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-20499/ukb-d-20499.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-20499/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 17:19:05 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-20499/ukb-d-20499.vcf.gz ...
Read summary statistics for 13571560 SNPs.
Dropped 12696 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: 0.0646 (0.0053)
Lambda GC: 1.1414
Mean Chi^2: 1.1599
Intercept: 1.0087 (0.0075)
Ratio: 0.0543 (0.0471)
Analysis finished at Mon Nov 25 17:21:42 2019
Total time elapsed: 2.0m:36.7s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.0923,
    "mean_EFFECT": 0,
    "n": 117677,
    "n_snps": 13571560,
    "n_clumped_hits": 3,
    "n_p_sig": 125,
    "n_mono": 0,
    "n_ns": 1251353,
    "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": 564587,
    "n_est": 118105.9668,
    "ratio_se_n": 1.0018,
    "mean_diff": 0,
    "ratio_diff": 21.6747,
    "sd_y_est1": 0.4798,
    "sd_y_est2": 0.4807,
    "r2_sum1": 0.0002,
    "r2_sum2": 0.0009,
    "r2_sum3": 0.0009,
    "r2_sum4": 0.0009,
    "ldsc_nsnp_merge_refpanel_ld": 1283502,
    "ldsc_nsnp_merge_regression_ld": 1283502,
    "ldsc_observed_scale_h2_beta": 0.0646,
    "ldsc_observed_scale_h2_se": 0.0053,
    "ldsc_intercept_beta": 1.0087,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.1414,
    "ldsc_mean_chisq": 1.1599,
    "ldsc_ratio": 0.0544
}

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 13559528 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57053 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 342 0 33331 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.051455e+00 6.185087e+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 7.902505e+07 5.591561e+07 3.02000e+02 3.292850e+07 7.013920e+07 1.148580e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 2.160000e-05 1.160330e-02 -1.34366e-01 -3.203200e-03 2.140000e-05 3.233100e-03 1.518720e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 8.286800e-03 7.987900e-03 1.63780e-03 2.365100e-03 4.352600e-03 1.189810e-02 3.995540e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.856737e-01 2.927586e-01 0.00000e+00 2.285362e-01 4.808515e-01 7.391899e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.856724e-01 2.927594e-01 0.00000e+00 2.285332e-01 4.808493e-01 7.391896e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 1.909976e-01 2.544492e-01 1.00000e-03 7.483500e-03 6.026490e-02 2.956750e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 564587 0.9583993 NA NA NA NA NA 1.964726e-01 2.471288e-01 0.00000e+00 5.790700e-03 8.446490e-02 3.083070e-01 1.000000e+00 ▇▂▁▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.176770e+05 0.000000e+00 1.17677e+05 1.176770e+05 1.176770e+05 1.176770e+05 1.176770e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C 0.0000202 0.0034436 0.9953110 0.9953110 0.1117450 0.1894970 117677
1 693731 rs12238997 A G 0.0013553 0.0032611 0.6777086 0.6777070 0.1167660 0.1417730 117677
1 707522 rs371890604 G C 0.0016619 0.0036594 0.6497361 0.6497356 0.0983539 0.1293930 117677
1 717587 rs144155419 G A -0.0023337 0.0087678 0.7901090 0.7901079 0.0157666 0.0045926 117677
1 723329 rs189787166 A T 0.0123955 0.0255888 0.6280960 0.6280941 0.0017740 0.0003994 117677
1 730087 rs148120343 T C 0.0019985 0.0045391 0.6597281 0.6597266 0.0569111 0.0127796 117677
1 731718 rs142557973 T C 0.0014232 0.0030943 0.6455635 0.6455643 0.1226810 0.1543530 117677
1 732032 rs61770163 A C -0.0002948 0.0032980 0.9287730 0.9287726 0.1222610 0.1555510 117677
1 734349 rs141242758 T C 0.0015311 0.0030959 0.6209162 0.6209138 0.1219370 0.1525560 117677
1 740284 rs61770167 C T -0.0087562 0.0141217 0.5352233 0.5352221 0.0058700 0.0023962 117677
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T -0.0060709 0.0036382 0.0951897 0.0951864 0.0555143 0.0309934 117677
23 154923374 rs111332691 T A -0.0013389 0.0039665 0.7357072 0.7357078 0.0447709 0.0116556 117677
23 154925045 rs509981 C T 0.0028093 0.0019102 0.1413781 0.1413753 0.2446450 0.3634440 117677
23 154925895 rs538470 C T 0.0028084 0.0019534 0.1505178 0.1505157 0.2410730 0.3634440 117677
23 154927581 rs644138 G A 0.0011008 0.0017973 0.5402453 0.5402447 0.3005210 0.4635760 117677
23 154929412 rs557132 C T 0.0027506 0.0019107 0.1499909 0.1499887 0.2445190 0.3568210 117677
23 154929637 rs35185538 CT C 0.0035937 0.0019959 0.0717794 0.0717759 0.2287620 0.3011920 117677
23 154929952 rs4012982 CAA C 0.0028750 0.0020108 0.1527981 0.1527963 0.2386030 0.3165560 117677
23 154930230 rs781880 A G 0.0027156 0.0019102 0.1551290 0.1551271 0.2449430 0.3618540 117677
23 154930487 rs781879 T A 0.0094786 0.0064925 0.1443128 0.1443104 0.0196688 0.1263580 117677

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.111745 ES:SE:LP:AF:SS:ID   2.02376e-05:0.0034436:0.0020412:0.111745:117677:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.116766 ES:SE:LP:AF:SS:ID   0.00135529:0.00326109:0.168957:0.116766:117677:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.0983539    ES:SE:LP:AF:SS:ID   0.00166186:0.00365944:0.187263:0.0983539:117677:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.0157666    ES:SE:LP:AF:SS:ID   -0.00233374:0.00876784:0.102313:0.0157666:117677:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.001774 ES:SE:LP:AF:SS:ID   0.0123955:0.0255888:0.201974:0.001774:117677:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.0569111    ES:SE:LP:AF:SS:ID   0.00199851:0.00453907:0.180635:0.0569111:117677:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122681 ES:SE:LP:AF:SS:ID   