Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_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-1538_0/ukb-d-1538_0.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-1538_0/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 16:53:15 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-1538_0/ukb-d-1538_0.vcf.gz ...
Read summary statistics for 13586568 SNPs.
Dropped 12711 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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0384 (0.0023)
Lambda GC: 1.2423
Mean Chi^2: 1.2827
Intercept: 1.018 (0.0084)
Ratio: 0.0637 (0.0299)
Analysis finished at Mon Nov 25 16:55:33 2019
Total time elapsed: 2.0m:18.78s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1455,
    "mean_EFFECT": -0,
    "n": 360294,
    "n_snps": 13586568,
    "n_clumped_hits": 11,
    "n_p_sig": 413,
    "n_mono": 0,
    "n_ns": 1251802,
    "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": 569298,
    "n_est": 361676.2897,
    "ratio_se_n": 1.0019,
    "mean_diff": -0,
    "ratio_diff": 59.3109,
    "sd_y_est1": 0.4878,
    "sd_y_est2": 0.4887,
    "r2_sum1": 0.0003,
    "r2_sum2": 0.0012,
    "r2_sum3": 0.0012,
    "r2_sum4": 0.0012,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.0384,
    "ldsc_observed_scale_h2_se": 0.0023,
    "ldsc_intercept_beta": 1.018,
    "ldsc_intercept_se": 0.0084,
    "ldsc_lambda_gc": 1.2423,
    "ldsc_mean_chisq": 1.2827,
    "ldsc_ratio": 0.0637
}

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 13574521 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57084 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33337 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051328e+00 6.184966e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 <U+2587><U+2585><U+2585><U+2582><U+2582>
numeric POS 0 1.0000000 NA NA NA NA NA 7.902497e+07 5.591474e+07 3.02000e+02 3.293093e+07 7.013838e+07 1.148587e+08 2.492309e+08 <U+2587><U+2586><U+2585><U+2582><U+2581>
numeric EFFECT 0 1.0000000 NA NA NA NA NA -3.970000e-05 6.800800e-03 -8.74165e-02 -1.960800e-03 -2.020000e-05 1.903900e-03 8.199030e-02 <U+2581><U+2581><U+2587><U+2581><U+2581>
numeric SE 0 1.0000000 NA NA NA NA NA 4.829300e-03 4.658500e-03 9.44800e-04 1.374800e-03 2.533600e-03 6.940200e-03 2.342550e-02 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.775753e-01 2.953015e-01 0.00000e+00 2.157839e-01 4.703628e-01 7.335555e-01 1.000000e+00 <U+2587><U+2587><U+2586><U+2586><U+2586>
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.775749e-01 2.953018e-01 0.00000e+00 2.157832e-01 4.703622e-01 7.335558e-01 9.999996e-01 <U+2587><U+2587><U+2586><U+2586><U+2586>
numeric AF 0 1.0000000 NA NA NA NA NA 1.908019e-01 2.544021e-01 1.00000e-03 7.428900e-03 6.002970e-02 2.953050e-01 9.989990e-01 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric AF_reference 569298 0.9580985 NA NA NA NA NA 1.963333e-01 2.471007e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric N 0 1.0000000 NA NA NA NA NA 3.602940e+05 0.000000e+00 3.60294e+05 3.602940e+05 3.602940e+05 3.602940e+05 3.602940e+05 <U+2581><U+2581><U+2587><U+2581><U+2581>

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0033475 0.0020127 0.0962676 0.0962684 0.1106260 0.1894970 360294
1 693731 rs12238997 A G -0.0042509 0.0019016 0.0253887 0.0253876 0.1158160 0.1417730 360294
1 707522 rs371890604 G C -0.0023639 0.0021380 0.2688710 0.2688697 0.0972904 0.1293930 360294
1 717587 rs144155419 G A -0.0086015 0.0051014 0.0917783 0.0917766 0.0156859 0.0045926 360294
1 723329 rs189787166 A T 0.0274467 0.0150437 0.0680832 0.0680818 0.0017348 0.0003994 360294
1 730087 rs148120343 T C -0.0039099 0.0026492 0.1399781 0.1399778 0.0564633 0.0127796 360294
1 731718 rs142557973 T C -0.0034289 0.0018035 0.0572704 0.0572697 0.1217220 0.1543530 360294
