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/public/UKB-b-15957/UKB-b-15957_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15957/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:37 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15957/UKB-b-15957_data.vcf.gz ...
Read summary statistics for 9259306 SNPs.
Dropped 10042 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../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 ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1287843 SNPs remain.
After merging with regression SNP LD, 1287843 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0223 (0.0016)
Lambda GC: 1.247
Mean Chi^2: 1.2675
Intercept: 1.0669 (0.0075)
Ratio: 0.2502 (0.0281)
Analysis finished at Thu Oct 17 14:46:19 2019
Total time elapsed: 1.0m:42.59s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9485,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 9,
    "n_p_sig": 324,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": true,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 0,
    "n_miss_AF_reference": 108767,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1287843,
    "ldsc_nsnp_merge_regression_ld": 1287843,
    "ldsc_observed_scale_h2_beta": 0.0223,
    "ldsc_observed_scale_h2_se": 0.0016,
    "ldsc_intercept_beta": 1.0669,
    "ldsc_intercept_se": 0.0075,
    "ldsc_lambda_gc": 1.247,
    "ldsc_mean_chisq": 1.2675,
    "ldsc_ratio": 0.2501
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n TRUE
is_snpid_non_unique FALSE
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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 58 0 9249315 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 9259306 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.636143e+00 5.754592e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.880520e+07 5.631134e+07 828.0000000 3.249227e+07 6.938609e+07 1.145344e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.320000e-05 3.603300e-03 -0.0433136 -1.372500e-03 -5.000000e-07 1.385100e-03 4.823300e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.707900e-03 2.111900e-03 0.0009202 1.105400e-03 1.737400e-03 3.713600e-03 2.291500e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.714003e-01 2.956416e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▇▇▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.714014e-01 2.956157e-01 0.0000000 2.083510e-01 4.612045e-01 7.266343e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.147190e-01 2.579141e-01 0.0025190 1.792000e-02 9.381900e-02 3.374810e-01 9.974810e-01 ▇▂▁▁▁
numeric AF_reference 108767 0.9882532 NA NA NA NA NA NA NA 2.155741e-01 2.497335e-01 0.0000000 1.517570e-02 1.120210e-01 3.370610e-01 1.000000e+00 ▇▂▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 49298 rs200943160 T C -0.0010080 0.0016931 0.5500004 0.5516028 0.623764 0.7821490 NA
1 54676 rs2462492 C T -0.0003504 0.0016771 0.8300000 0.8344822 0.400406 NA NA
1 86028 rs114608975 T C 0.0005505 0.0026812 0.8400000 0.8373341 0.103563 0.0277556 NA
1 91536 rs6702460 G T -0.0027256 0.0016514 0.0990011 0.0988390 0.456846 0.4207270 NA
1 234313 rs8179466 C T -0.0060111 0.0032561 0.0649995 0.0648733 0.074504 NA NA
1 534192 rs6680723 C T 0.0016796 0.0018865 0.3700002 0.3732950 0.240945 NA NA
1 546697 rs12025928 A G -0.0013378 0.0023537 0.5700002 0.5697708 0.913508 NA NA
1 693731 rs12238997 A G 0.0036448 0.0015806 0.0210000 0.0211159 0.116354 0.1417730 NA
1 705882 rs72631875 G A 0.0043919 0.0023167 0.0580003 0.0579960 0.067273 0.0315495 NA
1 706368 rs55727773 A G -0.0007742 0.0011710 0.5099998 0.5085001 0.515599 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0020426 0.0014131 0.1499999 0.1483335 0.137947 0.2052720 NA
22 51219387 rs9616832 T C 0.0037406 0.0018343 0.0409996 0.0414276 0.073727 0.0654952 NA
22 51219704 rs147475742 G A 0.0026535 0.0024582 0.2800000 0.2803838 0.041939 0.0473243 NA
22 51221190 rs369304721 G A 0.0051433 0.0024542 0.0359998 0.0361068 0.049719 NA NA
22 51221731 rs115055839 T C 0.0037749 0.0018355 0.0400000 0.0397198 0.073218 0.0625000 NA
22 51222100 rs114553188 G T 0.0003362 0.0021602 0.8800001 0.8763243 0.054475 0.0880591 NA
22 51223637 rs375798137 G A 0.0002366 0.0021707 0.9100000 0.9131883 0.054104 0.0788738 NA
22 51229805 rs9616985 T C 0.0035440 0.0018422 0.0539995 0.0543782 0.073051 0.0730831 NA
22 51232488 rs376461333 A G 0.0037888 0.0043372 0.3800004 0.3823580 0.020054 NA NA
