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-20435/ukb-d-20435.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-20435/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 17:18:45 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20435/ukb-d-20435.vcf.gz ...
Read summary statistics for 13558429 SNPs.
Dropped 12672 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0313 (0.0082)
Lambda GC: 1.0361
Mean Chi^2: 1.0414
Intercept: 1.0052 (0.0066)
Ratio: 0.1266 (0.1589)
Analysis finished at Mon Nov 25 17:21:02 2019
Total time elapsed: 2.0m:16.46s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.02,
    "mean_EFFECT": -0,
    "n": 58750,
    "n_snps": 13558429,
    "n_clumped_hits": 0,
    "n_p_sig": 1,
    "n_mono": 0,
    "n_ns": 1250854,
    "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": 561365,
    "n_est": 58924.3886,
    "ratio_se_n": 1.0015,
    "mean_diff": -0,
    "ratio_diff": 13.3362,
    "sd_y_est1": 0.4068,
    "sd_y_est2": 0.4074,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.0313,
    "ldsc_observed_scale_h2_se": 0.0082,
    "ldsc_intercept_beta": 1.0052,
    "ldsc_intercept_se": 0.0066,
    "ldsc_lambda_gc": 1.0361,
    "ldsc_mean_chisq": 1.0414,
    "ldsc_ratio": 0.1256
}

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 13546421 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57030 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33329 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051296e+00 6.184969e+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 7.902315e+07 5.591611e+07 3.02000e+02 3.292580e+07 7.013484e+07 1.148573e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -2.720000e-05 1.378910e-02 -2.09634e-01 -3.671600e-03 2.150000e-05 3.723800e-03 1.592600e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.919800e-03 9.554600e-03 2.00930e-03 2.837100e-03 5.213400e-03 1.424200e-02 5.088330e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.966869e-01 2.899601e-01 0.00000e+00 2.449740e-01 4.957435e-01 7.478440e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.966842e-01 2.899617e-01 0.00000e+00 2.449688e-01 4.957416e-01 7.478423e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911709e-01 2.544875e-01 1.00000e-03 7.529900e-03 6.046100e-02 2.960570e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 561365 0.9585966 NA NA NA NA NA 1.965983e-01 2.471520e-01 0.00000e+00 5.790700e-03 8.466450e-02 3.087060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 5.875000e+04 0.000000e+00 5.87500e+04 5.875000e+04 5.875000e+04 5.875000e+04 5.875000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0028669 0.0041320 0.4877935 0.4877891 0.1118220 0.1894970 58750
1 693731 rs12238997 A G 0.0084315 0.0039070 0.0309279 0.0309237 0.1169720 0.1417730 58750
1 707522 rs371890604 G C 0.0069071 0.0043775 0.1146019 0.1145962 0.0987790 0.1293930 58750
1 717587 rs144155419 G A 0.0115225 0.0105274 0.2737279 0.2737249 0.0157051 0.0045926 58750
1 723329 rs189787166 A T -0.0429233 0.0296711 0.1480038 0.1479987 0.0018775 0.0003994 58750
1 730087 rs148120343 T C 0.0014319 0.0054365 0.7922495 0.7922492 0.0570401 0.0127796 58750
1 731718 rs142557973 T C 0.0059661 0.0037072 0.1075489 0.1075434 0.1229220 0.1543530 58750
1 732032 rs61770163 A C 0.0060293 0.0039481 0.1267290 0.1267238 0.1225470 0.1555510 58750
1 734349 rs141242758 T C 0.0059857 0.0037083 0.1065021 0.1064969 0.1222140 0.1525560 58750
1 740284 rs61770167 C T 0.0051395 0.0168593 0.7604856 0.7604839 0.0059141 0.0023962 58750
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0058961 0.0044885 0.1889879 0.1889828 0.0552758 0.0309934 58750
23 154923374 rs111332691 T A -0.0039411 0.0049469 0.4256386 0.4256358 0.0435149 0.0116556 58750
23 154925045 rs509981 C T 0.0000777 0.0023449 0.9735721 0.9735723 0.2454930 0.3634440 58750
23 154925895 rs538470 C T 0.0000028 0.0023986 0.9990710 0.9990715 0.2416920 0.3634440 58750
23 154927581 rs644138 G A -0.0013929 0.0022082 0.5281825 0.5281817 0.3012080 0.4635760 58750
23 154929412 rs557132 C T -0.0000013 0.0023454 0.9995460 0.9995455 0.2453840 0.3568210 58750
23 154929637 rs35185538 CT C 0.0018343 0.0024504 0.4541152 0.4541130 0.2288610 0.3011920 58750
23 154929952 rs4012982 CAA C -0.0004166 0.0024717 0.8661580 0.8661569 0.2390270 0.3165560 58750
23 154930230 rs781880 A G 0.0000339 0.0023450 0.9884810 0.9884808 0.2457110 0.3618540 58750
23 154930487 rs781879 T A 0.0063392 0.0079700 0.4263959 0.4263927 0.0195183 0.1263580 58750

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111822 ES:SE:LP:AF:SS:ID   0.00286689:0.00413198:0.311764:0.111822:58750:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116972 ES:SE:LP:AF:SS:ID   0.00843149:0.00390699:1.50965:0.116972:58750:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.098779 ES:SE:LP:AF:SS:ID   0.00690708:0.00437748:0.940808:0.098779:58750:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157051    ES:SE:LP:AF:SS:ID   0.0115225:0.0105274:0.562681:0.0157051:58750:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00187751   ES:SE:LP:AF:SS:ID   -0.0429233:0.0296711:0.829727:0.00187751:58750:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0570401    ES:SE:LP:AF:SS:ID   0.00143192:0.00543648:0.101138:0.0570401:58750:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122922 ES:SE:LP:AF:SS:ID   0.00596609:0.00370718:0.968394:0.122922:58750:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122547 