1 732032 rs61770163 A C -0.0029603 0.0019238 0.1238660 0.1238646 0.1211580 0.1555510 360294
1 734349 rs141242758 T C -0.0034808 0.0018044 0.0537292 0.0537277 0.1209490 0.1525560 360294
1 740284 rs61770167 C T 0.0079362 0.0082532 0.3362598 0.3362589 0.0057877 0.0023962 360294
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0018514 0.0020832 0.3741623 0.3741614 0.0561742 0.0309934 360294
23 154923374 rs111332691 T A -0.0005989 0.0022895 0.7936226 0.7936232 0.0447940 0.0116556 360294
23 154925045 rs509981 C T 0.0009388 0.0011017 0.3941178 0.3941186 0.2455970 0.3634440 360294
23 154925895 rs538470 C T 0.0013018 0.0011270 0.2480539 0.2480548 0.2419100 0.3634440 360294
23 154927581 rs644138 G A 0.0012348 0.0010361 0.2333302 0.2333307 0.3021590 0.4635760 360294
23 154929412 rs557132 C T 0.0009097 0.0011020 0.4090751 0.4090741 0.2454490 0.3568210 360294
23 154929637 rs35185538 CT C 0.0012018 0.0011501 0.2960547 0.2960535 0.2296860 0.3011920 360294
23 154929952 rs4012982 CAA C 0.0009415 0.0011591 0.4166122 0.4166129 0.2394100 0.3165560 360294
23 154930230 rs781880 A G 0.0009768 0.0011018 0.3753470 0.3753448 0.2458580 0.3618540 360294
23 154930487 rs781879 T A -0.0073414 0.0037804 0.0521411 0.0521402 0.0195564 0.1263580 360294

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.110626 ES:SE:LP:AF:SS:ID   -0.00334753:0.00201268:1.01652:0.110626:360294:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.115816 ES:SE:LP:AF:SS:ID   -0.00425087:0.00190157:1.59536:0.115816:360294:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0972904    ES:SE:LP:AF:SS:ID   -0.00236391:0.00213799:0.570456:0.0972904:360294:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0156859    ES:SE:LP:AF:SS:ID   -0.00860152:0.00510143:1.03726:0.0156859:360294:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00173485   ES:SE:LP:AF:SS:ID   0.0274467:0.0150437:1.16696:0.00173485:360294:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0564633    ES:SE:LP:AF:SS:ID   -0.00390987:0.00264919:0.85394:0.0564633:360294:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.121722 ES:SE:LP:AF:SS:ID   -0.00342886:0.00180348:1.24207:0.121722:360294:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121158 ES:SE:LP:AF:SS:ID   -0.00296033:0.00192385:0.907048:0.121158:360294:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.120949 ES:SE:LP:AF:SS:ID   -0.00348081:0.00180444:1.26979:0.120949:360294:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00578766   ES:SE:LP:AF:SS:ID   0.00793617:0.00825323:0.473325:0.00578766:360294:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00187451   ES:SE:LP:AF:SS:ID   0.00105787:0.0156103:0.0241222:0.00187451:360294:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86976  ES:SE:LP:AF:SS:ID   0.00318745:0.00177892:1.13568:0.86976:360294:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00152812   ES:SE:LP:AF:SS:ID   0.0176499:0.0161184:0.56303:0.00152812:360294:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.122907 ES:SE:LP:AF:SS:ID   -0.00312809:0.00176177:1.12027:0.122907:360294:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.142703 ES:SE:LP:AF:SS:ID   -0.00303071:0.00174142:1.08727:0.142703:360294:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123023 ES:SE:LP:AF:SS:ID   -0.00312521:0.00175932:1.12107:0.123023:360294:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.870904 ES:SE:LP:AF:SS:ID   0.00257533:0.00171446:0.875933:0.870904:360294:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.875481 ES:SE:LP:AF:SS:ID   0.00313214:0.00174285:1.14078:0.875481:360294:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.128619 ES:SE:LP:AF:SS:ID   -0.00270131:0.00171871:0.935471:0.128619:360294:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0363703    ES:SE:LP:AF:SS:ID   0.00493266:0.00311776:0.94453:0.0363703:360294:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.870499 