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-8846/UKB-b-8846_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8846/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:04 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8846/UKB-b-8846_data.vcf.gz ...
Read summary statistics for 9282291 SNPs.
Dropped 10184 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, 1287888 SNPs remain.
After merging with regression SNP LD, 1287888 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0171 (0.0015)
Lambda GC: 1.2831
Mean Chi^2: 1.2905
Intercept: 1.1349 (0.0083)
Ratio: 0.4646 (0.0287)
Analysis finished at Thu Oct 17 14:43:37 2019
Total time elapsed: 1.0m:32.91s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9486,
    "inflation_factor": 1.2544,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 5,
    "n_p_sig": 16,
    "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": 110597,
    "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": 1287888,
    "ldsc_nsnp_merge_regression_ld": 1287888,
    "ldsc_observed_scale_h2_beta": 0.0171,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.1349,
    "ldsc_intercept_se": 0.0083,
    "ldsc_lambda_gc": 1.2831,
    "ldsc_mean_chisq": 1.2905,
    "ldsc_ratio": 0.4644
}

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 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 9272158 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 9282291 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 8.635485e+00 5.754380e+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 7.880793e+07 5.631026e+07 828.0000000 3.249797e+07 6.938790e+07 1.145385e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.460000e-05 3.748300e-03 -0.0552981 -1.397300e-03 9.700000e-06 1.425200e-03 4.179180e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.733600e-03 2.145300e-03 0.0009230 1.109500e-03 1.748100e-03 3.747800e-03 2.294430e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.660845e-01 2.970833e-01 0.0000000 2.000000e-01 4.500005e-01 7.199992e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.660847e-01 2.970571e-01 0.0000000 2.001671e-01 4.534807e-01 7.232548e-01 1.000000e+00 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.142374e-01 2.578545e-01 0.0024380 1.769900e-02 9.312900e-02 3.365900e-01 9.975620e-01 ▇▂▁▁▁
numeric AF_reference 110597 0.9880852 NA NA NA NA NA NA NA 2.151586e-01 2.496648e-01 0.0000000 1.497600e-02 1.114220e-01 3.362620e-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 0.0008591 0.0016977 0.6100002 0.6128215 0.623756 0.7821490 NA
1 54676 rs2462492 C T -0.0005648 0.0016819 0.7400005 0.7369932 0.400407 NA NA
1 86028 rs114608975 T C -0.0017332 0.0026893 0.5199996 0.5192665 0.103550 0.0277556 NA
1 91536 rs6702460 G T 0.0007454 0.0016560 0.6499995 0.6526266 0.456853 0.4207270 NA
1 234313 rs8179466 C T 0.0033567 0.0032653 0.2999998 0.3039466 0.074509 NA NA
1 534192 rs6680723 C T -0.0020911 0.0018916 0.2700001 0.2689748 0.240953 NA NA
1 546697 rs12025928 A G 0.0004739 0.0023599 0.8400000 0.8408377 0.913475 NA NA
1 693731 rs12238997 A G 0.0025962 0.0015853 0.1000000 0.1014777 0.116328 0.1417730 NA
1 705882 rs72631875 G A -0.0031157 0.0023231 0.1800002 0.1798553 0.067285 0.0315495 NA
1 706368 rs55727773 A G -0.0026625 0.0011743 0.0230001 0.0233679 0.515650 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0011804 0.0014175 0.4000000 0.4049963 0.137957 0.2052720 NA
22 51219387 rs9616832 T C 0.0019625 0.0018400 0.2900000 0.2861605 0.073749 0.0654952 NA
22 51219704 rs147475742 G A 0.0014716 0.0024655 0.5500004 0.5505825 0.041962 0.0473243 NA
22 51221190 rs369304721 G A 0.0016397 0.0024615 0.5099998 0.5053191 0.049736 NA NA
22 51221731 rs115055839 T C 0.0019966 0.0018411 0.2800000 0.2781639 0.073240 0.0625000 NA
22 51222100 rs114553188 G T -0.0004073 0.0021676 0.8499999 0.8509343 0.054464 0.0880591 NA
22 51223637 rs375798137 G A -0.0005148 0.0021780 0.8100000 0.8131582 0.054093 0.0788738 NA
22 51229805 rs9616985 T C 0.0020689 0.0018478 0.2599998 0.2628538 0.073075 0.0730831 NA
22 51232488 rs376461333 A G -0.0048843 0.0043528 0.2599998 0.2618261 0.020044 NA NA
22 51237063 rs3896457 T C 0.0024940 0.0011301 0.0269998 0.0273270 0.297976 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623756 ES:SE:LP:AF:ID  0.000859111:0.00169768:0.21467:0.623756:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400407 ES:SE:LP:AF:ID  -0.000564849:0.00168191:0.130768:0.400407:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.10355  ES:SE:LP:AF:ID  -0.00173321:0.00268933:0.283997:0.10355:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456853 ES:SE:LP:AF:ID  0.000745406:0.00165603:0.187087:0.456853:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074509 ES:SE:LP:AF:ID  0.00335672:0.00326527:0.522879:0.074509:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240953 ES:SE:LP:AF:ID  -0.00209108:0.00189165:0.568636:0.240953:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913475 ES:SE:LP:AF:ID  