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-30780_irnt/ukb-d-30780_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-30780_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 14:55:08 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30780_irnt/ukb-d-30780_irnt.vcf.gz ...
Read summary statistics for 13586015 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, 1283503 SNPs remain.
After merging with regression SNP LD, 1283503 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1116 (0.0228)
Lambda GC: 1.2864
Mean Chi^2: 1.7577
Intercept: 1.07 (0.0164)
Ratio: 0.0924 (0.0217)
Analysis finished at Mon Nov 25 14:57:27 2019
Total time elapsed: 2.0m:19.37s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.186,
    "mean_EFFECT": 6.747e-06,
    "n": 343621,
    "n_snps": 13586015,
    "n_clumped_hits": 165,
    "n_p_sig": 32244,
    "n_mono": 0,
    "n_ns": 1251782,
    "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": 569185,
    "n_est": 344946.0459,
    "ratio_se_n": 1.0019,
    "mean_diff": 2.2885e-08,
    "ratio_diff": 0.2135,
    "sd_y_est1": 0.9792,
    "sd_y_est2": 0.9811,
    "r2_sum1": 0.0609,
    "r2_sum2": 0.0635,
    "r2_sum3": 0.0633,
    "r2_sum4": 0.0625,
    "ldsc_nsnp_merge_refpanel_ld": 1283503,
    "ldsc_nsnp_merge_regression_ld": 1283503,
    "ldsc_observed_scale_h2_beta": 0.1116,
    "ldsc_observed_scale_h2_se": 0.0228,
    "ldsc_intercept_beta": 1.07,
    "ldsc_intercept_se": 0.0164,
    "ldsc_lambda_gc": 1.2864,
    "ldsc_mean_chisq": 1.7577,
    "ldsc_ratio": 0.0924
}
 

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 TRUE
n_p_sig TRUE
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 13573968 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57083 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 9.051258e+00 6.184972e+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 7.902571e+07 5.591512e+07 3.02000e+02 3.293113e+07 7.013918e+07 1.148605e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 6.700000e-06 1.436830e-02 -4.88230e-01 -4.075300e-03 1.400000e-06 4.075400e-03 3.035600e-01 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.925600e-03 9.574400e-03 1.94210e-03 2.826000e-03 5.207500e-03 1.426400e-02 4.838600e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.712606e-01 2.977119e-01 0.00000e+00 2.066798e-01 4.626100e-01 7.291603e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.712601e-01 2.977122e-01 0.00000e+00 2.066809e-01 4.626152e-01 7.291621e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908098e-01 2.544046e-01 1.00000e-03 7.431600e-03 6.003800e-02 2.953200e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 569185 0.9581051 NA NA NA NA NA 1.963395e-01 2.471028e-01 0.00000e+00 5.591000e-03 8.426520e-02 3.081070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 3.436210e+05 0.000000e+00 3.43621e+05 3.436210e+05 3.436210e+05 3.436210e+05 3.436210e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0045811 0.0041373 0.2681798 0.2681781 0.1105300 0.1894970 343621
1 693731 rs12238997 A G -0.0041109 0.0039073 0.2927602 0.2927502 0.1158200 0.1417730 343621
1 707522 rs371890604 G C -0.0056135 0.0043950 0.2015199 0.2015151 0.0972460 0.1293930 343621
1 717587 rs144155419 G A -0.0088776 0.0104880 0.3973095 0.3973000 0.0156720 0.0045926 343621
1 723329 rs189787166 A T -0.0017014 0.0309110 0.9561101 0.9561051 0.0017356 0.0003994 343621
1 730087 rs148120343 T C -0.0067022 0.0054459 0.2184399 0.2184398 0.0564230 0.0127796 343621
1 731718 rs142557973 T C -0.0049274 0.0037060 0.1836699 0.1836588 0.1217000 0.1543530 343621
1 732032 rs61770163 A C -0.0050596 0.0039545 0.2007299 0.2007373 0.1211100 0.1555510 343621
1 734349 rs141242758 T C -0.0047717 0.0037080 0.1981500 0.1981409 0.1209300 0.1525560 343621
1 740284 rs61770167 C T 0.0192450 0.0170020 0.2576802 0.2576657 0.0057596 0.0023962 343621
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0033727 0.0042828 0.4309997 0.4309899 0.056186 0.0309934 343621
23 154923374 rs111332691 T A -0.0001964 0.0047017 0.9666799 0.9666787 0.044866 0.0116556 343621
23 154925045 rs509981 C T 0.0015579 0.0022646 0.4914904 0.4914930 0.245650 0.3634440 343621
23 154925895 rs538470 C T 0.0017996 0.0023165 0.4372502 0.4372404 0.241990 0.3634440 343621
23 154927581 rs644138 G A 0.0004155 0.0021297 0.8453300 0.8453237 0.302220 0.4635760 343621
23 154929412 rs557132 C T 0.0015023 0.0022652 0.5071997 0.5071970 0.245510 0.3568210 343621
23 154929637 rs35185538 CT C 0.0002404 0.0023643 0.9190000 0.9190013 0.229760 0.3011920 343621
23 154929952 rs4012982 CAA C 0.0017873 0.0023823 0.4531104 0.4531094 0.239480 0.3165560 343621
23 154930230 rs781880 A G 0.0013805 0.0022649 0.5421906 0.5421804 0.245910 0.3618540 343621
23 154930487 rs781879 T A -0.0017117 0.0077659 0.8255500 0.8255501 0.019553 0.1263580 343621

