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-22604_2/ukb-d-22604_2.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-22604_2/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 16:38:42 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22604_2/ukb-d-22604_2.vcf.gz ...
Read summary statistics for 13563393 SNPs.
Dropped 12678 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, 1283500 SNPs remain.
After merging with regression SNP LD, 1283500 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0078 (0.0057)
Lambda GC: 1.0258
Mean Chi^2: 1.0202
Intercept: 1.0083 (0.0062)
Ratio: 0.4108 (0.3055)
Analysis finished at Mon Nov 25 16:40:59 2019
Total time elapsed: 2.0m:17.43s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0158,
    "mean_EFFECT": 1.3977e-06,
    "n": 75177,
    "n_snps": 13563393,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 1251060,
    "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": 562172,
    "n_est": 75447.5075,
    "ratio_se_n": 1.0018,
    "mean_diff": 2.7639e-06,
    "ratio_diff": 4.8318,
    "sd_y_est1": 0.3887,
    "sd_y_est2": 0.3894,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1283500,
    "ldsc_nsnp_merge_regression_ld": 1283500,
    "ldsc_observed_scale_h2_beta": 0.0078,
    "ldsc_observed_scale_h2_se": 0.0057,
    "ldsc_intercept_beta": 1.0083,
    "ldsc_intercept_se": 0.0062,
    "ldsc_lambda_gc": 1.0258,
    "ldsc_mean_chisq": 1.0202,
    "ldsc_ratio": 0.4109
}

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 13551378 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57038 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33329 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051500e+00 6.185025e+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 7.902521e+07 5.591715e+07 3.02000e+02 3.292786e+07 7.013476e+07 1.148632e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 1.400000e-06 1.164590e-02 -1.61658e-01 -3.123000e-03 -1.330000e-05 3.080300e-03 1.620940e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.385300e-03 8.079400e-03 1.66580e-03 2.397000e-03 4.407100e-03 1.203790e-02 4.075250e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.978823e-01 2.887842e-01 2.00000e-07 2.476242e-01 4.966232e-01 7.478733e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.978801e-01 2.887855e-01 2.00000e-07 2.476201e-01 4.966208e-01 7.478735e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.911163e-01 2.544894e-01 1.00000e-03 7.513700e-03 6.035730e-02 2.958730e-01 9.989990e-01 ▇▂▁▁▁
numeric AF_reference 562172 0.9585523 NA NA NA NA NA 1.965590e-01 2.471553e-01 0.00000e+00 5.790700e-03 8.446490e-02 3.085060e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 7.517700e+04 0.000000e+00 7.51770e+04 7.517700e+04 7.517700e+04 7.517700e+04 7.517700e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0035262 0.0035042 0.3142831 0.3142790 0.1115640 0.1894970 75177
1 693731 rs12238997 A G -0.0014391 0.0033179 0.6644755 0.6644748 0.1164770 0.1417730 75177
1 707522 rs371890604 G C -0.0028957 0.0037291 0.4374486 0.4374467 0.0977849 0.1293930 75177
1 717587 rs144155419 G A -0.0068340 0.0088479 0.4398909 0.4398892 0.0159063 0.0045926 75177
1 723329 rs189787166 A T 0.0118168 0.0259446 0.6487763 0.6487763 0.0017753 0.0003994 75177
1 730087 rs148120343 T C -0.0007288 0.0046005 0.8741211 0.8741204 0.0569733 0.0127796 75177
1 731718 rs142557973 T C -0.0016830 0.0031474 0.5928284 0.5928286 0.1223380 0.1543530 75177
1 732032 rs61770163 A C -0.0038778 0.0033589 0.2483019 0.2482983 0.1218660 0.1555510 75177
1 734349 rs141242758 T C -0.0019755 0.0031493 0.5304653 0.5304641 0.1216090 0.1525560 75177
1 740284 rs61770167 C T 0.0089995 0.0142644 0.5281022 0.5281009 0.0058807 0.0023962 75177
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0026386 0.0037293 0.4792466 0.4792453 0.0546566 0.0309934 75177
23 154923374 rs111332691 T A 0.0036520 0.0040207 0.3637232 0.3637197 0.0450404 0.0116556 75177
23 154925045 rs509981 C T 0.0005026 0.0019450 0.7961170 0.7961154 0.2443920 0.3634440 75177
23 154925895 rs538470 C T 0.0007352 0.0019884 0.7115673 0.7115674 0.2408890 0.3634440 75177
23 154927581 rs644138 G A 0.0010502 0.0018316 0.5664036 0.5664022 0.2994310 0.4635760 75177
23 154929412 rs557132 C T 0.0004818 0.0019455 0.8044240 0.8044230 0.2442760 0.3568210 75177
23 154929637 rs35185538 CT C 0.0006145 0.0020311 0.7622563 0.7622551 0.2287170 0.3011920 75177
23 154929952 rs4012982 CAA C 0.0002035 0.0020471 0.9208261 0.9208256 0.2382650 0.3165560 75177
23 154930230 rs781880 A G 0.0005671 0.0019450 0.7706106 0.7706101 0.2447030 0.3618540 75177
23 154930487 rs781879 T A 0.0021476 0.0066089 0.7452123 0.7452123 0.0195950 0.1263580 75177

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111564 ES:SE:LP:AF:SS:ID   -0.00352623:0.00350421:0.502679:0.111564:75177:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116477 ES:SE:LP:AF:SS:ID   -0.0014391:0.00331786:0.177521:0.116477:75177:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0977849    ES:SE:LP:AF:SS:ID   -0.00289566:0.00372906:0.359073:0.0977849:75177:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0159063    ES:SE:LP:AF:SS:ID   -0.00683396:0.00884792:0.356655:0.0159063:75177:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.00177526   ES:SE:LP:AF:SS:ID   0.0118168:0.0259446:0.187905:0.00177526:75177:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0569733    ES:SE:LP:AF:SS:ID   -0.00072884:0.00460048:0.0584284:0.0569733:75177:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122338 ES:SE:LP:AF:SS:ID   -0.00168304:0.00314739:0.227071:0.122338:75177:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.121866 ES:SE:LP:AF:SS:ID   -0.00387779:0.00335887:0.60502:0.121866:75177:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121609 ES:SE:LP:AF:SS:ID   -0.00197553:0.00314927:0.275343:0.121609:75177:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00588068   ES:SE:LP:AF:SS:ID   0.00899952:0.0142644:0.277282:0.00588068:75177:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00180846   ES:SE:LP:AF:SS:ID   -0.019631:0.0277832:0.318914:0.00180846:75177:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868816 ES:SE:LP:AF:SS:ID   0.000815491:0.00309864:0.101047:0.868816:75177:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00165878   ES:SE:LP:AF:SS:ID   -0.0143298:0.0268585:0.226456:0.00165878:75177:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123758 ES:SE:LP:AF:SS:ID   -0.000972116:0.00307214:0.123968:0.123758:75177:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.143056 ES:SE:LP:AF:SS:ID   -0.0012244:0.00304385:0.162727:0.143056:75177:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.123902 ES:SE:LP:AF:SS:ID   -0.000980046:0.00306757:0.12531:0.123902:75177:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869912 ES:SE:LP:AF:SS:ID   0.00136276:0.00298909:0.18812:0.869912:75177:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874529 ES:SE:LP:AF:SS:ID   0.000840582:0.00303743:0.106804:0.874529:75177:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129553 ES:SE:LP:AF:SS:ID   -0.00103687:0.00299863:0.13697:0.129553:75177:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0360084    ES:SE:LP:AF:SS:ID   -0.0156588:0.00546116:2.38289:0.0360084:75177:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869552 ES:SE:LP:AF:SS:ID   0.00124694:0.00298669:0.169851:0.869552:75177:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869633 ES:SE:LP:AF:SS:ID   0.00113687:0.00298781:0.152691:0.869633:75177:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869547 ES:SE:LP:AF:SS:ID   0.00123558:0.00298657:0.168075:0.869547:75177:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00528791   ES:SE:LP:AF:SS:ID   -0.00452424:0.0149886:0.117606:0.00528791:75177:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00525393   ES:SE:LP:AF:SS:ID   -0.00408464:0.0150263:0.104715:0.00525393:75177:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00558736   ES:SE:LP:AF:SS:ID   -0.0252723:0.0147757:1.0595:0.00558736:75177:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869525 ES:SE:LP:AF:SS:ID   0.00112912:0.00298017:0.151947:0.869525:75177:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126948 ES:SE:LP:AF:SS:ID   -0.000731879:0.00304339:0.0915375:0.126948:75177:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.869049 ES:SE:LP:AF:SS:ID   0.000922698:0.00297261:0.12133:0.869049:75177:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868472 ES:SE:LP:AF:SS:ID   0.00100323:0.0029712:0.133342:0.868472:75177:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869198 ES:SE:LP:AF:SS:ID   0.000978375:0.00297524:0.129433:0.869198:75177:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869203 ES:SE:LP:AF:SS:ID   0.000978977:0.00297544:0.129513:0.869203:75177:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869206 ES:SE:LP:AF:SS:ID   0.000978939:0.00297547:0.129506:0.869206:75177:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869689 ES:SE:LP:AF:SS:ID   0.00096708:0.00298318:0.127375:0.869689:75177:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0991701    ES:SE:LP:AF:SS:ID   0.000134196:0.00347086:0.013605:0.0991701:75177:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.00642849   ES:SE:LP:AF:SS:ID   -0.0220124:0.0134422:0.993461:0.00642849:75177:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873648 ES:SE:LP:AF:SS:ID   0.000586586:0.00302691:0.0724551:0.873648:75177:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.863065 ES:SE:LP:AF:SS:ID   0.00187462:0.00297023:0.277405:0.863065:75177:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868456 ES:SE:LP:AF:SS:ID   0.000956637:0.00299863:0.125108:0.868456:75177:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865365 ES:SE:LP:AF:SS:ID   0.000947246:0.00299969:0.123684:0.865365:75177:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0995942    ES:SE:LP:AF:SS:ID   0.00100672:0.00358956:0.108391:0.0995942:75177:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870659 ES:SE:LP:AF:SS:ID   0.000724562:0.00303361:0.0908576:0.870659:75177:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870659 ES:SE:LP:AF:SS:ID   0.000724761:0.00303361:0.0908849:0.870659:75177:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870656 ES:SE:LP:AF:SS:ID   0.000725028:0.00303362:0.0909213:0.870656:75177:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.871036 ES:SE:LP:AF:SS:ID   0.000659842:0.0030351:0.0820247:0.871036:75177:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126586 ES:SE:LP:AF:SS:ID   -0.000456091:0.00303849:0.0551809:0.126586:75177:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10597  ES:SE:LP:AF:SS:ID   8.81167e-06:0.00330318:0.000925163:0.10597:75177:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854336 ES:SE:LP:AF:SS:ID   0.000730721:0.00296942:0.0938698:0.854336:75177:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00168869   ES:SE:LP:AF:SS:ID   0.0158688:0.0260058:0.266218:0.00168869:75177:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839618 ES:SE:LP:AF:SS:ID   0.0034694:0.00293322:0.625446:0.839618:75177:rs376645387