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-1418_6/ukb-d-1418_6.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-1418_6/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 17:05:08 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1418_6/ukb-d-1418_6.vcf.gz ...
Read summary statistics for 13512194 SNPs.
Dropped 12621 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, 1283489 SNPs remain.
After merging with regression SNP LD, 1283489 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.014 (0.0015)
Lambda GC: 1.0968
Mean Chi^2: 1.1061
Intercept: 1.0067 (0.0059)
Ratio: 0.0632 (0.0552)
Analysis finished at Mon Nov 25 17:07:27 2019
Total time elapsed: 2.0m:19.08s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.952,
    "inflation_factor": 1.0572,
    "mean_EFFECT": 5.2877e-06,
    "n": 360806,
    "n_snps": 13512194,
    "n_clumped_hits": 2,
    "n_p_sig": 61,
    "n_mono": 0,
    "n_ns": 1249669,
    "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": 549110,
    "n_est": 362090.4891,
    "ratio_se_n": 1.0018,
    "mean_diff": 0,
    "ratio_diff": 75.4109,
    "sd_y_est1": 0.177,
    "sd_y_est2": 0.1773,
    "r2_sum1": 6.2757e-06,
    "r2_sum2": 0.0002,
    "r2_sum3": 0.0002,
    "r2_sum4": 0.0002,
    "ldsc_nsnp_merge_refpanel_ld": 1283489,
    "ldsc_nsnp_merge_regression_ld": 1283489,
    "ldsc_observed_scale_h2_beta": 0.014,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.0067,
    "ldsc_intercept_se": 0.0059,
    "ldsc_lambda_gc": 1.0968,
    "ldsc_mean_chisq": 1.1061,
    "ldsc_ratio": 0.0631
}

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 13500236 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56949 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33307 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.052287e+00 6.185275e+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 7.902138e+07 5.591950e+07 3.02000e+02 3.291582e+07 7.013443e+07 1.148569e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.300000e-06 2.398900e-03 -2.50323e-02 -6.663000e-04 -4.500000e-06 6.509000e-04 3.571490e-02 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.723200e-03 1.652100e-03 3.42600e-04 4.974000e-04 9.098000e-04 2.472700e-03 8.402300e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.910360e-01 2.911129e-01 0.00000e+00 2.368209e-01 4.879980e-01 7.431423e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.910356e-01 2.911132e-01 0.00000e+00 2.368200e-01 4.879978e-01 7.431432e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.917858e-01 2.546371e-01 1.07880e-03 7.684400e-03 6.121020e-02 2.973000e-01 9.989210e-01 ▇▂▁▁▁
numeric AF_reference 549110 0.9593619 NA NA NA NA NA 1.970538e-01 2.472550e-01 0.00000e+00 5.790700e-03 8.526360e-02 3.095050e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.608060e+05 0.000000e+00 3.60806e+05 3.608060e+05 3.608060e+05 3.608060e+05 3.608060e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0008103 0.0007296 0.2667497 0.2667493 0.1106400 0.1894970 360806
1 693731 rs12238997 A G 0.0003377 0.0006893 0.6242305 0.6242306 0.1158360 0.1417730 360806
1 707522 rs371890604 G C 0.0006264 0.0007750 0.4189180 0.4189172 0.0973005 0.1293930 360806
1 717587 rs144155419 G A 0.0013488 0.0018491 0.4657244 0.4657218 0.0156910 0.0045926 360806
1 723329 rs189787166 A T 0.0003549 0.0054557 0.9481370 0.9481375 0.0017340 0.0003994 360806
1 730087 rs148120343 T C 0.0004984 0.0009604 0.6037957 0.6037953 0.0564560 0.0127796 360806
1 731718 rs142557973 T C 0.0005974 0.0006538 0.3608228 0.3608223 0.1217420 0.1543530 360806
1 732032 rs61770163 A C 0.0009573 0.0006974 0.1698361 0.1698352 0.1211750 0.1555510 360806
1 734349 rs141242758 T C 0.0006058 0.0006541 0.3544011 0.3544002 0.1209690 0.1525560 360806
1 740284 rs61770167 C T -0.0007395 0.0029926 0.8048301 0.8048295 0.0057852 0.0023962 360806
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0002572 0.0007554 0.7334508 0.7334504 0.0561637 0.0309934 360806
23 154923374 rs111332691 T A -0.0001158 0.0008301 0.8890120 0.8890118 0.0447817 0.0116556 360806
23 154925045 rs509981 C T 0.0006231 0.0003994 0.1187569 0.1187563 0.2456180 0.3634440 360806
23 154925895 rs538470 C T 0.0005919 0.0004086 0.1474609 0.1474596 0.2419280 0.3634440 360806
23 154927581 rs644138 G A 0.0006124 0.0003756 0.1030400 0.1030398 0.3021690 0.4635760 360806
23 154929412 rs557132 C T 0.0006387 0.0003995 0.1099299 0.1099292 0.2454700 0.3568210 360806
23 154929637 rs35185538 CT C 0.0004803 0.0004170 0.2494170 0.2494173 0.2297070 0.3011920 360806
23 154929952 rs4012982 CAA C 0.0006528 0.0004202 0.1203140 0.1203140 0.2394320 0.3165560 360806
23 154930230 rs781880 A G 0.0005852 0.0003995 0.1429690 0.1429678 0.2458800 0.3618540 360806
23 154930487 rs781879 T A -0.0003068 0.0013702 0.8228391 0.8228394 0.0195658 0.1263580 360806

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11064  ES:SE:LP:AF:SS:ID   0.000810259:0.000729582:0.573896:0.11064:360806:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115836 ES:SE:LP:AF:SS:ID   0.000337678:0.000689331:0.204655:0.115836:360806:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0973005    ES:SE:LP:AF:SS:ID   0.000626423:0.000774987:0.377871:0.0973005:360806:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015691 ES:SE:LP:AF:SS:ID   0.00134884:0.0018491:0.331871:0.015691:360806:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173396   ES:SE:LP:AF:SS:ID   0.000354872:0.00545572:0.0231289:0.00173396:360806:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056456 ES:SE:LP:AF:SS:ID   0.0004984:0.0009604:0.21911:0.056456:360806:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121742 ES:SE:LP:AF:SS:ID   