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-3859_1/ukb-d-3859_1.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-3859_1/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 16:54:38 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-3859_1/ukb-d-3859_1.vcf.gz ...
Read summary statistics for 11249290 SNPs.
Dropped 9421 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, 1282292 SNPs remain.
After merging with regression SNP LD, 1282292 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0014 (0.0352)
Lambda GC: 1.0003
Mean Chi^2: 1.0004
Intercept: 1.0001 (0.0063)
Ratio: 0.1539 (15.7472)
Analysis finished at Mon Nov 25 16:56:30 2019
Total time elapsed: 1.0m:51.33s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9467,
    "inflation_factor": 1.0008,
    "mean_EFFECT": -0.0001,
    "n": 12110,
    "n_snps": 11249290,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1149925,
    "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": 231019,
    "n_est": 12158.8664,
    "ratio_se_n": 1.002,
    "mean_diff": -0.0001,
    "ratio_diff": 39.2084,
    "sd_y_est1": 0.4418,
    "sd_y_est2": 0.4427,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1282292,
    "ldsc_nsnp_merge_regression_ld": 1282292,
    "ldsc_observed_scale_h2_beta": 0.0014,
    "ldsc_observed_scale_h2_se": 0.0352,
    "ldsc_intercept_beta": 1.0001,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.0003,
    "ldsc_mean_chisq": 1.0004,
    "ldsc_ratio": 0.25
}

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 11240467 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 51699 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 31533 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.074143e+00 6.182205e+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 7.882965e+07 5.600747e+07 3.02000e+02 3.261418e+07 6.982822e+07 1.147296e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -5.860000e-05 1.847770e-02 -1.80956e-01 -7.071200e-03 -2.940000e-05 6.970400e-03 2.240420e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.478860e-02 1.109590e-02 4.66620e-03 6.417100e-03 9.563600e-03 1.994750e-02 6.739580e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 5.000105e-01 2.884332e-01 2.00000e-07 2.500872e-01 4.998216e-01 7.497401e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.999973e-01 2.884411e-01 2.00000e-07 2.500645e-01 4.998083e-01 7.497340e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.282386e-01 2.613215e-01 3.93210e-03 2.171760e-02 1.116030e-01 3.649710e-01 9.960670e-01 ▇▂▁▁▁
numeric AF_reference 231019 0.9794637 NA NA NA NA NA 2.286556e-01 2.524770e-01 0.00000e+00 1.956870e-02 1.297920e-01 3.642170e-01 1.000000e+00 ▇▂▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.211000e+04 0.000000e+00 1.21100e+04 1.211000e+04 1.211000e+04 1.211000e+04 1.211000e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0081462 0.0102172 0.4252918 0.4252742 0.1063710 0.1894970 12110
1 693731 rs12238997 A G -0.0017688 0.0096384 0.8543999 0.8543972 0.1124560 0.1417730 12110
1 707522 rs371890604 G C 0.0026408 0.0108244 0.8072599 0.8072547 0.0935590 0.1293930 12110
1 717587 rs144155419 G A -0.0376966 0.0263518 0.1525959 0.1525698 0.0146719 0.0045926 12110
1 730087 rs148120343 T C 0.0050896 0.0131964 0.6997421 0.6997358 0.0560767 0.0127796 12110
1 731718 rs142557973 T C 0.0024958 0.0091325 0.7846338 0.7846295 0.1181390 0.1543530 12110
1 732032 rs61770163 A C -0.0024321 0.0097087 0.8022019 0.8021983 0.1171860 0.1555510 12110
1 734349 rs141242758 T C 0.0020913 0.0091433 0.8190869 0.8190828 0.1172760 0.1525560 12110
1 740284 rs61770167 C T 0.0209415 0.0418626 0.6169131 0.6169035 0.0055098 0.0023962 12110
1 749963 rs529266287 T TAA -0.0062331 0.0089895 0.4880845 0.4880708 0.8732310 0.7641770 12110
