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-11161/UKB-b-11161_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11161/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:40:18 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-11161/UKB-b-11161_data.vcf.gz ...
Read summary statistics for 6357444 SNPs.
Dropped 3297 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, 1236156 SNPs remain.
After merging with regression SNP LD, 1236156 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0066 (0.0011)
Lambda GC: 1.0829
Mean Chi^2: 1.0849
Intercept: 1.024 (0.0067)
Ratio: 0.283 (0.0793)
Analysis finished at Thu Oct 17 14:41:32 2019
Total time elapsed: 1.0m:13.46s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9292,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 2.9377e-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": 58225,
    "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": 1236156,
    "ldsc_nsnp_merge_regression_ld": 1236156,
    "ldsc_observed_scale_h2_beta": 0.0066,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.024,
    "ldsc_intercept_se": 0.0067,
    "ldsc_lambda_gc": 1.0829,
    "ldsc_mean_chisq": 1.0849,
    "ldsc_ratio": 0.2827
}

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 6354168 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 6357444 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 8.667677e+00 5.763503e+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 7.857897e+07 5.650035e+07 828.0000000 3.201288e+07 6.900993e+07 1.144980e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.900000e-06 6.016000e-04 -0.0051474 -3.474000e-04 -7.000000e-07 3.485000e-04 5.748600e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 5.430000e-04 2.066000e-04 0.0003364 3.744000e-04 4.601000e-04 6.612000e-04 2.918500e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.869973e-01 2.922248e-01 0.0000001 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 4.869975e-01 2.921992e-01 0.0000001 2.309131e-01 4.819419e-01 7.401711e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.982940e-01 2.564301e-01 0.0262890 8.203300e-02 2.110290e-01 4.610590e-01 9.737110e-01 ▇▃▂▂▁
numeric AF_reference 58225 0.9908414 NA NA NA NA NA NA NA 2.955521e-01 2.490086e-01 0.0000000 9.125400e-02 2.200480e-01 4.526760e-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 0.0001351 0.0006190 0.8300000 0.8272626 0.623778 0.7821490 NA
1 54676 rs2462492 C T -0.0007142 0.0006132 0.2399999 0.2441504 0.400420 NA NA
1 86028 rs114608975 T C -0.0005711 0.0009804 0.5600000 0.5602090 0.103559 0.0277556 NA
1 91536 rs6702460 G T -0.0005163 0.0006038 0.3900004 0.3925311 0.456853 0.4207270 NA
1 234313 rs8179466 C T 0.0020148 0.0011908 0.0909997 0.0906453 0.074493 NA NA
1 534192 rs6680723 C T 0.0004919 0.0006898 0.4799997 0.4757536 0.240946 NA NA
1 546697 rs12025928 A G 0.0000782 0.0008603 0.9299999 0.9275544 0.913466 NA NA
1 693731 rs12238997 A G 0.0002161 0.0005780 0.7099994 0.7085395 0.116320 0.1417730 NA
1 705882 rs72631875 G A 0.0006368 0.0008470 0.4500005 0.4521357 0.067275 0.0315495 NA
1 706368 rs55727773 A G -0.0008200 0.0004281 0.0549997 0.0554518 0.515632 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C 0.0020629 0.0006690 0.0020000 0.0020472 0.073634 0.0826677 NA
22 51219006 rs28729663 G A 0.0003242 0.0005164 0.5300002 0.5301191 0.137978 0.2052720 NA
22 51219387 rs9616832 T C 0.0020069 0.0006704 0.0028000 0.0027574 0.073754 0.0654952 NA
22 51219704 rs147475742 G A 0.0019496 0.0008984 0.0299999 0.0299996 0.041956 0.0473243 NA
22 51221190 rs369304721 G A 0.0027656 0.0008968 0.0020000 0.0020441 0.049743 NA NA
22 51221731 rs115055839 T C 0.0020262 0.0006708 0.0025000 0.0025239 0.073246 0.0625000 NA
22 51222100 rs114553188 G T -0.0014057 0.0007897 0.0749998 0.0750869 0.054465 0.0880591 NA
22 51223637 rs375798137 G A -0.0013951 0.0007936 0.0790005 0.0787423 0.054094 0.0788738 NA
22 51229805 rs9616985 T C 0.0020154 0.0006732 0.0028000 0.0027564 0.073081 0.0730831 NA
22 51237063 rs3896457 T C -0.0004124 0.0004118 0.3200000 0.3165919 0.297941 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623778 ES:SE:LP:AF:ID  0.000135071:0.000618985:0.0809219:0.623778:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40042  ES:SE:LP:AF:ID  -0.000714186:0.000613206:0.619789:0.40042:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103559 ES:SE:LP:AF:ID  -0.000571138:0.000980442:0.251812:0.103559:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456853 ES:SE:LP:AF:ID  -0.000516288:0.00060382:0.408935:0.456853:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074493 ES:SE:LP:AF:ID  0.00201477:0.00119076:1.04096:0.074493:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240946 ES:SE:LP:AF:ID  0.000491918:0.000689783:0.318759:0.240946:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913466 ES:SE:LP:AF:ID  7.82247e-05:0.000860347:0.0315171:0.913466:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.11632  ES:SE:LP:AF:ID  