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-12648/UKB-b-12648_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12648/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-12648/UKB-b-12648_data.vcf.gz ...
Read summary statistics for 6771928 SNPs.
Dropped 3952 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, 1255502 SNPs remain.
After merging with regression SNP LD, 1255502 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0068 (0.0012)
Lambda GC: 1.0691
Mean Chi^2: 1.0817
Intercept: 1.0192 (0.0073)
Ratio: 0.2354 (0.0888)
Analysis finished at Thu Oct 17 14:43:28 2019
Total time elapsed: 1.0m:23.33s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9336,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 5.2468e-06,
    "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": 62184,
    "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": 1255502,
    "ldsc_nsnp_merge_regression_ld": 1255502,
    "ldsc_observed_scale_h2_beta": 0.0068,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0192,
    "ldsc_intercept_se": 0.0073,
    "ldsc_lambda_gc": 1.0691,
    "ldsc_mean_chisq": 1.0817,
    "ldsc_ratio": 0.235
}

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 6767998 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 6771928 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 8.664024e+00 5.764558e+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 7.861066e+07 5.647360e+07 828.0000000 3.209172e+07 6.905945e+07 1.145068e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 5.200000e-06 7.529000e-04 -0.0067538 -4.113000e-04 4.000000e-07 4.166000e-04 6.873700e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.714000e-04 2.922000e-04 0.0003878 4.356000e-04 5.506000e-04 8.345000e-04 3.391200e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.893458e-01 2.917854e-01 0.0000011 2.300001e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.893448e-01 2.917583e-01 0.0000011 2.335038e-01 4.860823e-01 7.419407e-01 9.999986e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.835303e-01 2.588332e-01 0.0195770 6.700100e-02 1.903190e-01 4.428172e-01 9.804230e-01 ▇▃▂▂▁
numeric AF_reference 62184 0.9908174 NA NA NA NA NA NA NA 2.814798e-01 2.509927e-01 0.0000000 7.567890e-02 2.012780e-01 4.351040e-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 0.0004552 0.0007136 0.5199996 0.5235081 0.623763 0.7821490 NA
1 54676 rs2462492 C T 0.0003027 0.0007069 0.6700003 0.6684652 0.400432 NA NA
1 86028 rs114608975 T C -0.0003424 0.0011304 0.7600007 0.7619446 0.103549 0.0277556 NA
1 91536 rs6702460 G T 0.0017248 0.0006961 0.0129999 0.0132225 0.456866 0.4207270 NA
1 234313 rs8179466 C T 0.0004690 0.0013724 0.7300002 0.7325509 0.074519 NA NA
1 534192 rs6680723 C T 0.0000463 0.0007952 0.9500000 0.9535450 0.240923 NA NA
1 546697 rs12025928 A G -0.0009121 0.0009918 0.3599996 0.3577686 0.913452 NA NA
1 693731 rs12238997 A G 0.0019778 0.0006662 0.0030000 0.0029918 0.116339 0.1417730 NA
1 705882 rs72631875 G A 0.0007341 0.0009764 0.4500005 0.4521404 0.067289 0.0315495 NA
1 706368 rs55727773 A G -0.0008293 0.0004936 0.0929994 0.0929247 0.515638 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A -0.0004104 0.0005954 0.4899999 0.4906082 0.137972 0.2052720 NA
22 51219387 rs9616832 T C 0.0005510 0.0007729 0.4799997 0.4759494 0.073734 0.0654952 NA
22 51219704 rs147475742 G A -0.0006127 0.0010358 0.5500004 0.5542084 0.041941 0.0473243 NA
22 51221190 rs369304721 G A 0.0002017 0.0010340 0.8499999 0.8453398 0.049723 NA NA
22 51221731 rs115055839 T C 0.0006455 0.0007734 0.4000000 0.4039424 0.073224 0.0625000 NA
22 51222100 rs114553188 G T -0.0014547 0.0009102 0.1100001 0.1099826 0.054493 0.0880591 NA
22 51223637 rs375798137 G A -0.0015693 0.0009146 0.0860003 0.0861750 0.054122 0.0788738 NA
22 51229805 rs9616985 T C 0.0005953 0.0007762 0.4400003 0.4431341 0.073060 0.0730831 NA
22 51232488 rs376461333 A G -0.0025692 0.0018276 0.1600000 0.1597864 0.020057 NA NA
22 51237063 rs3896457 T C 0.0005074 0.0004747 0.2900000 0.2851308 0.297978 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  0.000455234:0.000713592:0.283997:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400432 ES:SE:LP:AF:ID  0.000302747:0.000706931:0.173925:0.400432:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103549 ES:SE:LP:AF:ID  -0.000342427:0.00113039:0.119186:0.103549:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456866 ES:SE:LP:AF:ID  0.0017248:0.000696124:1.88606:0.456866:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074519 ES:SE:LP:AF:ID  0.000468979:0.00137235:0.136677:0.074519:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240923 ES:SE:LP:AF:ID  4.63249e-05:0.0007952:0.0222764:0.240923:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913452 ES:SE:LP:AF:ID  -0.000912088:0.000991804:0.443698:0.913452:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116339 ES:SE:LP:AF:ID  