ES:SE:LP:AF:SS:ID   0.00602934:0.0039481:0.897124:0.122547:58750:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.122214 ES:SE:LP:AF:SS:ID   0.00598567:0.00370827:0.972642:0.122214:58750:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00591409   ES:SE:LP:AF:SS:ID   0.00513948:0.0168593:0.118909:0.00591409:58750:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00192758   ES:SE:LP:AF:SS:ID   0.042592:0.031578:0.751022:0.00192758:58750:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868755 ES:SE:LP:AF:SS:ID   -0.00709983:0.00365141:1.28524:0.868755:58750:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0016021    ES:SE:LP:AF:SS:ID   0.0573746:0.0323151:1.12019:0.0016021:58750:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.124193 ES:SE:LP:AF:SS:ID   0.0068836:0.00361441:1.24526:0.124193:58750:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143652 ES:SE:LP:AF:SS:ID   0.00559971:0.00357913:0.929242:0.143652:58750:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12429  ES:SE:LP:AF:SS:ID   0.00681854:0.00360965:1.22988:0.12429:58750:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869521 ES:SE:LP:AF:SS:ID   -0.00708017:0.00351944:1.35406:0.869521:58750:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874072 ES:SE:LP:AF:SS:ID   -0.00735682:0.00357435:1.40261:0.874072:58750:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129785 ES:SE:LP:AF:SS:ID   0.00705628:0.00353121:1.34015:0.129785:58750:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0362723    ES:SE:LP:AF:SS:ID   0.0082582:0.00644166:0.6993:0.0362723:58750:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869172 ES:SE:LP:AF:SS:ID   -0.00720985:0.00351655:1.39423:0.869172:58750:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86923  ES:SE:LP:AF:SS:ID   -0.00727728:0.00351728:1.41398:0.86923:58750:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869167 ES:SE:LP:AF:SS:ID   -0.00720578:0.00351638:1.39312:0.869167:58750:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00494458   ES:SE:LP:AF:SS:ID   0.01874:0.0183853:0.511355:0.00494458:58750:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00491651   ES:SE:LP:AF:SS:ID   0.0189426:0.0184264:0.517199:0.00491651:58750:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00573777   ES:SE:LP:AF:SS:ID   0.0108955:0.0172956:0.27677:0.00573777:58750:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869168 ES:SE:LP:AF:SS:ID   -0.00712368:0.00350923:1.37302:0.869168:58750:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.127188 ES:SE:LP:AF:SS:ID   0.00720902:0.00358247:1.35465:0.127188:58750:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868681 ES:SE:LP:AF:SS:ID   -0.006987:0.00350007:1.33807:0.868681:58750:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868206 ES:SE:LP:AF:SS:ID   -0.00704399:0.00349934:1.35532:0.868206:58750:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.868883 ES:SE:LP:AF:SS:ID   -0.00702014:0.00350343:1.34585:0.868883:58750:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.868889 ES:SE:LP:AF:SS:ID   -0.00702002:0.00350367:1.34567:0.868889:58750:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.868892 ES:SE:LP:AF:SS:ID   -0.00701694:0.00350369:1.34476:0.868892:58750:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869303 ES:SE:LP:AF:SS:ID   -0.00715493:0.00351257:1.38028:0.869303:58750:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.100093 ES:SE:LP:AF:SS:ID   0.00741478:0.00407737:1.16121:0.100093:58750:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00665115   ES:SE:LP:AF:SS:ID   -0.00038338:0.0156254:0.00858562:0.00665115:58750:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873284 ES:SE:LP:AF:SS:ID   -0.00700307:0.00356532:1.30531:0.873284:58750:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862832 ES:SE:LP:AF:SS:ID   -0.00758286:0.00349794:1.52032:0.862832:58750:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868021 ES:SE:LP:AF:SS:ID   -0.00672353:0.00353212:1.24432:0.868021:58750:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865178 ES:SE:LP:AF:SS:ID   -0.00613675:0.0035348:1.08327:0.865178:58750:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.100283 ES:SE:LP:AF:SS:ID   0.00790495:0.00421893:1.21482:0.100283:58750:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870192 ES:SE:LP:AF:SS:ID   -0.00636171:0.00357233:1.12525:0.870192:58750:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870192 ES:SE:LP:AF:SS:ID   -0.00636164:0.00357233:1.12523:0.870192:58750:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870188 ES:SE:LP:AF:SS:ID   -0.00636311:0.00357234:1.12562:0.870188:58750:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870509 ES:SE:LP:AF:SS:ID   -0.00647143:0.00357367:1.15387:0.870509:58750:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126848 ES:SE:LP:AF:SS:ID   0.0064818:0.00357813:1.15448:0.126848:58750:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106679 ES:SE:LP:AF:SS:ID   0.00518005:0.00389059:0.737423:0.106679:58750:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854053 ES:SE:LP:AF:SS:ID   -0.00712425:0.0034949:1.38187:0.854053:58750:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00177802   ES:SE:LP:AF:SS:ID   -0.043827:0.0299079:0.845217:0.00177802:58750:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.837828 ES:SE:LP:AF:SS:ID   0.000593491:0.00346231:0.0635375:0.837828:58750:rs376645387