0.000216067:0.000578:0.148742:0.11632:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067275 ES:SE:LP:AF:ID  0.000636827:0.000847003:0.346787:0.067275:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515632 ES:SE:LP:AF:ID  -0.00082004:0.000428148:1.25964:0.515632:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.03298  ES:SE:LP:AF:ID  -0.000173135:0.00107975:0.0604807:0.03298:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036592 ES:SE:LP:AF:ID  7.21646e-06:0.000980808:0.00436481:0.036592:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036708 ES:SE:LP:AF:ID  4.34634e-05:0.000977111:0.0177288:0.036708:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036409 ES:SE:LP:AF:ID  4.24967e-05:0.000984123:0.0132283:0.036409:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.036947 ES:SE:LP:AF:ID  3.37238e-06:0.000973235:-0:0.036947:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037044 ES:SE:LP:AF:ID  4.13774e-05:0.000969891:0.0132283:0.037044:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.10124  ES:SE:LP:AF:ID  0.000478584:0.000706224:0.30103:0.10124:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.95913  ES:SE:LP:AF:ID  -0.000327464:0.00093548:0.136677:0.95913:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031445 ES:SE:LP:AF:ID  -0.00273178:0.00169779:0.958607:0.031445:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053268 ES:SE:LP:AF:ID  -0.000893136:0.00134997:0.29243:0.053268:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036562 ES:SE:LP:AF:ID  2.38175e-05:0.000976168:0.00877392:0.036562:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036879 ES:SE:LP:AF:ID  0.000113181:0.000967282:0.0409586:0.036879:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843257 ES:SE:LP:AF:ID  -0.000302052:0.000500965:0.259637:0.843257:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055921 ES:SE:LP:AF:ID  0.000605588:0.000810953:0.337242:0.055921:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122298 ES:SE:LP:AF:ID  0.000473138:0.000548302:0.408935:0.122298:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121541 ES:SE:LP:AF:ID  0.000450703:0.000548535:0.387216:0.121541:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132304 ES:SE:LP:AF:ID  0.000281074:0.000540672:0.221849:0.132304:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036791 ES:SE:LP:AF:ID  8.92662e-05:0.000957536:0.0315171:0.036791:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.838991 ES:SE:LP:AF:ID  -0.000339099:0.000485145:0.318759:0.838991:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838618 ES:SE:LP:AF:ID  -0.000295419:0.000484622:0.267606:0.838618:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869789 ES:SE:LP:AF:ID  -0.000599326:0.000520013:0.60206:0.869789:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129861 ES:SE:LP:AF:ID  0.000584802:0.000521071:0.585027:0.129861:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037302 ES:SE:LP:AF:ID  0.000118179:0.000941286:0.0457575:0.037302:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037546 ES:SE:LP:AF:ID  0.000109597:0.000935335:0.0409586:0.037546:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.86913  ES:SE:LP:AF:ID  -0.000553236:0.000518994:0.537602:0.86913:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869227 ES:SE:LP:AF:ID  -0.000565843:0.0005192:0.552842:0.869227:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037504 ES:SE:LP:AF:ID  9.41224e-05:0.000939389:0.0362122:0.037504:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869133 ES:SE:LP:AF:ID  -0.000553978:0.000518984:0.537602:0.869133:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838069 ES:SE:LP:AF:ID  -0.0002547:0.00048327:0.221849:0.838069:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037517 ES:SE:LP:AF:ID  1.77034e-05:0.000940715:0.00877392:0.037517:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838699 ES:SE:LP:AF:ID  -0.000252232:0.000484627:0.221849:0.838699:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83981  ES:SE:LP:AF:ID  -0.000358787:0.000491179:0.327902:0.83981:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869411 ES:SE:LP:AF:ID  -0.00060339:0.000518374:0.619789:0.869411:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868957 ES:SE:LP:AF:ID  -0.000584401:0.000517066:0.585027:0.868957:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867909 ES:SE:LP:AF:ID  -0.000579547:0.000516074:0.585027:0.867909:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -0.000610998:0.000517491:0.619789:0.869101:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869109 ES:SE:LP:AF:ID  -0.000610204:0.00051753:0.619789:0.869109:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  -0.000611418:0.000517542:0.619789:0.869117:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869595 ES:SE:LP:AF:ID  -0.000592159:0.000518965:0.60206:0.869595:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.037565 ES:SE:LP:AF:ID  -0.000185315:0.000935199:0.0757207:0.037565:rs114525117