0.00197778:0.000666239:2.52288:0.116339:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067289 ES:SE:LP:AF:ID  0.00073408:0.000976363:0.346787:0.067289:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515638 ES:SE:LP:AF:ID  -0.000829334:0.000493602:1.03152:0.515638:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032999 ES:SE:LP:AF:ID  -0.000122971:0.00124444:0.0362122:0.032999:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036615 ES:SE:LP:AF:ID  0.000132217:0.00113034:0.0409586:0.036615:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036732 ES:SE:LP:AF:ID  0.000211794:0.00112607:0.0705811:0.036732:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036432 ES:SE:LP:AF:ID  0.000130107:0.00113415:0.0409586:0.036432:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036971 ES:SE:LP:AF:ID  0.000155938:0.00112161:0.05061:0.036971:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037068 ES:SE:LP:AF:ID  0.00011291:0.00111775:0.0362122:0.037068:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10121  ES:SE:LP:AF:ID  -0.000341547:0.000814223:0.173925:0.10121:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959108 ES:SE:LP:AF:ID  -0.00031246:0.00107813:0.113509:0.959108:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031448 ES:SE:LP:AF:ID  0.000978194:0.00195699:0.207608:0.031448:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053259 ES:SE:LP:AF:ID  -0.000760092:0.00155662:0.200659:0.053259:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036587 ES:SE:LP:AF:ID  5.42409e-05:0.00112496:0.0177288:0.036587:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036902 ES:SE:LP:AF:ID  0.00032898:0.00111472:0.113509:0.036902:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843209 ES:SE:LP:AF:ID  -0.00145285:0.000577419:1.92082:0.843209:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055938 ES:SE:LP:AF:ID  0.00203951:0.000934741:1.5376:0.055938:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122328 ES:SE:LP:AF:ID  0.00164602:0.000631969:2.03621:0.122328:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025708 ES:SE:LP:AF:ID  0.0012641:0.00155467:0.376751:0.025708:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121572 ES:SE:LP:AF:ID  0.00165116:0.000632233:2.04576:0.121572:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132346 ES:SE:LP:AF:ID  0.00128957:0.000623167:1.40894:0.132346:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036817 ES:SE:LP:AF:ID  0.000132158:0.00110348:0.0457575:0.036817:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838925 ES:SE:LP:AF:ID  -0.0010389:0.000559179:1.20066:0.838925:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838557 ES:SE:LP:AF:ID  -0.00106306:0.000558582:1.24413:0.838557:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869744 ES:SE:LP:AF:ID  -0.00128346:0.000599354:1.49485:0.869744:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129904 ES:SE:LP:AF:ID  0.00139854:0.000600577:1.69897:0.129904:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037328 ES:SE:LP:AF:ID  0.000246312:0.00108478:0.0861861:0.037328:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037572 ES:SE:LP:AF:ID  0.000182529:0.00107791:0.0604807:0.037572:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869089 ES:SE:LP:AF:ID  -0.00135526:0.000598188:1.63827:0.869089:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869185 ES:SE:LP:AF:ID  -0.00133464:0.000598424:1.58503:0.869185:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.03753  ES:SE:LP:AF:ID  0.000226925:0.00108258:0.0809219:0.03753:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869092 ES:SE:LP:AF:ID  -0.00135548:0.000598176:1.63827:0.869092:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838009 ES:SE:LP:AF:ID  -0.00108357:0.000557026:1.284:0.838009:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037543 ES:SE:LP:AF:ID  0.000248776:0.00108411:0.0861861:0.037543:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.83864  ES:SE:LP:AF:ID  -0.00111299:0.000558594:1.33724:0.83864:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83975  ES:SE:LP:AF:ID  -0.000982669:0.000566145:1.08092:0.83975:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869368 ES:SE:LP:AF:ID  -0.00128478:0.000597475:1.49485:0.869368:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868914 ES:SE:LP:AF:ID  -0.00128074:0.000595969:1.49485:0.868914:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867871 ES:SE:LP:AF:ID  -0.00134242:0.000594835:1.61979:0.867871:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869058 ES:SE:LP:AF:ID  -0.00128857:0.000596459:1.50864:0.869058:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869067 ES:SE:LP:AF:ID  -0.00128906:0.000596505:1.50864:0.869067:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869075 ES:SE:LP:AF:ID  -0.00129236:0.000596519:1.52288:0.869075:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869552 ES:SE:LP:AF:ID  -0.00126575:0.000598158:1.46852:0.869552:rs3131954