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11053  ES:SE:LP:AF:SS:ID   -0.0045811:0.0041373:0.571574:0.11053:343621:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11582  ES:SE:LP:AF:SS:ID   -0.0041109:0.0039073:0.533488:0.11582:343621:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097246 ES:SE:LP:AF:SS:ID   -0.0056135:0.004395:0.695682:0.097246:343621:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015672 ES:SE:LP:AF:SS:ID   -0.0088776:0.010488:0.400871:0.015672:343621:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017356    ES:SE:LP:AF:SS:ID   -0.0017014:0.030911:0.0194921:0.0017356:343621:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056423 ES:SE:LP:AF:SS:ID   -0.0067022:0.0054459:0.660668:0.056423:343621:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.1217   ES:SE:LP:AF:SS:ID   -0.0049274:0.003706:0.735962:0.1217:343621:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12111  ES:SE:LP:AF:SS:ID   -0.0050596:0.0039545:0.697388:0.12111:343621:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12093  ES:SE:LP:AF:SS:ID   -0.0047717:0.003708:0.703006:0.12093:343621:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057596    ES:SE:LP:AF:SS:ID   0.019245:0.017002:0.588919:0.0057596:343621:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.0018602    ES:SE:LP:AF:SS:ID   0.059844:0.032254:1.19694:0.0018602:343621:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86979  ES:SE:LP:AF:SS:ID   0.0027671:0.0036557:0.347667:0.86979:343621:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015213    ES:SE:LP:AF:SS:ID   -0.012723:0.033209:0.153886:0.0015213:343621:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12289  ES:SE:LP:AF:SS:ID   -0.0037448:0.0036202:0.521535:0.12289:343621:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14271  ES:SE:LP:AF:SS:ID   -0.003659:0.0035781:0.513584:0.14271:343621:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12301  ES:SE:LP:AF:SS:ID   -0.0035182:0.0036151:0.480894:0.12301:343621:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87095  ES:SE:LP:AF:SS:ID   0.002915:0.0035234:0.389287:0.87095:343621:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87551  ES:SE:LP:AF:SS:ID   0.0027788:0.0035813:0.358734:0.87551:343621:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12859  ES:SE:LP:AF:SS:ID   -0.0039921:0.0035321:0.587741:0.12859:343621:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036307 ES:SE:LP:AF:SS:ID   -0.0021477:0.0064137:0.132103:0.036307:343621:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   0.0032638:0.0035198:0.451267:0.87054:343621:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87065  ES:SE:LP:AF:SS:ID   0.0033093:0.0035214:0.459245:0.87065:343621:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   0.0032978:0.0035196:0.457461:0.87054:343621:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050508    ES:SE:LP:AF:SS:ID   -0.0054515:0.018051:0.11768:0.0050508:343621:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050177    ES:SE:LP:AF:SS:ID   -0.0049929:0.018099:0.106432:0.0050177:343621:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055474    ES:SE:LP:AF:SS:ID   0.035843:0.017566:1.38402:0.0055474:343621:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87063  ES:SE:LP:AF:SS:ID   0.0030262:0.0035136:0.409961:0.87063:343621:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12593  ES:SE:LP:AF:SS:ID   -0.0037467:0.0035848:0.528767:0.12593:343621:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.8702   ES:SE:LP:AF:SS:ID   0.0031488:0.0035052:0.43295:0.8702:343621:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86948  ES:SE:LP:AF:SS:ID   0.0036701:0.003502:0.530723:0.86948:343621:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87035  ES:SE:LP:AF:SS:ID   0.0031961:0.0035081:0.44098:0.87035:343621:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87035  ES:SE:LP:AF:SS:ID   0.0031923:0.0035084:0.440249:0.87035:343621:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   0.0032223:0.0035085:0.44562:0.87036:343621:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8708   ES:SE:LP:AF:SS:ID   0.0031307:0.0035174:0.427791:0.8708:343621:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.09879  ES:SE:LP:AF:SS:ID   -0.0036803:0.0040878:0.434199:0.09879:343621:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.006434 ES:SE:LP:AF:SS:ID   0.025411:0.015869:0.96134:0.006434:343621:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87469  ES:SE:LP:AF:SS:ID   0.0029577:0.0035695:0.390043:0.87469:343621:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.8641   ES:SE:LP:AF:SS:ID   0.0034982:0.0035011:0.497942:0.8641:343621:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86949  ES:SE:LP:AF:SS:ID   0.0035117:0.0035345:0.49424:0.86949:343621:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86643  ES:SE:LP:AF:SS:ID   0.0031084:0.0035352:0.421063:0.86643:343621:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098765 ES:SE:LP:AF:SS:ID   -0.0038633:0.0042317:0.442168:0.098765:343621:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.0031326:0.0035756:0.419098:0.87161:343621:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   0.003133:0.0035756:0.419166:0.87161:343621:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.8716   ES:SE:LP:AF:SS:ID   0.0031363:0.0035757:0.419725:0.8716:343621:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87198  ES:SE:LP:AF:SS:ID   0.0031102:0.0035777:0.414923:0.87198:343621:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12553  ES:SE:LP:AF:SS:ID   -0.0040061:0.0035802:0.57978:0.12553:343621:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10539  ES:SE:LP:AF:SS:ID   -0.0040647:0.0038985:0.527068:0.10539:343621:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85544  ES:SE:LP:AF:SS:ID   0.0030734:0.0034996:0.420411:0.85544:343621:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016544    ES:SE:LP:AF:SS:ID   0.010068:0.030989:0.127686:0.0016544:343621:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83824  ES:SE:LP:AF:SS:ID   0.00063091:0.0034458:0.0681761:0.83824:343621:rs376645387