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-15869/UKB-b-15869_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15869/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:34 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15869/UKB-b-15869_data.vcf.gz ...
Read summary statistics for 7413540 SNPs.
Dropped 5004 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, 1274307 SNPs remain.
After merging with regression SNP LD, 1274307 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0236 (0.0015)
Lambda GC: 1.2367
Mean Chi^2: 1.2785
Intercept: 1.0689 (0.0063)
Ratio: 0.2472 (0.0227)
Analysis finished at Thu Oct 17 14:46:00 2019
Total time elapsed: 1.0m:26.01s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9391,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 0,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 5,
    "n_p_sig": 36,
    "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": 68628,
    "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": 1274307,
    "ldsc_nsnp_merge_regression_ld": 1274307,
    "ldsc_observed_scale_h2_beta": 0.0236,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.0689,
    "ldsc_intercept_se": 0.0063,
    "ldsc_lambda_gc": 1.2367,
    "ldsc_mean_chisq": 1.2785,
    "ldsc_ratio": 0.2474
}

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 7408558 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 7413540 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 8.664133e+00 5.763863e+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 7.863866e+07 5.644080e+07 828.0000000 3.218205e+07 6.905723e+07 1.145152e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.490000e-05 1.136600e-03 -0.0111615 -5.790000e-04 6.300000e-06 5.982000e-04 1.214120e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 9.367000e-04 4.895000e-04 0.0004799 5.474000e-04 7.268000e-04 1.200000e-03 5.205700e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.692429e-01 2.972342e-01 0.0000000 2.000000e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.692438e-01 2.972084e-01 0.0000000 2.036949e-01 4.588707e-01 7.264411e-01 9.999999e-01 ▇▆▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.627226e-01 2.607184e-01 0.0124830 4.840500e-02 1.609515e-01 4.140030e-01 9.875170e-01 ▇▂▂▁▁
numeric AF_reference 68628 0.9907429 NA NA NA NA NA NA NA 2.614714e-01 2.525794e-01 0.0000000 5.391370e-02 1.745210e-01 4.079470e-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 -0.0002719 0.0008831 0.7600007 0.7581631 0.623782 0.7821490 NA
1 54676 rs2462492 C T 0.0000801 0.0008747 0.9299999 0.9270522 0.400397 NA NA
1 86028 rs114608975 T C -0.0002512 0.0013983 0.8600001 0.8574181 0.103566 0.0277556 NA
1 91536 rs6702460 G T 0.0007498 0.0008613 0.3800004 0.3839847 0.456836 0.4207270 NA
1 234313 rs8179466 C T -0.0011691 0.0016978 0.4899999 0.4910860 0.074517 NA NA
1 534192 rs6680723 C T -0.0002455 0.0009840 0.8000000 0.8029825 0.240936 NA NA
1 546697 rs12025928 A G 0.0012332 0.0012276 0.3200000 0.3151080 0.913502 NA NA
1 693731 rs12238997 A G -0.0000219 0.0008244 0.9800000 0.9788281 0.116349 0.1417730 NA
1 705882 rs72631875 G A -0.0017483 0.0012084 0.1499999 0.1479379 0.067272 0.0315495 NA
1 706368 rs55727773 A G -0.0013597 0.0006107 0.0259998 0.0259991 0.515605 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219006 rs28729663 G A 0.0001987 0.0007371 0.7899998 0.7874713 0.137938 0.2052720 NA
22 51219387 rs9616832 T C 0.0001367 0.0009567 0.8900000 0.8864056 0.073731 0.0654952 NA
22 51219704 rs147475742 G A -0.0017366 0.0012822 0.1800002 0.1755991 0.041939 0.0473243 NA
22 51221190 rs369304721 G A 0.0003868 0.0012801 0.7600007 0.7625099 0.049715 NA NA
22 51221731 rs115055839 T C 0.0000997 0.0009573 0.9199999 0.9170262 0.073221 0.0625000 NA
22 51222100 rs114553188 G T 0.0001913 0.0011268 0.8700001 0.8652070 0.054465 0.0880591 NA
22 51223637 rs375798137 G A 0.0002243 0.0011323 0.8400000 0.8429355 0.054096 0.0788738 NA
22 51229805 rs9616985 T C 0.0000901 0.0009608 0.9299999 0.9252517 0.073053 0.0730831 NA
22 51232488 rs376461333 A G 0.0000927 0.0022623 0.9699999 0.9672985 0.020051 NA NA
22 51237063 rs3896457 T C 0.0000563 0.0005876 0.9199999 0.9236108 0.297957 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623782 ES:SE:LP:AF:ID  -0.000271894:0.000883077:0.119186:0.623782:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400397 ES:SE:LP:AF:ID  8.00854e-05:0.000874732:0.0315171:0.400397:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103566 ES:SE:LP:AF:ID  -0.000251221:0.0013983:0.0655015:0.103566:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456836 ES:SE:LP:AF:ID  0.000749847:0.000861321:0.420216:0.456836:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074517 ES:SE:LP:AF:ID  -0.00116911:0.00169785:0.309804:0.074517:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240936 ES:SE:LP:AF:ID  -0.00024549:0.000983971:0.09691:0.240936:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913502 ES:SE:LP:AF:ID  0.00123324:0.00122764:0.49485:0.913502:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116349 ES:SE:LP:AF:ID  -2.18781e-05:0.000824403:0.00877392:0.116349:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067272 ES:SE:LP:AF:ID  -0.00174832:0.00120836:0.823909:0.067272:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515605 ES:SE:LP:AF:ID  -0.00135966:0.000610747:1.58503:0.515605:rs12029736
