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-30730_irnt/ukb-d-30730_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-30730_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 15:03:47 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30730_irnt/ukb-d-30730_irnt.vcf.gz ...
Read summary statistics for 13586025 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: 0.1965 (0.025)
Lambda GC: 1.6572
Mean Chi^2: 2.4683
Intercept: 1.1706 (0.0177)
Ratio: 0.1162 (0.012)
Analysis finished at Mon Nov 25 15:05:51 2019
Total time elapsed: 2.0m:3.93s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9521,
    "inflation_factor": 1.3989,
    "mean_EFFECT": 0.0001,
    "n": 344104,
    "n_snps": 13586025,
    "n_clumped_hits": 288,
    "n_p_sig": 53540,
    "n_mono": 0,
    "n_ns": 1251779,
    "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": 569161,
    "n_est": 345441.4465,
    "ratio_se_n": 1.0019,
    "mean_diff": 2.2368e-06,
    "ratio_diff": 1.0098,
    "sd_y_est1": 0.924,
    "sd_y_est2": 0.9257,
    "r2_sum1": 0.0898,
    "r2_sum2": 0.1052,
    "r2_sum3": 0.1048,
    "r2_sum4": 0.1044,
    "ldsc_nsnp_merge_refpanel_ld": 1283504,
    "ldsc_nsnp_merge_regression_ld": 1283504,
    "ldsc_observed_scale_h2_beta": 0.1965,
    "ldsc_observed_scale_h2_se": 0.025,
    "ldsc_intercept_beta": 1.1706,
    "ldsc_intercept_se": 0.0177,
    "ldsc_lambda_gc": 1.6572,
    "ldsc_mean_chisq": 2.4683,
    "ldsc_ratio": 0.1162
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
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 13573978 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 100 0 57082 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 9.051241e+00 6.184968e+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 7.902581e+07 5.591529e+07 3.02000e+02 3.293104e+07 7.013951e+07 1.148605e+08 2.492309e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.550000e-05 1.390750e-02 -4.67010e-01 -4.253500e-03 3.020000e-05 4.309700e-03 4.452400e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.359200e-03 9.028000e-03 1.83120e-03 2.664700e-03 4.910300e-03 1.345000e-02 4.559200e-02 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.445059e-01 3.044380e-01 0.00000e+00 1.665900e-01 4.250099e-01 7.084301e-01 1.000000e+00 ▇▆▅▅▅
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.445054e-01 3.044383e-01 0.00000e+00 1.665851e-01 4.250072e-01 7.084284e-01 9.999997e-01 ▇▆▅▅▅
numeric AF 0 1.0000000 NA NA NA NA NA 1.908095e-01 2.544044e-01 1.00000e-03 7.431500e-03 6.003800e-02 2.953200e-01 9.990000e-01 ▇▂▁▁▁
numeric AF_reference 569161 0.9581069 NA NA NA NA NA 1.963388e-01 2.471025e-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 3.441040e+05 0.000000e+00 3.44104e+05 3.441040e+05 3.441040e+05 3.441040e+05 3.441040e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 692794 rs530212009 CA C -0.0008958 0.0039010 0.8183800 0.8183846 0.1105300 0.1894970 344104
1 693731 rs12238997 A G -0.0000497 0.0036845 0.9892300 0.9892345 0.1158100 0.1417730 344104
1 707522 rs371890604 G C 0.0055576 0.0041442 0.1799099 0.1799026 0.0972480 0.1293930 344104
1 717587 rs144155419 G A -0.0292170 0.0098932 0.0031443 0.0031446 0.0156620 0.0045926 344104
1 723329 rs189787166 A T -0.0427290 0.0291220 0.1423099 0.1423104 0.0017386 0.0003994 344104
1 730087 rs148120343 T C 0.0080121 0.0051346 0.1186599 0.1186622 0.0564340 0.0127796 344104
1 731718 rs142557973 T C 0.0010359 0.0034945 0.7669005 0.7668962 0.1217000 0.1543530 344104
1 732032 rs61770163 A C 0.0023290 0.0037288 0.5322296 0.5322351 0.1211100 0.1555510 344104
1 734349 rs141242758 T C 0.0011882 0.0034964 0.7339695 0.7339806 0.1209200 0.1525560 344104
1 740284 rs61770167 C T 0.0042971 0.0160350 0.7887094 0.7887128 0.0057579 0.0023962 344104
