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-30740_irnt/ukb-d-30740_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-30740_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 15:34:25 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30740_irnt/ukb-d-30740_irnt.vcf.gz ...
Read summary statistics for 13585278 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, 1283502 SNPs remain.
After merging with regression SNP LD, 1283502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0785 (0.0127)
Lambda GC: 1.2915
Mean Chi^2: 1.5276
Intercept: 1.0492 (0.0109)
Ratio: 0.0932 (0.0207)
Analysis finished at Mon Nov 25 15:36:48 2019
Total time elapsed: 2.0m:22.07s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.1866,
    "mean_EFFECT": 0,
    "n": 314916,
    "n_snps": 13585278,
    "n_clumped_hits": 109,
    "n_p_sig": 9535,
    "n_mono": 0,
    "n_ns": 1251740,
    "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": 568968,
    "n_est": 316137.5341,
    "ratio_se_n": 1.0019,
    "mean_diff": -1.7806e-06,
    "ratio_diff": 0.8782,
    "sd_y_est1": 0.9896,
    "sd_y_est2": 0.9915,
    "r2_sum1": 0.0342,
    "r2_sum2": 0.0349,
    "r2_sum3": 0.0348,
    "r2_sum4": 0.0349,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.0785,
    "ldsc_observed_scale_h2_se": 0.0127,
    "ldsc_intercept_beta": 1.0492,
    "ldsc_intercept_se": 0.0109,
    "ldsc_lambda_gc": 1.2915,
    "ldsc_mean_chisq": 1.5276,
    "ldsc_ratio": 0.0933
}

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 13573231 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57080 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33334 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051272e+00 6.184943e+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 7.902528e+07 5.591529e+07 3.02000e+02 3.293031e+07 7.013866e+07 1.148601e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.880000e-05 1.492610e-02 -2.79160e-01 -4.259100e-03 1.220000e-05 4.303100e-03 1.896300e-01 ▁▁▇▅▁
numeric SE 0 1.0000000 NA NA NA NA NA 1.047620e-02 1.010520e-02 2.04760e-03 2.983200e-03 5.496600e-03 1.505400e-02 5.094800e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.720648e-01 2.968077e-01 0.00000e+00 2.081000e-01 4.625003e-01 7.293601e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.720643e-01 2.968080e-01 0.00000e+00 2.081017e-01 4.625000e-01 7.293583e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA 1.908202e-01 2.544079e-01 1.00000e-03 7.434100e-03 6.004350e-02 2.953400e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 568968 0.9581188 NA NA NA NA NA 1.963465e-01 2.471050e-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 3.149160e+05 0.000000e+00 3.14916e+05 3.149160e+05 3.149160e+05 3.149160e+05 3.149160e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0023337 0.0043672 0.5930796 0.5930857 0.1105400 0.1894970 314916
1 693731 rs12238997 A G 0.0002258 0.0041254 0.9563400 0.9563445 0.1158600 0.1417730 314916
1 707522 rs371890604 G C 0.0002690 0.0046419 0.9537901 0.9537933 0.0972190 0.1293930 314916
1 717587 rs144155419 G A 0.0035628 0.0110530 0.7472106 0.7471968 0.0157110 0.0045926 314916
1 723329 rs189787166 A T 0.0237310 0.0326500 0.4673400 0.4673301 0.0017334 0.0003994 314916
1 730087 rs148120343 T C -0.0066410 0.0057472 0.2478803 0.2478779 0.0564710 0.0127796 314916
1 731718 rs142557973 T C -0.0000082 0.0039132 0.9983400 0.9983365 0.1217400 0.1543530 314916
1 732032 rs61770163 A C -0.0005332 0.0041763 0.8984200 0.8984174 0.1210900 0.1555510 314916
1 734349 rs141242758 T C 0.0000902 0.0039153 0.9816100 0.9816138 0.1209600 0.1525560 314916
1 740284 rs61770167 C T 0.0390450 0.0179540 0.0296469 0.0296508 0.0057537 0.0023962 314916
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0001944 0.0045184 0.9656799 0.9656753 0.056103 0.0309934 314916
23 154923374 rs111332691 T A 0.0130120 0.0049466 0.0085249 0.0085261 0.044977 0.0116556 314916
23 154925045 rs509981 C T -0.0040051 0.0023874 0.0934243 0.0934254 0.245750 0.3634440 314916
23 154925895 rs538470 C T -0.0041541 0.0024422 0.0889447 0.0889493 0.242050 0.3634440 314916
23 154927581 rs644138 G A -0.0032497 0.0022455 0.1478301 0.1478394 0.302240 0.4635760 314916
23 154929412 rs557132 C T -0.0038321 0.0023881 0.1085700 0.1085676 0.245600 0.3568210 314916
23 154929637 rs35185538 CT C -0.0028998 0.0024920 0.2445699 0.2445685 0.229980 0.3011920 314916
23 154929952 rs4012982 CAA C -0.0039719 0.0025114 0.1137601 0.1137528 0.239540 0.3165560 314916
23 154930230 rs781880 A G -0.0039310 0.0023878 0.0997057 0.0997050 0.245980 0.3618540 314916
23 154930487 rs781879 T A -0.0004365 0.0082058 0.9575801 0.9575773 0.019473 0.1263580 314916

