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-929/UKB-b-929_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-929/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:25 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-929/UKB-b-929_data.vcf.gz ...
Read summary statistics for 9851866 SNPs.
Dropped 14738 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, 1289166 SNPs remain.
After merging with regression SNP LD, 1289166 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.059 (0.0024)
Lambda GC: 1.4516
Mean Chi^2: 1.562
Intercept: 1.0391 (0.0083)
Ratio: 0.0695 (0.0148)
Analysis finished at Thu Oct 17 14:44:34 2019
Total time elapsed: 2.0m:9.4s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9499,
    "inflation_factor": 1.3107,
    "mean_EFFECT": 0.0002,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 40,
    "n_p_sig": 2326,
    "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": 184849,
    "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": 1289166,
    "ldsc_nsnp_merge_regression_ld": 1289166,
    "ldsc_observed_scale_h2_beta": 0.059,
    "ldsc_observed_scale_h2_se": 0.0024,
    "ldsc_intercept_beta": 1.0391,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.4516,
    "ldsc_mean_chisq": 1.562,
    "ldsc_ratio": 0.0696
}

Flags

name value
af_correlation FALSE
inflation_factor TRUE
n TRUE
is_snpid_non_unique FALSE
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 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 9837196 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 9851866 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 8.622825e+00 5.748290e+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 7.886027e+07 5.628334e+07 828.0000000 3.259061e+07 6.948835e+07 1.145912e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.763000e-04 8.735400e-03 -0.1206260 -2.813200e-03 5.540000e-05 2.971700e-03 1.301920e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.014600e-03 5.694700e-03 0.0016832 2.060000e-03 3.454600e-03 7.970900e-03 8.832630e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.566095e-01 3.009849e-01 0.0000000 1.800002e-01 4.400003e-01 7.199992e-01 1.000000e+00 ▇▆▆▅▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.566128e-01 3.009592e-01 0.0000000 1.846137e-01 4.408176e-01 7.176822e-01 9.999999e-01 ▇▆▆▆▅
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.035071e-01 2.568633e-01 0.0009750 1.316800e-02 7.790700e-02 3.164558e-01 9.990220e-01 ▇▂▁▁▁
numeric AF_reference 184849 0.9812372 NA NA NA NA NA NA NA 2.068392e-01 2.482924e-01 0.0000000 1.198080e-02 9.984030e-02 3.202880e-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 0.0017940 0.0030951 0.5600000 0.5621726 0.623764 0.7821490 NA
1 54676 rs2462492 C T -0.0031798 0.0030666 0.2999998 0.2997789 0.400400 NA NA
1 86028 rs114608975 T C 0.0084905 0.0049004 0.0830004 0.0831639 0.103596 0.0277556 NA
1 91536 rs6702460 G T 0.0002390 0.0030195 0.9400001 0.9368994 0.456846 0.4207270 NA
1 234313 rs8179466 C T 0.0075916 0.0059507 0.2000000 0.2020418 0.074528 NA NA
1 534192 rs6680723 C T -0.0001199 0.0034484 0.9699999 0.9722527 0.241034 NA NA
1 546697 rs12025928 A G -0.0007214 0.0043024 0.8700001 0.8668372 0.913482 NA NA
1 693731 rs12238997 A G 0.0035268 0.0028898 0.2200002 0.2222997 0.116339 0.1417730 NA
1 705882 rs72631875 G A 0.0020580 0.0042362 0.6300007 0.6270907 0.067250 0.0315495 NA
1 706368 rs55727773 A G -0.0018946 0.0021408 0.3800004 0.3761572 0.515574 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219704 rs147475742 G A -0.0009237 0.0044965 0.8400000 0.8372414 0.041947 0.0473243 NA
22 51219766 rs182321900 C T 0.0130242 0.0209530 0.5300002 0.5342107 0.001940 NA NA
22 51220146 rs868950473 C T 0.0141392 0.0207636 0.5000000 0.4958962 0.001987 NA NA
22 51221190 rs369304721 G A 0.0021294 0.0044880 0.6400000 0.6351714 0.049741 NA NA
22 51221731 rs115055839 T C 0.0010036 0.0033578 0.7700005 0.7650253 0.073200 0.0625000 NA
22 51222100 rs114553188 G T 0.0018466 0.0039540 0.6400000 0.6404860 0.054418 0.0880591 NA
22 51223637 rs375798137 G A 0.0014882 0.0039732 0.7099994 0.7079822 0.054048 0.0788738 NA
22 51229805 rs9616985 T C 0.0010075 0.0033698 0.7600007 0.7649485 0.073039 0.0730831 NA
22 51232488 rs376461333 A G 0.0013419 0.0079442 0.8700001 0.8658654 0.020009 NA NA
22 51237063 rs3896457 T C 0.0024901 0.0020608 0.2300001 0.2269403 0.297960 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623764 ES:SE:LP:AF:ID  0.00179398:0.00309511:0.251812:0.623764:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.4004   ES:SE:LP:AF:ID  -0.00317976:0.00306658:0.522879:0.4004:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103596 ES:SE:LP:AF:ID  0.00849046:0.00490037:1.08092:0.103596:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  0.000239043:0.00301946:0.0268721:0.456846:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074528 ES:SE:LP:AF:ID  0.00759159:0.00595066:0.69897:0.074528:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.241034 ES:SE:LP:AF:ID  -0.000119945:0.00344837:0.0132283:0.241034:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913482 