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-18712/UKB-b-18712_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18712/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-18712/UKB-b-18712_data.vcf.gz ...
Read summary statistics for 8994996 SNPs.
Dropped 8704 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, 1287117 SNPs remain.
After merging with regression SNP LD, 1287117 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.007 (0.0012)
Lambda GC: 1.0946
Mean Chi^2: 1.1031
Intercept: 1.0399 (0.0067)
Ratio: 0.3872 (0.0653)
Analysis finished at Thu Oct 17 14:42:00 2019
Total time elapsed: 1.0m:40.52s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9476,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "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": 93291,
    "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": 1287117,
    "ldsc_nsnp_merge_regression_ld": 1287117,
    "ldsc_observed_scale_h2_beta": 0.007,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0399,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0946,
    "ldsc_mean_chisq": 1.1031,
    "ldsc_ratio": 0.387
}

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 8986331 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 8994996 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 8.643634e+00 5.758243e+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 7.879026e+07 5.633770e+07 828.0000000 3.243315e+07 6.935729e+07 1.145429e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.960000e-05 2.875100e-03 -0.0327632 -1.119400e-03 5.600000e-06 1.143300e-03 3.279510e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.255000e-03 1.649400e-03 0.0008214 9.788000e-04 1.497700e-03 3.091300e-03 1.904830e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.871168e-01 2.924432e-01 0.0000003 2.300001e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.871162e-01 2.924174e-01 0.0000003 2.303686e-01 4.827611e-01 7.406936e-01 9.999997e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.204410e-01 2.585765e-01 0.0036020 2.061900e-02 1.018330e-01 3.478030e-01 9.963980e-01 ▇▂▁▁▁
numeric AF_reference 93291 0.9896286 NA NA NA NA NA NA NA 2.207020e-01 2.504766e-01 0.0000000 1.797120e-02 1.192090e-01 3.460460e-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 0.0008759 0.0015116 0.5600000 0.5622950 0.623799 0.7821490 NA
1 54676 rs2462492 C T -0.0016846 0.0014974 0.2599998 0.2605735 0.400435 NA NA
1 86028 rs114608975 T C 0.0007138 0.0023945 0.7700005 0.7656171 0.103546 0.0277556 NA
1 91536 rs6702460 G T 0.0007641 0.0014746 0.5999997 0.6043243 0.456844 0.4207270 NA
1 234313 rs8179466 C T -0.0007289 0.0029075 0.8000000 0.8020525 0.074511 NA NA
1 534192 rs6680723 C T 0.0029195 0.0016844 0.0830004 0.0830414 0.240982 NA NA
1 546697 rs12025928 A G -0.0011049 0.0021015 0.5999997 0.5990568 0.913490 NA NA
1 693731 rs12238997 A G -0.0008126 0.0014111 0.5600000 0.5647259 0.116360 0.1417730 NA
1 705882 rs72631875 G A 0.0023179 0.0020688 0.2599998 0.2625264 0.067257 0.0315495 NA
1 706368 rs55727773 A G -0.0004967 0.0010456 0.6300007 0.6347606 0.515625 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0015844 0.0012616 0.2099999 0.2091524 0.137940 0.2052720 NA
22 51219387 rs9616832 T C -0.0011264 0.0016377 0.4899999 0.4916018 0.073713 0.0654952 NA
22 51219704 rs147475742 G A -0.0022121 0.0021943 0.3100002 0.3133941 0.041941 0.0473243 NA
22 51221190 rs369304721 G A -0.0030945 0.0021910 0.1600000 0.1578412 0.049706 NA NA
22 51221731 rs115055839 T C -0.0011762 0.0016388 0.4700002 0.4729200 0.073202 0.0625000 NA
22 51222100 rs114553188 G T -0.0011326 0.0019285 0.5600000 0.5570245 0.054476 0.0880591 NA
22 51223637 rs375798137 G A -0.0010630 0.0019378 0.5800000 0.5833092 0.054106 0.0788738 NA
22 51229805 rs9616985 T C -0.0012070 0.0016447 0.4600002 0.4630136 0.073038 0.0730831 NA
22 51232488 rs376461333 A G 0.0031713 0.0038730 0.4100001 0.4128784 0.020043 NA NA
22 51237063 rs3896457 T C 0.0008676 0.0010057 0.3900004 0.3883334 0.297924 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623799 ES:SE:LP:AF:ID  0.000875887:0.00151162:0.251812:0.623799:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400435 ES:SE:LP:AF:ID  -0.00168463:0.0014974:0.585027:0.400435:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103546 ES:SE:LP:AF:ID  0.000713822:0.00239447:0.113509:0.103546:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456844 ES:SE:LP:AF:ID  0.0007641:0.00147455:0.221849:0.456844:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074511 ES:SE:LP:AF:ID  -0.000728876:0.00290746:0.09691:0.074511:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240982 ES:SE:LP:AF:ID  0.00291951:0.00168436:1.08092:0.240982:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91349  ES:SE:LP:AF:ID  -0.0011049:0.00210154:0.221849:0.91349:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11636  ES:SE:LP:AF:ID  -0.000812551:0.00141108:0.251812:0.11636:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067257 ES:SE:LP:AF:ID  0.00231791:0.00206875:0.585027:0.067257:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515625 ES:SE:LP:AF:ID  -0.000496713:0.00104563:0.200659:0.515625:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032997 ES:SE:LP:AF:ID  -0.000661212:0.00263629:0.09691:0.032997:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036611 ES:SE:LP:AF:ID  -0.000684301:0.00239468:0.107905:0.036611:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036726 ES:SE:LP:AF:ID  -0.00106774:0.00238565:0.187087:0.036726:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036428 ES:SE:LP:AF:ID  -0.000815885:0.00240273:0.136677:0.036428:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016395 ES:SE:LP:AF:ID  -0.000663833:0.00370053:0.0655015:0.016395:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036967 ES:SE:LP:AF:ID  -0.000735842:0.00237612:0.119186:0.036967:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037066 ES:SE:LP:AF:ID  -0.000689189:0.00236792:0.113509:0.037066:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101202 ES:SE:LP:AF:ID  0.000262479:0.00172502:0.0555173:0.101202:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959115 ES:SE:LP:AF:ID  0.000428894:0.00228411:0.0705811:0.959115:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031442 ES:SE:LP:AF:ID  -0.00264938:0.00414623:0.283997:0.031442:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053274 ES:SE:LP:AF:ID  -0.00656619:0.00329597:1.33724:0.053274:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036581 ES:SE:LP:AF:ID  -0.000600141:0.00238335:0.09691:0.036581:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036898 ES:SE:LP:AF:ID  -0.000613139:0.00236157:0.09691:0.036898:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.8432   ES:SE:LP:AF:ID  0.000896275:0.00122306:0.337242:0.8432:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055952 ES:SE:LP:AF:ID  0.000957253:0.00197973:0.200659:0.055952:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122336 ES:SE:LP:AF:ID  -0.000712163:0.00133857:0.229148:0.122336:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025701 ES:SE:LP:AF:ID  0.00282121:0.00329416:0.408935:0.025701:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12158  ES:SE:LP:AF:ID  -0.000773377:0.00133913:0.251812:0.12158:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132365 ES:SE:LP:AF:ID  -0.00132658:0.00131992:0.508638:0.132365:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011137 ES:SE:LP:AF:ID  0.0103898:0.00479916:1.52288:0.011137:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005707 ES:SE:LP:AF:ID  -0.00742543:0.00619212:0.638272:0.005707:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036812 ES:SE:LP:AF:ID  -0.000282542:0.00233777:0.0457575:0.036812:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838931 ES:SE:LP:AF:ID  0.000866609:0.00118448:0.337242:0.838931:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838565 ES:SE:LP:AF:ID  0.000761872:0.00118322:0.283997:0.838565:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869755 ES:SE:LP:AF:ID  0.000582521:0.0012696:0.187087:0.869755:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129891 ES:SE:LP:AF:ID  -0.000641984:0.00127219:0.21467:0.129891:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037323 ES:SE:LP:AF:ID  -0.00077734:0.00229811:0.130768:0.037323:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037566 ES:SE:LP:AF:ID  -0.000822441:0.0022836:0.142668:0.037566:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  0.000510585:0.00126712:0.161151:0.869101:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869199 ES:SE:LP:AF:ID  0.000508998:0.00126763:0.161151:0.869199:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037526 ES:SE:LP:AF:ID  -0.000705856:0.00229344:0.119186:0.037526:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  0.00050141:0.0012671:0.161151:0.869104:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005117 ES:SE:LP:AF:ID  0.00796601:0.00650982:0.657577:0.005117:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005083 ES:SE:LP:AF:ID  0.00779462:0.00652694:0.638272:0.005083:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838014 ES:SE:LP:AF:ID  0.000858501:0.00117991:0.327902:0.838014:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037539 ES:SE:LP:AF:ID  -0.000797086:0.00229666:0.136677:0.037539:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838645 ES:SE:LP:AF:ID  0.000864142:0.00118323:0.327902:0.838645:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013793 ES:SE:LP:AF:ID  -0.000576296:0.00412778:0.05061:0.013793:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005545 ES:SE:LP:AF:ID  0.00338403:0.00637457:0.221849:0.005545:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839752 ES:SE:LP:AF:ID  0.000773863:0.00119922:0.283997:0.839752:rs3131965