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11054  ES:SE:LP:AF:SS:ID   -0.0023337:0.0043672:0.226887:0.11054:314916:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11586  ES:SE:LP:AF:SS:ID   0.00022583:0.0041254:0.0193877:0.11586:314916:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097219 ES:SE:LP:AF:SS:ID   0.00026897:0.0046419:0.0205472:0.097219:314916:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015711 ES:SE:LP:AF:SS:ID   0.0035628:0.011053:0.126557:0.015711:314916:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017334    ES:SE:LP:AF:SS:ID   0.023731:0.03265:0.330367:0.0017334:314916:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056471 ES:SE:LP:AF:SS:ID   -0.006641:0.0057472:0.605758:0.056471:314916:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12174  ES:SE:LP:AF:SS:ID   -8.1587e-06:0.0039132:0.000721528:0.12174:314916:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12109  ES:SE:LP:AF:SS:ID   -0.00053315:0.0041763:0.0465206:0.12109:314916:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12096  ES:SE:LP:AF:SS:ID   9.0231e-05:0.0039153:0.00806103:0.12096:314916:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057537    ES:SE:LP:AF:SS:ID   0.039045:0.017954:1.52802:0.0057537:314916:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.001856 ES:SE:LP:AF:SS:ID   -0.015483:0.034074:0.187381:0.001856:314916:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.86974  ES:SE:LP:AF:SS:ID   0.0022135:0.0038601:0.246915:0.86974:314916:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015168    ES:SE:LP:AF:SS:ID   -0.00077514:0.035108:0.00771607:0.0015168:314916:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12292  ES:SE:LP:AF:SS:ID   -0.0016678:0.0038232:0.178703:0.12292:314916:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14274  ES:SE:LP:AF:SS:ID   -0.0016929:0.0037781:0.184349:0.14274:314916:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12304  ES:SE:LP:AF:SS:ID   -0.0016402:0.0038178:0.175568:0.12304:314916:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87096  ES:SE:LP:AF:SS:ID   0.0013261:0.0037213:0.141722:0.87096:314916:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87548  ES:SE:LP:AF:SS:ID   0.0014337:0.003782:0.152045:0.87548:314916:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12859  ES:SE:LP:AF:SS:ID   -0.0018838:0.0037302:0.21215:0.12859:314916:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036307 ES:SE:LP:AF:SS:ID   -0.010224:0.0067709:0.882563:0.036307:314916:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   0.0015384:0.0037173:0.168137:0.87054:314916:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   0.0018563:0.0037191:0.209222:0.87066:314916:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87054  ES:SE:LP:AF:SS:ID   0.0015296:0.0037171:0.167038:0.87054:314916:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.0050287    ES:SE:LP:AF:SS:ID   -0.023475:0.019088:0.660012:0.0050287:314916:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0049954    ES:SE:LP:AF:SS:ID   -0.024172:0.01914:0.684807:0.0049954:314916:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055197    ES:SE:LP:AF:SS:ID   -0.00010088:0.018587:0.00188458:0.0055197:314916:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   0.0011626:0.003711:0.122588:0.87064:314916:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12593  ES:SE:LP:AF:SS:ID   -0.0016899:0.0037859:0.18354:0.12593:314916:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87021  ES:SE:LP:AF:SS:ID   0.0011814:0.0037021:0.125153:0.87021:314916:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86948  ES:SE:LP:AF:SS:ID   0.0011639:0.0036988:0.123193:0.86948:314916:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87035  ES:SE:LP:AF:SS:ID   0.0010903:0.0037052:0.114322:0.87035:314916:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   0.0010932:0.0037055:0.11465:0.87036:314916:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   0.0010875:0.0037056:0.113983:0.87037:314916:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87081  ES:SE:LP:AF:SS:ID   0.0011043:0.003715:0.115618:0.87081:314916:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.09881  ES:SE:LP:AF:SS:ID   -0.0019741:0.0043174:0.18876:0.09881:314916:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064013    ES:SE:LP:AF:SS:ID   0.0067718:0.016798:0.163132:0.0064013:314916:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.87466  ES:SE:LP:AF:SS:ID   0.0018119:0.0037694:0.20015:0.87466:314916:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86409  ES:SE:LP:AF:SS:ID   0.0023969:0.0036976:0.286652:0.86409:314916:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86948  ES:SE:LP:AF:SS:ID   0.0017919:0.0037327:0.19984:0.86948:314916:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86643  ES:SE:LP:AF:SS:ID   0.00082454:0.0037335:0.0834355:0.86643:314916:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098807 ES:SE:LP:AF:SS:ID   -0.0021224:0.0044677:0.197397:0.098807:314916:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87159  ES:SE:LP:AF:SS:ID   0.0016683:0.0037758:0.181378:0.87159:314916:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87159  ES:SE:LP:AF:SS:ID   0.0016686:0.0037758:0.181411:0.87159:314916:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87159  ES:SE:LP:AF:SS:ID   0.0016647:0.0037758:0.18091:0.87159:314916:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87195  ES:SE:LP:AF:SS:ID   0.0018891:0.0037779:0.20968:0.87195:314916:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12555  ES:SE:LP:AF:SS:ID   -0.0014661:0.0037807:0.156033:0.12555:314916:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10538  ES:SE:LP:AF:SS:ID   -0.0001856:0.004118:0.0159004:0.10538:314916:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85543  ES:SE:LP:AF:SS:ID   0.0032921:0.003696:0.428198:0.85543:314916:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016514    ES:SE:LP:AF:SS:ID   0.012022:0.03274:0.146624:0.0016514:314916:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83823  ES:SE:LP:AF:SS:ID   -0.0018109:0.0036358:0.208702:0.83823:314916:rs376645387