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-7926/UKB-b-7926_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7926/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:04 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-7926/UKB-b-7926_data.vcf.gz ...
Read summary statistics for 8886658 SNPs.
Dropped 8234 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, 1286736 SNPs remain.
After merging with regression SNP LD, 1286736 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0147 (0.0013)
Lambda GC: 1.1448
Mean Chi^2: 1.1609
Intercept: 1.0284 (0.0064)
Ratio: 0.1765 (0.0395)
Analysis finished at Thu Oct 17 14:43:28 2019
Total time elapsed: 2.0m:24.03s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9472,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 3.3806e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 54,
    "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": 89353,
    "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": 1286736,
    "ldsc_nsnp_merge_regression_ld": 1286736,
    "ldsc_observed_scale_h2_beta": 0.0147,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0284,
    "ldsc_intercept_se": 0.0064,
    "ldsc_lambda_gc": 1.1448,
    "ldsc_mean_chisq": 1.1609,
    "ldsc_ratio": 0.1765
}

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 8878463 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 8886658 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 8.646538e+00 5.759635e+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 7.878518e+07 5.634378e+07 828.0000000 3.242070e+07 6.934394e+07 1.145590e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 3.400000e-06 2.638700e-03 -0.0277384 -1.081000e-03 1.400000e-06 1.080200e-03 2.869650e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.081500e-03 1.489100e-03 0.0007784 9.244000e-04 1.398700e-03 2.845700e-03 1.804980e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.817192e-01 2.938617e-01 0.0000000 2.200002e-01 4.799997e-01 7.400005e-01 1.000000e+00 ▇▇▇▆▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.817207e-01 2.938374e-01 0.0000000 2.224054e-01 4.751929e-01 7.363716e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.228938e-01 2.588456e-01 0.0041250 2.186500e-02 1.053280e-01 3.519420e-01 9.958750e-01 ▇▂▁▁▁
numeric AF_reference 89353 0.9899453 NA NA NA NA NA NA NA 2.229692e-01 2.507767e-01 0.0000000 1.916930e-02 1.224040e-01 3.498400e-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 0.0000880 0.0014325 0.9500000 0.9509896 0.623772 0.7821490 NA
1 54676 rs2462492 C T -0.0000348 0.0014191 0.9800000 0.9804411 0.400421 NA NA
1 86028 rs114608975 T C 0.0008157 0.0022686 0.7199992 0.7191607 0.103585 0.0277556 NA
1 91536 rs6702460 G T 0.0015477 0.0013972 0.2700001 0.2679913 0.456816 0.4207270 NA
1 234313 rs8179466 C T -0.0019045 0.0027538 0.4899999 0.4891964 0.074526 NA NA
1 534192 rs6680723 C T 0.0006894 0.0015961 0.6700003 0.6657810 0.240962 NA NA
1 546697 rs12025928 A G 0.0007047 0.0019913 0.7199992 0.7234198 0.913481 NA NA
1 693731 rs12238997 A G 0.0002003 0.0013372 0.8800001 0.8809186 0.116349 0.1417730 NA
1 705882 rs72631875 G A -0.0018821 0.0019602 0.3400001 0.3369741 0.067273 0.0315495 NA
1 706368 rs55727773 A G -0.0002602 0.0009908 0.7899998 0.7928104 0.515645 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0007446 0.0011954 0.5300002 0.5333796 0.137923 0.2052720 NA
22 51219387 rs9616832 T C -0.0019363 0.0015518 0.2099999 0.2121205 0.073721 0.0654952 NA
22 51219704 rs147475742 G A -0.0002922 0.0020797 0.8900000 0.8882792 0.041940 0.0473243 NA
22 51221190 rs369304721 G A -0.0024984 0.0020764 0.2300001 0.2288800 0.049710 NA NA
22 51221731 rs115055839 T C -0.0018292 0.0015528 0.2399999 0.2387850 0.073212 0.0625000 NA
22 51222100 rs114553188 G T 0.0006173 0.0018276 0.7400005 0.7355323 0.054457 0.0880591 NA
22 51223637 rs375798137 G A 0.0006733 0.0018365 0.7099994 0.7139099 0.054086 0.0788738 NA
22 51229805 rs9616985 T C -0.0018380 0.0015584 0.2399999 0.2382335 0.073046 0.0730831 NA
22 51232488 rs376461333 A G 0.0048720 0.0036677 0.1800002 0.1840630 0.020058 NA NA
22 51237063 rs3896457 T C -0.0001202 0.0009528 0.9000000 0.8996172 0.297994 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623772 ES:SE:LP:AF:ID  8.80498e-05:0.00143254:0.0222764:0.623772:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400421 ES:SE:LP:AF:ID  -3.47896e-05:0.00141906:0.00877392:0.400421:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103585 ES:SE:LP:AF:ID  0.000815734:0.00226857:0.142668:0.103585:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456816 ES:SE:LP:AF:ID  0.00154769:0.00139721:0.568636:0.456816:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074526 ES:SE:LP:AF:ID  -0.00190448:0.00275378:0.309804:0.074526:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240962 ES:SE:LP:AF:ID  0.000689424:0.00159609:0.173925:0.240962:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913481 ES:SE:LP:AF:ID  0.000704691:0.00199126:0.142668:0.913481:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116349 