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-12340_irnt/ukb-d-12340_irnt.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-12340_irnt/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 15:35:31 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-12340_irnt/ukb-d-12340_irnt.vcf.gz ...
Read summary statistics for 13479244 SNPs.
Dropped 12539 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, 1283473 SNPs remain.
After merging with regression SNP LD, 1283473 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1979 (0.062)
Lambda GC: 1.0337
Mean Chi^2: 1.0442
Intercept: 1.0006 (0.0078)
Ratio: 0.014 (0.1773)
Analysis finished at Mon Nov 25 15:37:47 2019
Total time elapsed: 2.0m:16.08s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9519,
    "inflation_factor": 1.0265,
    "mean_EFFECT": 0.0002,
    "n": 10815,
    "n_snps": 13479244,
    "n_clumped_hits": 6,
    "n_p_sig": 181,
    "n_mono": 0,
    "n_ns": 1247921,
    "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": 544284,
    "n_est": 10899.5601,
    "ratio_se_n": 1.0039,
    "mean_diff": 0,
    "ratio_diff": 498.7377,
    "sd_y_est1": 0.9281,
    "sd_y_est2": 0.9317,
    "r2_sum1": 0.0217,
    "r2_sum2": 0.0252,
    "r2_sum3": 0.025,
    "r2_sum4": 0.025,
    "ldsc_nsnp_merge_refpanel_ld": 1283473,
    "ldsc_nsnp_merge_regression_ld": 1283473,
    "ldsc_observed_scale_h2_beta": 0.1979,
    "ldsc_observed_scale_h2_se": 0.062,
    "ldsc_intercept_beta": 1.0006,
    "ldsc_intercept_se": 0.0078,
    "ldsc_lambda_gc": 1.0337,
    "ldsc_mean_chisq": 1.0442,
    "ldsc_ratio": 0.0136
}

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 13467367 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 56883 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33286 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.052447e+00 6.184533e+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 7.901826e+07 5.591896e+07 3.02000e+02 3.291160e+07 7.012677e+07 1.148529e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.609000e-04 7.233410e-02 -9.54985e-01 -1.938760e-02 4.590000e-05 1.960740e-02 9.903430e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 5.190830e-02 4.984090e-02 1.02435e-02 1.505620e-02 2.743460e-02 7.429050e-02 2.876270e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.958716e-01 2.900019e-01 0.00000e+00 2.434838e-01 4.943813e-01 7.471761e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.958568e-01 2.900107e-01 0.00000e+00 2.434583e-01 4.943658e-01 7.471700e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.922283e-01 2.547596e-01 1.00010e-03 7.807800e-03 6.181230e-02 2.981830e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 544284 0.9596206 NA NA NA NA NA 1.974393e-01 2.473497e-01 0.00000e+00 5.990400e-03 8.586260e-02 3.103040e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.081500e+04 0.000000e+00 1.08150e+04 1.081500e+04 1.081500e+04 1.081500e+04 1.081500e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0126074 0.0217927 0.5629295 0.5629166 0.1139760 0.1894970 10815
1 693731 rs12238997 A G 0.0104354 0.0206423 0.6131941 0.6131833 0.1199000 0.1417730 10815
1 707522 rs371890604 G C 0.0062361 0.0230645 0.7868755 0.7868702 0.1008110 0.1293930 10815
1 717587 rs144155419 G A 0.0744992 0.0537643 0.1658788 0.1658498 0.0171633 0.0045926 10815
1 723329 rs189787166 A T 0.1796860 0.1500490 0.2311320 0.2311057 0.0020663 0.0003994 10815
1 730087 rs148120343 T C -0.0209791 0.0286399 0.4638729 0.4638555 0.0587617 0.0127796 10815
1 731718 rs142557973 T C 0.0095752 0.0194807 0.6230674 0.6230581 0.1264700 0.1543530 10815
1 732032 rs61770163 A C 0.0086733 0.0207084 0.6753470 0.6753389 0.1262090 0.1555510 10815