ES:SE:LP:AF:SS:ID   0.00266133:0.00171268:0.920059:0.870499:360294:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870604 ES:SE:LP:AF:SS:ID   0.00261672:0.00171347:0.897141:0.870604:360294:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870496 ES:SE:LP:AF:SS:ID   0.0026795:0.00171262:0.929272:0.870496:360294:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00504167   ES:SE:LP:AF:SS:ID   0.0035184:0.00879398:0.161725:0.00504167:360294:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00500863   ES:SE:LP:AF:SS:ID   0.00342305:0.00881753:0.156231:0.00500863:360294:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558826   ES:SE:LP:AF:SS:ID   -0.00768176:0.0085132:0.435477:0.00558826:360294:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.870578 ES:SE:LP:AF:SS:ID   0.00257814:0.00170961:0.880912:0.870578:360294:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.125973 ES:SE:LP:AF:SS:ID   -0.00278104:0.00174437:0.955182:0.125973:360294:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.870141 ES:SE:LP:AF:SS:ID   0.00264645:0.00170549:0.918188:0.870141:360294:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.869429 ES:SE:LP:AF:SS:ID   0.00284868:0.00170394:1.02429:0.869429:360294:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.870295 ES:SE:LP:AF:SS:ID   0.0026596:0.00170696:0.923673:0.870295:360294:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.870301 ES:SE:LP:AF:SS:ID   0.00265805:0.00170708:0.922796:0.870301:360294:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87031  ES:SE:LP:AF:SS:ID   0.00264374:0.00170714:0.915535:0.87031:360294:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870754 ES:SE:LP:AF:SS:ID   0.002617:0.00171149:0.898782:0.870754:360294:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0988389    ES:SE:LP:AF:SS:ID   -0.00225219:0.00198888:0.589268:0.0988389:360294:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00647783   ES:SE:LP:AF:SS:ID   -0.0095102:0.00769137:0.66498:0.00647783:360294:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.874646 ES:SE:LP:AF:SS:ID   0.00295328:0.00173696:1.0502:0.874646:360294:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.864042 ES:SE:LP:AF:SS:ID   0.00223937:0.00170337:0.72441:0.864042:360294:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.869437 ES:SE:LP:AF:SS:ID   0.00272156:0.00171987:0.944794:0.869437:360294:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86638  ES:SE:LP:AF:SS:ID   0.00290539:0.0017202:1.03989:0.86638:360294:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0987644    ES:SE:LP:AF:SS:ID   -0.00282835:0.00205953:0.770418:0.0987644:360294:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.871565 ES:SE:LP:AF:SS:ID   0.00279006:0.00173982:0.963399:0.871565:360294:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.871565 ES:SE:LP:AF:SS:ID   0.00279012:0.00173982:0.963431:0.871565:360294:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.871564 ES:SE:LP:AF:SS:ID   0.00279636:0.00173985:0.966564:0.871564:360294:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871939 ES:SE:LP:AF:SS:ID   0.00285954:0.00174085:0.99799:0.871939:360294:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.125553 ES:SE:LP:AF:SS:ID   -0.00290449:0.00174218:1.02007:0.125553:360294:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10542  ES:SE:LP:AF:SS:ID   -0.00252331:0.0018967:0.736605:0.10542:360294:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.855389 ES:SE:LP:AF:SS:ID   0.00233728:0.00170266:0.76996:0.855389:360294:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00165572   ES:SE:LP:AF:SS:ID   0.0256941:0.0150761:1.05391:0.00165572:360294:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.838365 ES:SE:LP:AF:SS:ID   0.0025507:0.00167751:0.891506:0.838365:360294:rs376645387