ES:SE:LP:AF:ID  0.000200313:0.00133716:0.0555173:0.116349:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067273 ES:SE:LP:AF:ID  -0.00188206:0.00196015:0.468521:0.067273:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -0.000260238:0.000990768:0.102373:0.515645:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032976 ES:SE:LP:AF:ID  -0.000154866:0.00249885:0.0222764:0.032976:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.03659  ES:SE:LP:AF:ID  -0.000151844:0.00226972:0.0222764:0.03659:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036705 ES:SE:LP:AF:ID  -2.5492e-05:0.00226117:0.00436481:0.036705:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036407 ES:SE:LP:AF:ID  0.000217533:0.00227739:0.0362122:0.036407:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016397 ES:SE:LP:AF:ID  -0.00449685:0.0035068:0.69897:0.016397:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036944 ES:SE:LP:AF:ID  -0.000414396:0.00225221:0.0705811:0.036944:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037043 ES:SE:LP:AF:ID  -0.000501894:0.00224444:0.0861861:0.037043:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101233 ES:SE:LP:AF:ID  0.000134919:0.00163427:0.0315171:0.101233:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959133 ES:SE:LP:AF:ID  0.000415941:0.00216481:0.0705811:0.959133:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031452 ES:SE:LP:AF:ID  0.00084788:0.00392739:0.0809219:0.031452:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053268 ES:SE:LP:AF:ID  -0.00114555:0.00312365:0.148742:0.053268:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036561 ES:SE:LP:AF:ID  -1.02256e-05:0.00225893:-0:0.036561:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036873 ES:SE:LP:AF:ID  -0.000407289:0.00223851:0.0655015:0.036873:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.84323  ES:SE:LP:AF:ID  0.000215914:0.00115906:0.0705811:0.84323:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055944 ES:SE:LP:AF:ID  0.00126909:0.00187617:0.30103:0.055944:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122334 ES:SE:LP:AF:ID  0.000387197:0.00126845:0.119186:0.122334:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025728 ES:SE:LP:AF:ID  0.00210192:0.00311969:0.30103:0.025728:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121576 ES:SE:LP:AF:ID  0.000286083:0.00126898:0.0861861:0.121576:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132332 ES:SE:LP:AF:ID  0.000361145:0.00125081:0.113509:0.132332:rs79010578
1   736689  rs181876450 T   C   .   PASS    AF=0.011138 ES:SE:LP:AF:ID  0.0032828:0.00454713:0.327902:0.011138:rs181876450
1   740284  rs61770167  C   T   .   PASS    AF=0.005701 ES:SE:LP:AF:ID  0.00767005:0.00587018:0.721246:0.005701:rs61770167
1   752478  rs146277091 G   A   .   PASS    AF=0.036789 ES:SE:LP:AF:ID  -0.00013858:0.00221585:0.0222764:0.036789:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838985 ES:SE:LP:AF:ID  8.42277e-05:0.00112251:0.0268721:0.838985:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838616 ES:SE:LP:AF:ID  0.000108157:0.00112133:0.0362122:0.838616:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869779 ES:SE:LP:AF:ID  -0.000283227:0.0012031:0.091515:0.869779:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129873 ES:SE:LP:AF:ID  2.27272e-05:0.00120556:0.00877392:0.129873:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037298 ES:SE:LP:AF:ID  -0.000508864:0.00217834:0.0861861:0.037298:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037541 ES:SE:LP:AF:ID  -0.000608809:0.00216458:0.107905:0.037541:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869122 ES:SE:LP:AF:ID  -0.000206455:0.00120078:0.0655015:0.869122:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869218 ES:SE:LP:AF:ID  -0.000258554:0.00120125:0.0809219:0.869218:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.0375   ES:SE:LP:AF:ID  -0.000595196:0.00217392:0.107905:0.0375:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869125 ES:SE:LP:AF:ID  -0.000201729:0.00120076:0.0604807:0.869125:rs3131967
1   754433  rs150578204 G   A   .   PASS    AF=0.005119 ES:SE:LP:AF:ID  -0.00183063:0.00616771:0.113509:0.005119:rs150578204
1   754458  rs142682604 G   T   .   PASS    AF=0.005085 ES:SE:LP:AF:ID  -0.00181559:0.00618394:0.113509:0.005085:rs142682604
1   754503  rs3115859   G   A   .   PASS    AF=0.838068 ES:SE:LP:AF:ID  0.000206492:0.00111822:0.0705811:0.838068:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037514 ES:SE:LP:AF:ID  -0.0004677:0.00217697:0.0809219:0.037514:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838697 ES:SE:LP:AF:ID  0.000162835:0.00112136:0.0555173:0.838697:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013781 ES:SE:LP:AF:ID  0.00189383:0.00391242:0.200659:0.013781:rs181660517
1   755435  rs184270342 T   G   .   PASS    AF=0.005531 ES:SE:LP:AF:ID  -0.000810708:0.00604905:0.05061:0.005531:rs184270342
1   755775  rs3131965   A   G   .   PASS    AF=0.839797 ES:SE:LP:AF:ID  2.10953e-05:0.00113647:0.00436481:0.839797:rs3131965