0.00059741:0.000653765:0.442706:0.121742:360806:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121175 ES:SE:LP:AF:SS:ID   0.000957306:0.000697372:0.76997:0.121175:360806:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120969 ES:SE:LP:AF:SS:ID   0.00060577:0.000654117:0.450505:0.120969:360806:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578523   ES:SE:LP:AF:SS:ID   -0.000739479:0.00299261:0.0942958:0.00578523:360806:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187907   ES:SE:LP:AF:SS:ID   0.000621162:0.00564937:0.0397924:0.00187907:360806:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.869735 ES:SE:LP:AF:SS:ID   -0.000693319:0.000644854:0.54928:0.869735:360806:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00152775   ES:SE:LP:AF:SS:ID   -0.00338848:0.00584402:0.250235:0.00152775:360806:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122925 ES:SE:LP:AF:SS:ID   0.000711672:0.000638643:0.576541:0.122925:360806:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14272  ES:SE:LP:AF:SS:ID   0.000730383:0.000631251:0.606853:0.14272:360806:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123041 ES:SE:LP:AF:SS:ID   0.00072709:0.000637753:0.594732:0.123041:360806:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87088  ES:SE:LP:AF:SS:ID   -0.000697163:0.000621474:0.581778:0.87088:360806:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875464 ES:SE:LP:AF:SS:ID   -0.00074625:0.000631777:0.624287:0.875464:360806:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128641 ES:SE:LP:AF:SS:ID   0.000758713:0.000623024:0.651102:0.128641:360806:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.03637  ES:SE:LP:AF:SS:ID   0.000795247:0.00113023:0.317249:0.03637:360806:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870473 ES:SE:LP:AF:SS:ID   -0.000737636:0.000620827:0.629348:0.870473:360806:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870579 ES:SE:LP:AF:SS:ID   -0.000769127:0.000621111:0.666347:0.870579:360806:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87047  ES:SE:LP:AF:SS:ID   -0.000740636:0.000620804:0.632905:0.87047:360806:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504757   ES:SE:LP:AF:SS:ID   0.00238498:0.00318594:0.342848:0.00504757:360806:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00501451   ES:SE:LP:AF:SS:ID   0.00227597:0.00319446:0.322236:0.00501451:360806:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558365   ES:SE:LP:AF:SS:ID   -0.000399736:0.0030875:0.0472139:0.00558365:360806:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870553 ES:SE:LP:AF:SS:ID   -0.000727474:0.000619711:0.618995:0.870553:360806:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125995 ES:SE:LP:AF:SS:ID   0.000829187:0.000632327:0.721821:0.125995:360806:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870116 ES:SE:LP:AF:SS:ID   -0.000776929:0.000618218:0.680155:0.870116:360806:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869403 ES:SE:LP:AF:SS:ID   -0.000762705:0.000617654:0.66376:0.869403:360806:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87027  ES:SE:LP:AF:SS:ID   -0.000739181:0.000618751:0.63408:0.87027:360806:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870276 ES:SE:LP:AF:SS:ID   -0.00073929:0.000618795:0.634147:0.870276:360806:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.870285 ES:SE:LP:AF:SS:ID   -0.000724124:0.000618814:0.61631:0.870285:360806:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870728 ES:SE:LP:AF:SS:ID   -0.000737519:0.000620391:0.62982:0.870728:360806:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988444    ES:SE:LP:AF:SS:ID   0.000569988:0.000720954:0.367365:0.0988444:360806:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647302   ES:SE:LP:AF:SS:ID   -0.000532784:0.00278926:0.07134:0.00647302:360806:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874626 ES:SE:LP:AF:SS:ID   -0.00082631:0.000629641:0.722613:0.874626:360806:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864015 ES:SE:LP:AF:SS:ID   -0.000806835:0.000617451:0.718265:0.864015:360806:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869416 ES:SE:LP:AF:SS:ID   -0.000782746:0.000623447:0.679245:0.869416:360806:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86636  ES:SE:LP:AF:SS:ID   -0.000971281:0.000623572:0.923261:0.86636:360806:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987861    ES:SE:LP:AF:SS:ID   0.000929683:0.00074655:0.671578:0.0987861:360806:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871547 ES:SE:LP:AF:SS:ID   -0.000983244:0.000630681:0.924479:0.871547:360806:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871547 ES:SE:LP:AF:SS:ID   -0.000983127:0.000630681:0.924322:0.871547:360806:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871546 ES:SE:LP:AF:SS:ID   -0.000983678:0.000630692:0.925048:0.871546:360806:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87192  ES:SE:LP:AF:SS:ID   -0.000930013:0.000631053:0.852169:0.87192:360806:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125571 ES:SE:LP:AF:SS:ID   0.000828764:0.000631544:0.722563:0.125571:360806:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.105431 ES:SE:LP:AF:SS:ID   0.000340376:0.000687544:0.207218:0.105431:360806:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855365 ES:SE:LP:AF:SS:ID   -0.000559275:0.000617216:0.437862:0.855365:360806:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00165469   ES:SE:LP:AF:SS:ID   0.00312017:0.00546746:0.245486:0.00165469:360806:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838366 ES:SE:LP:AF:SS:ID   -0.000419699:0.000608112:0.309725:0.838366:360806:rs376645387