ES:SE:LP:AF:ID  -0.000721411:0.00430238:0.0604807:0.913482:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116339 ES:SE:LP:AF:ID  0.00352684:0.00288982:0.657577:0.116339:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.06725  ES:SE:LP:AF:ID  0.00205805:0.00423619:0.200659:0.06725:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515574 ES:SE:LP:AF:ID  -0.00189465:0.00214085:0.420216:0.515574:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032993 ES:SE:LP:AF:ID  -0.000800539:0.00539829:0.0555173:0.032993:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03661  ES:SE:LP:AF:ID  -0.00173959:0.0049033:0.142668:0.03661:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036724 ES:SE:LP:AF:ID  -0.00134604:0.00488488:0.107905:0.036724:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036428 ES:SE:LP:AF:ID  -0.00149995:0.00491962:0.119186:0.036428:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016399 ES:SE:LP:AF:ID  0.00349738:0.00757411:0.19382:0.016399:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036965 ES:SE:LP:AF:ID  -0.00125134:0.00486534:0.09691:0.036965:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037059 ES:SE:LP:AF:ID  -0.00126134:0.00484881:0.102373:0.037059:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101199 ES:SE:LP:AF:ID  -0.0031319:0.00353171:0.420216:0.101199:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959104 ES:SE:LP:AF:ID  0.00326831:0.00467654:0.318759:0.959104:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.03144  ES:SE:LP:AF:ID  -0.00551633:0.00849123:0.283997:0.03144:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053289 ES:SE:LP:AF:ID  -0.00342324:0.00674838:0.21467:0.053289:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036581 ES:SE:LP:AF:ID  -0.00129331:0.00488003:0.102373:0.036581:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036895 ES:SE:LP:AF:ID  -0.00155698:0.00483567:0.124939:0.036895:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843224 ES:SE:LP:AF:ID  -0.00192262:0.00250438:0.356547:0.843224:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055921 ES:SE:LP:AF:ID  0.00640005:0.00405503:0.958607:0.055921:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122325 ES:SE:LP:AF:ID  0.00352548:0.00274122:0.69897:0.122325:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025687 ES:SE:LP:AF:ID  0.00027816:0.0067468:0.0132283:0.025687:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121565 ES:SE:LP:AF:ID  0.00366842:0.00274236:0.744727:0.121565:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132344 ES:SE:LP:AF:ID  0.00205509:0.00270294:0.346787:0.132344:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011163 ES:SE:LP:AF:ID  -0.0103717:0.00980831:0.537602:0.011163:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005713 ES:SE:LP:AF:ID  -0.0170367:0.0126704:0.744727:0.005713:rs61770167
1   742813  rs112573343 C   T   .   PASS    AF=0.00227  ES:SE:LP:AF:ID  -0.0242011:0.0213251:0.585027:0.00227:rs112573343
1   746189  rs139221807 A   G   .   PASS    AF=0.00103  ES:SE:LP:AF:ID  -0.0387717:0.0348808:0.568636:0.00103:rs139221807
1   752478  rs146277091 G   A   .   PASS    AF=0.036812 ES:SE:LP:AF:ID  -0.00160823:0.00478676:0.130768:0.036812:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838963 ES:SE:LP:AF:ID  -0.00285399:0.00242559:0.619789:0.838963:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838592 ES:SE:LP:AF:ID  -0.00247156:0.002423:0.508638:0.838592:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86976  ES:SE:LP:AF:ID  -0.00404164:0.00259988:0.920819:0.86976:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129881 ES:SE:LP:AF:ID  0.00389271:0.00260527:0.853872:0.129881:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037319 ES:SE:LP:AF:ID  -0.00206733:0.00470583:0.180456:0.037319:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037564 ES:SE:LP:AF:ID  -0.00174166:0.00467596:0.148742:0.037564:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869107 ES:SE:LP:AF:ID  -0.00367066:0.0025948:0.79588:0.869107:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869206 ES:SE:LP:AF:ID  -0.00353235:0.00259585:0.769551:0.869206:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037521 ES:SE:LP:AF:ID  -0.00187381:0.00469631:0.161151:0.037521:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.86911  ES:SE:LP:AF:ID  -0.00367188:0.00259475:0.79588:0.86911:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005119 ES:SE:LP:AF:ID  -0.0104718:0.0133284:0.366532:0.005119:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005085 ES:SE:LP:AF:ID  -0.010209:0.0133636:0.356547:0.005085:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838046 ES:SE:LP:AF:ID  -0.00247713:0.00241632:0.508638:0.838046:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037534 ES:SE:LP:AF:ID  -0.00207676:0.00470294:0.180456:0.037534:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838679 ES:SE:LP:AF:ID  -0.00235272:0.0024231:0.481486:0.838679:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013778 ES:SE:LP:AF:ID  -0.00726321:0.00845545:0.408935:0.013778:rs181660517