22 51237063 rs3896457 T C -0.0000335 0.0011266 0.9800000 0.9762780 0.297950 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623764 ES:SE:LP:AF:ID  -0.00100801:0.00169311:0.259637:0.623764:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400406 ES:SE:LP:AF:ID  -0.000350441:0.0016771:0.0809219:0.400406:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103563 ES:SE:LP:AF:ID  0.000550465:0.00268121:0.0757207:0.103563:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  -0.0027256:0.00165137:1.00436:0.456846:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074504 ES:SE:LP:AF:ID  -0.00601111:0.00325606:1.18709:0.074504:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240945 ES:SE:LP:AF:ID  0.00167955:0.00188646:0.431798:0.240945:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913508 ES:SE:LP:AF:ID  -0.00133784:0.00235374:0.244125:0.913508:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116354 ES:SE:LP:AF:ID  0.00364483:0.00158065:1.67778:0.116354:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067273 ES:SE:LP:AF:ID  0.00439191:0.00231674:1.23657:0.067273:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515599 ES:SE:LP:AF:ID  -0.000774236:0.001171:0.29243:0.515599:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032979 ES:SE:LP:AF:ID  0.00115464:0.00295344:0.154902:0.032979:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036594 ES:SE:LP:AF:ID  0.000856602:0.0026826:0.124939:0.036594:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036711 ES:SE:LP:AF:ID  0.00107048:0.00267243:0.161151:0.036711:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036411 ES:SE:LP:AF:ID  0.00129072:0.00269165:0.200659:0.036411:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016396 ES:SE:LP:AF:ID  0.0040438:0.00414475:0.481486:0.016396:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.03695  ES:SE:LP:AF:ID  0.000989452:0.00266184:0.148742:0.03695:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037046 ES:SE:LP:AF:ID  0.00117587:0.00265276:0.180456:0.037046:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101247 ES:SE:LP:AF:ID  -0.00165381:0.0019316:0.408935:0.101247:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959119 ES:SE:LP:AF:ID  -0.00220942:0.00255836:0.408935:0.959119:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031449 ES:SE:LP:AF:ID  -0.00723248:0.00464269:0.920819:0.031449:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.05328  ES:SE:LP:AF:ID  -0.00487575:0.00369176:0.721246:0.05328:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036565 ES:SE:LP:AF:ID  0.00126811:0.00266985:0.200659:0.036565:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036879 ES:SE:LP:AF:ID  0.00108757:0.00264562:0.167491:0.036879:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843219 ES:SE:LP:AF:ID  -0.00350533:0.00137002:1.95861:0.843219:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055932 ES:SE:LP:AF:ID  0.00442876:0.00221781:1.33724:0.055932:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122326 ES:SE:LP:AF:ID  0.00370432:0.00149943:1.88606:0.122326:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025683 ES:SE:LP:AF:ID  -0.00338935:0.00369043:0.443698:0.025683:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12157  ES:SE:LP:AF:ID  0.00367473:0.00150005:1.85387:0.12157:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132331 ES:SE:LP:AF:ID  0.00333336:0.00147862:1.61979:0.132331:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011145 ES:SE:LP:AF:ID  0.000310613:0.00537248:0.0222764:0.011145:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005706 ES:SE:LP:AF:ID  0.0121313:0.006936:1.09691:0.005706:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036795 ES:SE:LP:AF:ID  0.00110928:0.00261885:0.173925:0.036795:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838954 ES:SE:LP:AF:ID  -0.00343453:0.00132673:2.01773:0.838954:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838582 ES:SE:LP:AF:ID  -0.00344734:0.00132531:2.03152:0.838582:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869756 ES:SE:LP:AF:ID  -0.00383469:0.00142204:2.1549:0.869756:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129892 ES:SE:LP:AF:ID  0.0038338:0.00142493:2.14874:0.129892:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037306 ES:SE:LP:AF:ID  0.00153206:0.00257443:0.259637:0.037306:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.03755  ES:SE:LP:AF:ID  0.00151836:0.00255815:0.259637:0.03755:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869099 ES:SE:LP:AF:ID  -0.00388668:0.00141926:2.20761:0.869099:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869196 ES:SE:LP:AF:ID  -0.00392664:0.00141982:2.24413:0.869196:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037508 ES:SE:LP:AF:ID  0.00146255:0.00256923:0.244125:0.037508:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -0.00388969:0.00141923:2.21467:0.869101:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005123 ES:SE:LP:AF:ID  0.00562782:0.00728557:0.356547:0.005123:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005089 ES:SE:LP:AF:ID  0.0054916:0.00730468:0.346787:0.005089:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838034 ES:SE:LP:AF:ID  -0.0034598:0.00132162:2.05552:0.838034:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037521 ES:SE:LP:AF:ID  0.00157544:0.00257284:0.267606:0.037521:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838663 ES:SE:LP:AF:ID  -0.0034653:0.00132534:2.05061:0.838663:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013784 ES:SE:LP:AF:ID  0.00484616:0.00462394:0.537602:0.013784:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005543 ES:SE:LP:AF:ID  -0.00196614:0.00714009:0.107905:0.005543:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  -0.00337283:0.00134326:1.92082:0.839777:rs3131965