0.00142318:0.00309432:0.190061:0.122681:117677:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.122261 ES:SE:LP:AF:SS:ID   -0.000294809:0.00329804:0.0320904:0.122261:117677:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.121937 ES:SE:LP:AF:SS:ID   0.0015311:0.00309591:0.206967:0.121937:117677:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.00587004   ES:SE:LP:AF:SS:ID   -0.00875622:0.0141217:0.271465:0.00587004:117677:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00182795   ES:SE:LP:AF:SS:ID   0.0557856:0.0271567:1.3984:0.00182795:117677:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.868987 ES:SE:LP:AF:SS:ID   -0.0013473:0.00305068:0.181279:0.868987:117677:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.00158321   ES:SE:LP:AF:SS:ID   -0.000309087:0.0271426:0.00396404:0.00158321:117677:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.123708 ES:SE:LP:AF:SS:ID   0.00125706:0.00302267:0.169091:0.123708:117677:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.14333  ES:SE:LP:AF:SS:ID   0.00263526:0.00298961:0.422435:0.14333:117677:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12383  ES:SE:LP:AF:SS:ID   0.00122887:0.00301847:0.164993:0.12383:117677:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.869768 ES:SE:LP:AF:SS:ID   -0.00199321:0.00293954:0.303007:0.869768:117677:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.874545 ES:SE:LP:AF:SS:ID   -0.00176203:0.00298899:0.255299:0.874545:117677:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.129695 ES:SE:LP:AF:SS:ID   0.00167173:0.00294775:0.243644:0.129695:117677:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.0365322    ES:SE:LP:AF:SS:ID   0.0110507:0.00535315:1.40906:0.0365322:117677:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869361 ES:SE:LP:AF:SS:ID   -0.00204039:0.00293674:0.312298:0.869361:117677:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869428 ES:SE:LP:AF:SS:ID   -0.00198331:0.0029378:0.301365:0.869428:117677:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.86936  ES:SE:LP:AF:SS:ID   -0.00201863:0.00293666:0.308177:0.86936:117677:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.00510457   ES:SE:LP:AF:SS:ID   0.000351179:0.0150447:0.00816412:0.00510457:117677:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00507359   ES:SE:LP:AF:SS:ID   -0.000162546:0.0150781:0.00375152:0.00507359:117677:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.00568504   ES:SE:LP:AF:SS:ID   -0.0102024:0.0144805:0.317778:0.00568504:117677:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.869435 ES:SE:LP:AF:SS:ID   -0.00190538:0.00293127:0.287619:0.869435:117677:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.126972 ES:SE:LP:AF:SS:ID   0.00145991:0.00299216:0.203694:0.126972:117677:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.868955 ES:SE:LP:AF:SS:ID   -0.00181817:0.00292355:0.272455:0.868955:117677:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868354 ES:SE:LP:AF:SS:ID   -0.00177195:0.00292244:0.264162:0.868354:117677:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869145 ES:SE:LP:AF:SS:ID   -0.00188502:0.00292646:0.284421:0.869145:117677:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869152 ES:SE:LP:AF:SS:ID   -0.00188589:0.00292667:0.284557:0.869152:117677:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869154 ES:SE:LP:AF:SS:ID   -0.00188309:0.00292668:0.284037:0.869154:117677:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.86959  ES:SE:LP:AF:SS:ID   -0.00198928:0.00293419:0.30295:0.86959:117677:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.0995957    ES:SE:LP:AF:SS:ID   0.00200805:0.00341107:0.254868:0.0995957:117677:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0065427    ES:SE:LP:AF:SS:ID   -0.00642314:0.0131477:0.204001:0.0065427:117677:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.873645 ES:SE:LP:AF:SS:ID   -0.00173773:0.00297919:0.252045:0.873645:117677:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.862934 ES:SE:LP:AF:SS:ID   -0.00210824:0.00292168:0.327394:0.862934:117677:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.868335 ES:SE:LP:AF:SS:ID   -0.00170905:0.0029498:0.250006:0.868335:117677:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.865338 ES:SE:LP:AF:SS:ID   -0.0015593:0.00295025:0.22393:0.865338:117677:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.0997639    ES:SE:LP:AF:SS:ID   0.000523238:0.00352522:0.0545285:0.0997639:117677:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.870631 ES:SE:LP:AF:SS:ID   -0.0019318:0.00298506:0.286063:0.870631:117677:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.870631 ES:SE:LP:AF:SS:ID   -0.00193168:0.00298506:0.28604:0.870631:117677:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.870629 ES:SE:LP:AF:SS:ID   -0.00193775:0.00298506:0.287146:0.870629:117677:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.870952 ES:SE:LP:AF:SS:ID   -0.00196289:0.00298633:0.291584:0.870952:117677:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.126564 ES:SE:LP:AF:SS:ID   0.00128775:0.00298892:0.176145:0.126564:117677:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106341 ES:SE:LP:AF:SS:ID   0.00172608:0.00324821:0.225376:0.106341:117677:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.854374 ES:SE:LP:AF:SS:ID   -0.00279351:0.00292085:0.469966:0.854374:117677:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.00169052   ES:SE:LP:AF:SS:ID   0.0100655:0.0256659:0.15806:0.00169052:117677:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.839056 ES:SE:LP:AF:SS:ID   -0.00388309:0.00289374:0.745614:0.839056:117677:rs376645387