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154923311 rs141127553 C T 0.0072998 0.0040382 0.0706578 0.0706553 0.056191 0.0309934 344104
23 154923374 rs111332691 T A 0.0053119 0.0044332 0.2308400 0.2308357 0.044861 0.0116556 344104
23 154925045 rs509981 C T -0.0043860 0.0021352 0.0399632 0.0399621 0.245660 0.3634440 344104
23 154925895 rs538470 C T -0.0041553 0.0021842 0.0571176 0.0571142 0.242000 0.3634440 344104
23 154927581 rs644138 G A -0.0021200 0.0020081 0.2910999 0.2910942 0.302240 0.4635760 344104
23 154929412 rs557132 C T -0.0043382 0.0021358 0.0422396 0.0422365 0.245520 0.3568210 344104
23 154929637 rs35185538 CT C -0.0037689 0.0022292 0.0908887 0.0908948 0.229770 0.3011920 344104
23 154929952 rs4012982 CAA C -0.0052212 0.0022462 0.0201030 0.0201009 0.239500 0.3165560 344104
23 154930230 rs781880 A G -0.0044681 0.0021355 0.0364141 0.0364120 0.245920 0.3618540 344104
23 154930487 rs781879 T A -0.0037192 0.0073214 0.6114599 0.6114602 0.019557 0.1263580 344104

bcf preview

1   692794  rs530212009 CA  C   .   PASS    AF=0.11053  ES:SE:LP:AF:SS:ID   -0.00089576:0.003901:0.087045:0.11053:344104:1_692794_CA_C
1   693731  rs12238997  A   G   .   PASS    AF=0.11581  ES:SE:LP:AF:SS:ID   -4.9715e-05:0.0036845:0.00470272:0.11581:344104:rs12238997
1   707522  rs371890604 G   C   .   PASS    AF=0.097248 ES:SE:LP:AF:SS:ID   0.0055576:0.0041442:0.744945:0.097248:344104:rs371890604
1   717587  rs144155419 G   A   .   PASS    AF=0.015662 ES:SE:LP:AF:SS:ID   -0.029217:0.0098932:2.50248:0.015662:344104:rs144155419
1   723329  rs189787166 A   T   .   PASS    AF=0.0017386    ES:SE:LP:AF:SS:ID   -0.042729:0.029122:0.846765:0.0017386:344104:rs189787166
1   730087  rs148120343 T   C   .   PASS    AF=0.056434 ES:SE:LP:AF:SS:ID   0.0080121:0.0051346:0.925696:0.056434:344104:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.1217   ES:SE:LP:AF:SS:ID   0.0010359:0.0034945:0.115261:0.1217:344104:rs58276399
1   732032  rs61770163  A   C   .   PASS    AF=0.12111  ES:SE:LP:AF:SS:ID   0.002329:0.0037288:0.273901:0.12111:344104:rs61770163
1   734349  rs141242758 T   C   .   PASS    AF=0.12092  ES:SE:LP:AF:SS:ID   0.0011882:0.0034964:0.134322:0.12092:344104:rs141242758
1   740284  rs61770167  C   T   .   PASS    AF=0.0057579    ES:SE:LP:AF:SS:ID   0.0042971:0.016035:0.103083:0.0057579:344104:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.001861 ES:SE:LP:AF:SS:ID   0.00074804:0.030409:0.00860999:0.001861:344104:rs112573343
1   749963  rs529266287 T   TAA .   PASS    AF=0.8698   ES:SE:LP:AF:SS:ID   -0.00024361:0.0034471:0.0251845:0.8698:344104:rs529266287
1   750230  rs190826124 G   C   .   PASS    AF=0.0015226    ES:SE:LP:AF:SS:ID   0.029624:0.0313:0.463555:0.0015226:344104:rs190826124
1   751343  rs28544273  T   A   .   PASS    AF=0.12288  ES:SE:LP:AF:SS:ID   0.0012981:0.0034137:0.152588:0.12288:344104:rs28544273
1   751488  rs200141114 G   GA  .   PASS    AF=0.1427   ES:SE:LP:AF:SS:ID   0.0015962:0.0033738:0.196454:0.1427:344104:rs200141114
1   751756  rs28527770  T   C   .   PASS    AF=0.12299  ES:SE:LP:AF:SS:ID   0.0013295:0.0034089:0.15706:0.12299:344104:rs28527770
1   753405  rs3115860   C   A   .   PASS    AF=0.87096  ES:SE:LP:AF:SS:ID   -0.0024095:0.0033224:0.329467:0.87096:344104:rs3115860
1   753425  rs3131970   T   C   .   PASS    AF=0.87552  ES:SE:LP:AF:SS:ID   -0.0019834:0.003377:0.254153:0.87552:344104:rs3131970
1   753541  rs2073813   G   A   .   PASS    AF=0.12858  ES:SE:LP:AF:SS:ID   0.0022648:0.0033305:0.304089:0.12858:344104:rs2073813