0.000473926:0.00235993:0.0757207:0.913475:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116328 ES:SE:LP:AF:ID  0.00259623:0.00158526:1:0.116328:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067285 ES:SE:LP:AF:ID  -0.00311569:0.00232306:0.744727:0.067285:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -0.0026625:0.00117427:1.63827:0.51565:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.033004 ES:SE:LP:AF:ID  -0.00236814:0.00296042:0.376751:0.033004:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036619 ES:SE:LP:AF:ID  -0.00229228:0.00268912:0.408935:0.036619:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036735 ES:SE:LP:AF:ID  -0.00210783:0.00267895:0.366532:0.036735:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036435 ES:SE:LP:AF:ID  -0.00220784:0.00269823:0.387216:0.036435:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016407 ES:SE:LP:AF:ID  0.00965397:0.00415445:1.69897:0.016407:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036975 ES:SE:LP:AF:ID  -0.00229943:0.00266832:0.408935:0.036975:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037072 ES:SE:LP:AF:ID  -0.00224372:0.00265918:0.39794:0.037072:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101211 ES:SE:LP:AF:ID  0.00059753:0.00193744:0.119186:0.101211:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959095 ES:SE:LP:AF:ID  0.00168863:0.00256466:0.29243:0.959095:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031447 ES:SE:LP:AF:ID  0.00465459:0.00465647:0.49485:0.031447:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053252 ES:SE:LP:AF:ID  -0.00472713:0.00370406:0.69897:0.053252:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036588 ES:SE:LP:AF:ID  -0.00238003:0.00267643:0.431798:0.036588:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036905 ES:SE:LP:AF:ID  -0.00242613:0.00265207:0.443698:0.036905:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843209 ES:SE:LP:AF:ID  -0.0017929:0.00137382:0.721246:0.843209:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055915 ES:SE:LP:AF:ID  0.00071122:0.00222429:0.124939:0.055915:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12231  ES:SE:LP:AF:ID  0.0024271:0.00150377:0.958607:0.12231:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025714 ES:SE:LP:AF:ID  -0.00253312:0.00369872:0.309804:0.025714:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121553 ES:SE:LP:AF:ID  0.00253541:0.0015044:1.03621:0.121553:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132331 ES:SE:LP:AF:ID  0.000276183:0.00148271:0.0705811:0.132331:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011136 ES:SE:LP:AF:ID  -0.00117788:0.00539065:0.0809219:0.011136:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005697 ES:SE:LP:AF:ID  0.0128263:0.00696104:1.18709:0.005697:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036819 ES:SE:LP:AF:ID  -0.00193573:0.00262526:0.337242:0.036819:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83895  ES:SE:LP:AF:ID  -0.00160338:0.00133045:0.638272:0.83895:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838578 ES:SE:LP:AF:ID  -0.00167638:0.00132902:0.677781:0.838578:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869774 ES:SE:LP:AF:ID  -0.00222535:0.00142608:0.920819:0.869774:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129877 ES:SE:LP:AF:ID  0.00239212:0.001429:1.02687:0.129877:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037331 ES:SE:LP:AF:ID  -0.00212702:0.00258074:0.387216:0.037331:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037574 ES:SE:LP:AF:ID  -0.00210558:0.00256443:0.387216:0.037574:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869116 ES:SE:LP:AF:ID  -0.0022762:0.00142328:0.958607:0.869116:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869214 ES:SE:LP:AF:ID  -0.00232214:0.00142385:1:0.869214:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037532 ES:SE:LP:AF:ID  -0.00230082:0.00257553:0.431798:0.037532:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869119 ES:SE:LP:AF:ID  -0.00229332:0.00142326:0.958607:0.869119:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005124 ES:SE:LP:AF:ID  0.00147397:0.00730627:0.0757207:0.005124:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.00509  ES:SE:LP:AF:ID  0.00106272:0.00732542:0.0555173:0.00509:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838031 ES:SE:LP:AF:ID  -0.00155181:0.00132533:0.619789:0.838031:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037545 ES:SE:LP:AF:ID  -0.00222501:0.00257916:0.408935:0.037545:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838662 ES:SE:LP:AF:ID  -0.00157177:0.00132906:0.619789:0.838662:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013774 ES:SE:LP:AF:ID  0.000626105:0.00463914:0.05061:0.013774:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005544 ES:SE:LP:AF:ID  0.0130958:0.00716056:1.17393:0.005544:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839775 ES:SE:LP:AF:ID  -0.00136291:0.00134703:0.508638:0.839775:rs3131965