1 734349 rs141242758 T C 0.0098811 0.0194909 0.6121925 0.6121817 0.1257700 0.1525560 10815
1 740284 rs61770167 C T 0.0063365 0.0922387 0.9452331 0.9452313 0.0056294 0.0023962 10815
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0087743 0.0225611 0.6973487 0.6973410 0.0570511 0.0309934 10815
23 154923374 rs111332691 T A 0.0009749 0.0253697 0.9693480 0.9693471 0.0427647 0.0116556 10815
23 154925045 rs509981 C T 0.0122648 0.0120172 0.3074659 0.3074422 0.2438940 0.3634440 10815
23 154925895 rs538470 C T 0.0112160 0.0122711 0.3607281 0.3607077 0.2401820 0.3634440 10815
23 154927581 rs644138 G A 0.0079202 0.0112743 0.4823808 0.4823650 0.3012260 0.4635760 10815
23 154929412 rs557132 C T 0.0124222 0.0120206 0.3014338 0.3014124 0.2436250 0.3568210 10815
23 154929637 rs35185538 CT C 0.0122206 0.0125979 0.3320443 0.3320213 0.2261650 0.3011920 10815
23 154929952 rs4012982 CAA C 0.0123707 0.0126240 0.3271410 0.3271182 0.2381630 0.3165560 10815
23 154930230 rs781880 A G 0.0117053 0.0120090 0.3297243 0.3297038 0.2446020 0.3618540 10815
23 154930487 rs781879 T A 0.0135295 0.0413676 0.7436319 0.7436259 0.0189611 0.1263580 10815

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.113976 ES:SE:LP:AF:SS:ID   0.0126074:0.0217927:0.249546:0.113976:10815:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.1199   ES:SE:LP:AF:SS:ID   0.0104354:0.0206423:0.212402:0.1199:10815:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.100811 ES:SE:LP:AF:SS:ID   0.00623611:0.0230645:0.104094:0.100811:10815:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0171633    ES:SE:LP:AF:SS:ID   0.0744992:0.0537643:0.780209:0.0171633:10815:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0020663    ES:SE:LP:AF:SS:ID   0.179686:0.150049:0.63614:0.0020663:10815:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0587617    ES:SE:LP:AF:SS:ID   -0.0209791:0.0286399:0.333601:0.0587617:10815:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12647  ES:SE:LP:AF:SS:ID   0.00957517:0.0194807:0.205465:0.12647:10815:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.126209 ES:SE:LP:AF:SS:ID   0.00867334:0.0207084:0.170473:0.126209:10815:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12577  ES:SE:LP:AF:SS:ID   0.00988114:0.0194909:0.213112:0.12577:10815:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00562944   ES:SE:LP:AF:SS:ID   0.00633646:0.0922387:0.0244611:0.00562944:10815:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00164079   ES:SE:LP:AF:SS:ID   -0.0451154:0.187201:0.091751:0.00164079:10815:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.864266 ES:SE:LP:AF:SS:ID   -0.0125219:0.0191507:0.289701:0.864266:10815:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00183659   ES:SE:LP:AF:SS:ID   -0.0201401:0.153707:0.0478108:0.00183659:10815:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.127987 ES:SE:LP:AF:SS:ID   0.00900584:0.0189886:0.197013:0.127987:10815:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14622  ES:SE:LP:AF:SS:ID   -0.00346723:0.0188609:0.0684664:0.14622:10815:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.128176 ES:SE:LP:AF:SS:ID   0.00912303:0.0189585:0.2004:0.128176:10815:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.865564 ES:SE:LP:AF:SS:ID   -0.00924554:0.0184842:0.209747:0.865564:10815:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.870164 ES:SE:LP:AF:SS:ID   -0.00820337:0.0187728:0.179055:0.870164:10815:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.133888 ES:SE:LP:AF:SS:ID   0.00998626:0.0185456:0.228954:0.133888:10815:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0339344    ES:SE:LP:AF:SS:ID   -0.0671453:0.0353551:1.23981:0.0339344:10815:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.865314 ES:SE:LP:AF:SS:ID   -0.00900436:0.0184772:0.203398:0.865314:10815:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.865404 ES:SE:LP:AF:SS:ID   -0.0092955:0.0184883:0.211033:0.865404:10815:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.865306 ES:SE:LP:AF:SS:ID   -0.00893847:0.0184771:0.201649:0.865306:10815:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00542855   ES:SE:LP:AF:SS:ID   -0.0298104:0.0934884:0.125035:0.00542855:10815:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00539973   ES:SE:LP:AF:SS:ID   -0.0300194:0.0936866:0.125719:0.00539973:10815:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00501482   ES:SE:LP:AF:SS:ID   -0.0544458:0.0971971:0.240043:0.00501482:10815:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.865224 ES:SE:LP:AF:SS:ID   -0.00903729:0.0184323:0.204861:0.865224:10815:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.131317 ES:SE:LP:AF:SS:ID   0.00911007:0.0187926:0.202144:0.131317:10815:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.86491  ES:SE:LP:AF:SS:ID   -0.00827705:0.0183978:0.185223:0.86491:10815:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.864135 ES:SE:LP:AF:SS:ID   -0.00761915:0.0183869:0.168383:0.864135:10815:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.865064 ES:SE:LP:AF:SS:ID   -0.00893845:0.0184129:0.202476:0.865064:10815:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86507  ES:SE:LP:AF:SS:ID   -0.00891894:0.0184143:0.201939:0.86507:10815:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.865071 ES:SE:LP:AF:SS:ID   -0.00894184:0.0184141:0.202551:0.865071:10815:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.865448 ES:SE:LP:AF:SS:ID   -0.00950353:0.0184614:0.217013:0.865448:10815:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.102327 ES:SE:LP:AF:SS:ID   0.0133534:0.0215293:0.271556:0.102327:10815:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00565844   ES:SE:LP:AF:SS:ID   -0.101647:0.0907409:0.580606:0.00565844:10815:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.869225 ES:SE:LP:AF:SS:ID   -0.00789847:0.018706:0.172077:0.869225:10815:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.85924  ES:SE:LP:AF:SS:ID   -0.00217009:0.0183994:0.0428172:0.85924:10815:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.864122 ES:SE:LP:AF:SS:ID   -0.0100184:0.018542:0.229888:0.864122:10815:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86123  ES:SE:LP:AF:SS:ID   -0.00506548:0.0185426:0.105286:0.86123:10815:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.103685 ES:SE:LP:AF:SS:ID   0.00977681:0.0221053:0.18158:0.103685:10815:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.866608 ES:SE:LP:AF:SS:ID   -0.00535959:0.0187634:0.110609:0.866608:10815:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.866608 ES:SE:LP:AF:SS:ID   -0.00536133:0.0187633:0.11065:0.866608:10815:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.866624 ES:SE:LP:AF:SS:ID   -0.00530537:0.0187634:0.109371:0.866624:10815:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.866867 ES:SE:LP:AF:SS:ID   -0.00562412:0.0187688:0.116652:0.866867:10815:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.13091  ES:SE:LP:AF:SS:ID   0.00814727:0.0187757:0.177602:0.13091:10815:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.108113 ES:SE:LP:AF:SS:ID   -0.0020977:0.0206094:0.0367176:0.108113:10815:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.8518   ES:SE:LP:AF:SS:ID   -0.0044149:0.0184926:0.0908121:0.8518:10815:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00196858   ES:SE:LP:AF:SS:ID   0.182749:0.150302:0.64964:0.00196858:10815:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838913 ES:SE:LP:AF:SS:ID   0.0190151:0.0184926:0.517334:0.838913:10815:rs376645387