.863685:35038:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.101097 ES:SE:LP:AF:SS:ID   -0.00170378:0.00573477:0.115548:0.101097:35038:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.868923 ES:SE:LP:AF:SS:ID   0.0037211:0.00485804:0.35291:0.868923:35038:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.868923 ES:SE:LP:AF:SS:ID   0.00371993:0.00485804:0.35277:0.868923:35038:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.868919 ES:SE:LP:AF:SS:ID   0.00372042:0.00485805:0.352827:0.868919:35038:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.869318 ES:SE:LP:AF:SS:ID   0.00422204:0.00486116:0.414412:0.869318:35038:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.128127 ES:SE:LP:AF:SS:ID   -0.00461919:0.00486769:0.465145:0.128127:35038:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106945 ES:SE:LP:AF:SS:ID   -0.00576769:0.00530799:0.557177:0.106945:35038:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.852719 ES:SE:LP:AF:SS:ID   0.00518573:0.00475114:0.56055:0.852719:35038:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00172228   ES:SE:LP:AF:SS:ID   -0.0680719:0.0418267:0.984452:0.00172228:35038:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837767 ES:SE:LP:AF:SS:ID   0.00149955:0.00473334:0.124133:0.837767:35038:rs376645387