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0057168 0.0102891 0.5784835 0.5784740 0.0568286 0.0309934 12110
23 154923374 rs111332691 T A 0.0072274 0.0113068 0.5226994 0.5226875 0.0450041 0.0116556 12110
23 154925045 rs509981 C T -0.0062116 0.0054388 0.2534399 0.2534177 0.2481290 0.3634440 12110
23 154925895 rs538470 C T -0.0053406 0.0055713 0.3377902 0.3377709 0.2435470 0.3634440 12110
23 154927581 rs644138 G A -0.0041877 0.0051041 0.4119713 0.4119553 0.3053340 0.4635760 12110
23 154929412 rs557132 C T -0.0061880 0.0054390 0.2552607 0.2552385 0.2481050 0.3568210 12110
23 154929637 rs35185538 CT C -0.0100455 0.0056805 0.0770158 0.0769900 0.2314130 0.3011920 12110
23 154929952 rs4012982 CAA C -0.0066996 0.0057265 0.2420572 0.2420346 0.2421550 0.3165560 12110
23 154930230 rs781880 A G -0.0058720 0.0054408 0.2804969 0.2804756 0.2481380 0.3618540 12110
23 154930487 rs781879 T A -0.0550604 0.0192445 0.0042290 0.0042218 0.0191383 0.1263580 12110

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.106371 ES:SE:LP:AF:SS:ID   0.00814622:0.0102172:0.371313:0.106371:12110:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.112456 ES:SE:LP:AF:SS:ID   -0.00176876:0.00963845:0.0683388:0.112456:12110:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.093559 ES:SE:LP:AF:SS:ID   0.00264082:0.0108244:0.0929866:0.093559:12110:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0146719    ES:SE:LP:AF:SS:ID   -0.0376966:0.0263518:0.816457:0.0146719:12110:rs144155419
1   730087  rs148120343 T   C   .   PASS    AF=0.0560767    ES:SE:LP:AF:SS:ID   0.00508955:0.0131964:0.155062:0.0560767:12110:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.118139 ES:SE:LP:AF:SS:ID   0.00249582:0.00913246:0.105333:0.118139:12110:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.117186 ES:SE:LP:AF:SS:ID   -0.00243206:0.0097087:0.0957163:0.117186:12110:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.117276 ES:SE:LP:AF:SS:ID   0.0020913:0.0091433:0.08667:0.117276:12110:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00550979   ES:SE:LP:AF:SS:ID   0.0209415:0.0418626:0.209776:0.00550979:12110:rs61770167
1   749963  rs529266287 T   TAA .   PASS    AF=0.873231 ES:SE:LP:AF:SS:ID   -0.00623313:0.00898948:0.311505:0.873231:12110:rs529266287
1   751343  rs28544273  T   A   .   PASS    AF=0.118847 ES:SE:LP:AF:SS:ID   0.00407945:0.00889972:0.189305:0.118847:12110:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.139392 ES:SE:LP:AF:SS:ID   0.00247173:0.00874913:0.109268:0.139392:12110:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.118898 ES:SE:LP:AF:SS:ID   0.00379628:0.00888884:0.174362:0.118898:12110:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.874652 ES:SE:LP:AF:SS:ID   -0.00185788:0.00864901:0.0809638:0.874652:12110:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.880224 ES:SE:LP:AF:SS:ID   -0.00257305:0.00881408:0.113312:0.880224:12110:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.125144 ES:SE:LP:AF:SS:ID   0.00225541:0.00866914:0.0997744:0.125144:12110:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0373245    ES:SE:LP:AF:SS:ID   -0.011034:0.0152324:0.328968:0.0373245:12110:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.874034 ES:SE:LP:AF:SS:ID   -0.0019119:0.00863827:0.0836303:0.874034:12110:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.874136 ES:SE:LP:AF:SS:ID   -0.00120137:0.00864251:0.0508799:0.874136:12110:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.873944 ES:SE:LP:AF:SS:ID   -0.00204927:0.00863622:0.0902098:0.873944:12110:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00498632   ES:SE:LP:AF:SS:ID   -0.0130746:0.0435088:0.117022:0.00498632:12110:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00496705   