1   754105  rs12184325  C   T   .   PASS    AF=0.036315 ES:SE:LP:AF:SS:ID   0.0023089:0.0060472:0.153292:0.036315:344104:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.87055  ES:SE:LP:AF:SS:ID   -0.002356:0.0033189:0.320772:0.87055:344104:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.87066  ES:SE:LP:AF:SS:ID   -0.0023619:0.0033204:0.321591:0.87066:344104:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.87055  ES:SE:LP:AF:SS:ID   -0.0023546:0.0033188:0.320545:0.87055:344104:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005051 ES:SE:LP:AF:SS:ID   0.012335:0.017019:0.329216:0.005051:344104:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.0050179    ES:SE:LP:AF:SS:ID   0.01214:0.017065:0.321646:0.0050179:344104:rs142682604
1   755435  rs184270342 T   G   .   PASS    AF=0.0055485    ES:SE:LP:AF:SS:ID   -0.0066761:0.016561:0.163132:0.0055485:344104:rs184270342
1   755890  rs3115858   A   T   .   PASS    AF=0.87064  ES:SE:LP:AF:SS:ID   -0.0026245:0.003313:0.368282:0.87064:344104:rs3115858
1   756434  rs61768170  G   C   .   PASS    AF=0.12592  ES:SE:LP:AF:SS:ID   0.0023717:0.0033803:0.316143:0.12592:344104:rs61768170
1   756604  rs3131962   A   G   .   PASS    AF=0.87021  ES:SE:LP:AF:SS:ID   -0.0028122:0.0033052:0.403557:0.87021:344104:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.86948  ES:SE:LP:AF:SS:ID   -0.0023516:0.0033021:0.322056:0.86948:344104:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.87035  ES:SE:LP:AF:SS:ID   -0.0026523:0.0033079:0.374009:0.87035:344104:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.87036  ES:SE:LP:AF:SS:ID   -0.0026564:0.0033081:0.374708:0.87036:344104:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.87037  ES:SE:LP:AF:SS:ID   -0.0026385:0.0033083:0.371478:0.87037:344104:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.87081  ES:SE:LP:AF:SS:ID   -0.0025141:0.0033166:0.348305:0.87081:344104:rs3131954
1   759293  rs10157329  T   A   .   PASS    AF=0.098788 ES:SE:LP:AF:SS:ID   0.0047236:0.0038547:0.656749:0.098788:344104:rs10157329
1   759600  rs545998451 AGT A   .   PASS    AF=0.0064335    ES:SE:LP:AF:SS:ID   -0.010724:0.014963:0.324625:0.0064335:344104:1_759600_AGT_A
1   759837  rs3115851   T   A   .   PASS    AF=0.8747   ES:SE:LP:AF:SS:ID   -0.0018281:0.0033658:0.231332:0.8747:344104:rs3115851
1   761732  rs2286139   C   T   .   PASS    AF=0.86411  ES:SE:LP:AF:SS:ID   -0.0020837:0.0033013:0.277415:0.86411:344104:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.86949  ES:SE:LP:AF:SS:ID   -0.0024899:0.0033328:0.341979:0.86949:344104:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.86643  ES:SE:LP:AF:SS:ID   -0.0016259:0.0033335:0.203613:0.86643:344104:rs3115849
1   762485  rs12095200  C   A   .   PASS    AF=0.098745 ES:SE:LP:AF:SS:ID   7.033e-06:0.0039905:0.000612787:0.098745:344104:rs12095200
1   762589  rs3115848   G   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   -0.0015099:0.0033716:0.184243:0.87161:344104:rs3115848
1   762592  rs3131950   C   G   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   -0.0015102:0.0033716:0.184283:0.87161:344104:rs3131950
1   762601  rs3131949   T   C   .   PASS    AF=0.87161  ES:SE:LP:AF:SS:ID   -0.0014992:0.0033716:0.182719:0.87161:344104:rs3131949
1   762632  rs3131948   T   A   .   PASS    AF=0.87198  ES:SE:LP:AF:SS:ID   -0.0016997:0.0033735:0.21157:0.87198:344104:rs3131948
1   764191  rs7515915   T   G   .   PASS    AF=0.12551  ES:SE:LP:AF:SS:ID   0.0019773:0.0033759:0.253304:0.12551:344104:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.10539  ES:SE:LP:AF:SS:ID   0.0057014:0.003676:0.917538:0.10539:344104:rs61768174
1   766105  rs2519015   T   A   .   PASS    AF=0.85545  ES:SE:LP:AF:SS:ID   -0.0030073:0.0033:0.441124:0.85545:344104:rs2519015
1   767393  rs538667473 A   C   .   PASS    AF=0.0016573    ES:SE:LP:AF:SS:ID   -0.049452:0.029195:1.04434:0.0016573:344104:rs538667473
1   768116  rs376645387 A   AGTTTT  .   PASS    AF=0.83826  ES:SE:LP:AF:SS:ID   -6.4086e-05:0.0032493:0.00689016:0.83826:344104:rs376645387