ES:SE:LP:AF:SS:ID   -0.0132286:0.0435849:0.118327:0.00496705:12110:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00578715   ES:SE:LP:AF:SS:ID   0.0137515:0.0416504:0.130017:0.00578715:12110:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.874264 ES:SE:LP:AF:SS:ID   -0.00160465:0.00861868:0.0694055:0.874264:12110:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12222  ES:SE:LP:AF:SS:ID   0.00254813:0.00880881:0.112169:0.12222:12110:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.873823 ES:SE:LP:AF:SS:ID   -0.0022868:0.00859214:0.102303:0.873823:12110:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.872988 ES:SE:LP:AF:SS:ID   -0.00186726:0.00858841:0.0820289:0.872988:12110:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.873975 ES:SE:LP:AF:SS:ID   -0.00161811:0.00860149:0.0701797:0.873975:12110:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.873985 ES:SE:LP:AF:SS:ID   -0.00161406:0.00860214:0.0699857:0.873985:12110:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.873982 ES:SE:LP:AF:SS:ID   -0.00162025:0.00860193:0.0702751:0.873982:12110:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.874532 ES:SE:LP:AF:SS:ID   -0.00197885:0.00863128:0.0868927:0.874532:12110:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0949144    ES:SE:LP:AF:SS:ID   0.00400169:0.0101063:0.159806:0.0949144:12110:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00666602   ES:SE:LP:AF:SS:ID   -0.0155191:0.037475:0.168262:0.00666602:12110:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87903  ES:SE:LP:AF:SS:ID   -0.00356444:0.0087775:0.164509:0.87903:12110:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.867233 ES:SE:LP:AF:SS:ID   -0.000758626:0.00857671:0.0317417:0.867233:12110:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.873282 ES:SE:LP:AF:SS:ID   -0.00162853:0.00867218:0.070047:0.873282:12110:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.869868 ES:SE:LP:AF:SS:ID   -0.00118143:0.0086782:0.0497739:0.869868:12110:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0954198    ES:SE:LP:AF:SS:ID   0.00569275:0.0103765:0.234127:0.0954198:12110:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.875398 ES:SE:LP:AF:SS:ID   -0.0051262:0.00878725:0.252078:0.875398:12110:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.875398 ES:SE:LP:AF:SS:ID   -0.0051262:0.00878725:0.252078:0.875398:12110:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.875395 ES:SE:LP:AF:SS:ID   -0.00512641:0.00878729:0.25209:0.875395:12110:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87594  ES:SE:LP:AF:SS:ID   -0.00542728:0.00879411:0.269906:0.87594:12110:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.121511 ES:SE:LP:AF:SS:ID   0.00240678:0.00879949:0.105428:0.121511:12110:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.102697 ES:SE:LP:AF:SS:ID   0.00532928:0.00958213:0.237993:0.102697:12110:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.858913 ES:SE:LP:AF:SS:ID   -0.00406707:0.00860093:0.196325:0.858913:12110:rs2519015
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.836338 ES:SE:LP:AF:SS:ID   0.0156645:0.00829078:1.23015:0.836338:12110:rs376645387
1   768253  rs2977608   A   C   .   PASS    AF=0.765008 ES:SE:LP:AF:SS:ID   0.00583153:0.00672398:0.413627:0.765008:12110:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.107762 ES:SE:LP:AF:SS:ID   -0.0128509:0.00918261:0.791301:0.107762:12110:rs12562034
1   768819  rs12562811  C   T   .   PASS    AF=0.00752999   ES:SE:LP:AF:SS:ID   -0.0706341:0.034564:1.38703:0.00752999:12110:rs12562811
1   769138  rs59306077  CAT C   .   PASS    AF=0.12536  ES:SE:LP:AF:SS:ID   0.00145213:0.00865567:0.0620961:0.12536:12110:rs762168062