1   714596  rs149887893 T   C   .   PASS    AF=0.032986 ES:SE:LP:AF:ID  0.000207224:0.00154027:0.05061:0.032986:rs149887893
1   715265  rs12184267  C   T   .   PASS    AF=0.036602 ES:SE:LP:AF:ID  -5.99414e-05:0.00139903:0.0132283:0.036602:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.036718 ES:SE:LP:AF:ID  -0.000219139:0.00139373:0.0555173:0.036718:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.036419 ES:SE:LP:AF:ID  -0.000254005:0.00140373:0.0655015:0.036419:rs12184279
1   717587  rs144155419 G   A   .   PASS    AF=0.016401 ES:SE:LP:AF:ID  0.000872551:0.0021614:0.161151:0.016401:rs144155419
1   720381  rs116801199 G   T   .   PASS    AF=0.036957 ES:SE:LP:AF:ID  -0.0001976:0.00138822:0.05061:0.036957:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037053 ES:SE:LP:AF:ID  -0.000344946:0.00138347:0.09691:0.037053:rs12565286
1   722670  rs116030099 T   C   .   PASS    AF=0.101242 ES:SE:LP:AF:ID  2.55665e-05:0.00100747:0.00877392:0.101242:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959112 ES:SE:LP:AF:ID  -0.000209504:0.00133423:0.0555173:0.959112:rs2977670
1   724849  rs12126395  C   A   .   PASS    AF=0.031448 ES:SE:LP:AF:ID  0.00202626:0.00242169:0.39794:0.031448:rs12126395
1   725060  rs865924913 A   T   .   PASS    AF=0.053275 ES:SE:LP:AF:ID  0.00159861:0.00192577:0.387216:0.053275:rs865924913
1   726794  rs28454925  C   G   .   PASS    AF=0.036574 ES:SE:LP:AF:ID  -1.87312e-05:0.00139235:0.00436481:0.036574:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.036886 ES:SE:LP:AF:ID  -0.000105098:0.00137976:0.0268721:0.036886:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.843211 ES:SE:LP:AF:ID  -3.9484e-05:0.000714544:0.0177288:0.843211:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055936 ES:SE:LP:AF:ID  0.00106764:0.00115668:0.443698:0.055936:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122327 ES:SE:LP:AF:ID  0.000212161:0.000782037:0.102373:0.122327:rs58276399
1   732989  rs369030935 C   T   .   PASS    AF=0.025679 ES:SE:LP:AF:ID  0.00252608:0.00192505:0.721246:0.025679:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.12157  ES:SE:LP:AF:ID  0.000271145:0.000782366:0.136677:0.12157:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132338 ES:SE:LP:AF:ID  -0.000141767:0.000771189:0.0705811:0.132338:rs79010578
1   752478  rs146277091 G   A   .   PASS    AF=0.036802 ES:SE:LP:AF:ID  0.000282154:0.00136579:0.0757207:0.036802:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.83895  ES:SE:LP:AF:ID  0.000171876:0.000691975:0.09691:0.83895:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838577 ES:SE:LP:AF:ID  0.000136505:0.000691225:0.0757207:0.838577:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869761 ES:SE:LP:AF:ID  -8.57413e-05:0.00074168:0.0409586:0.869761:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129886 ES:SE:LP:AF:ID  0.000209574:0.000743187:0.107905:0.129886:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.037312 ES:SE:LP:AF:ID  -0.000168601:0.00134265:0.0457575:0.037312:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.037556 ES:SE:LP:AF:ID  -0.000143427:0.00133416:0.0409586:0.037556:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.869103 ES:SE:LP:AF:ID  -0.000111608:0.000740225:0.0555173:0.869103:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869201 ES:SE:LP:AF:ID  -0.000101124:0.000740518:0.05061:0.869201:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.037514 ES:SE:LP:AF:ID  -5.85962e-05:0.00133994:0.0132283:0.037514:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.869106 ES:SE:LP:AF:ID  -0.000116729:0.00074021:0.0604807:0.869106:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838032 ES:SE:LP:AF:ID  0.000194014:0.00068931:0.107905:0.838032:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.037527 ES:SE:LP:AF:ID  -1.75247e-05:0.00134183:0.00436481:0.037527:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.838663 ES:SE:LP:AF:ID  0.000183913:0.00069125:0.102373:0.838663:rs3131966
1   755240  rs181660517 T   G   .   PASS    AF=0.013783 ES:SE:LP:AF:ID  -0.00372166:0.00241189:0.920819:0.013783:rs181660517
1   755775  rs3131965   A   G   .   PASS    AF=0.839777 ES:SE:LP:AF:ID  0.000313208:0.000700603:0.187087:0.839777:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869387 ES:SE:LP:AF:ID  -8.17881e-05:0.000739357:0.0409586:0.869387:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868933 ES:SE:LP:AF:ID  -8.31669e-05:0.000737494:0.0409586:0.868933:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867885 ES:SE:LP:AF:ID  -0.000163547:0.00073608:0.0861861:0.867885:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869077 ES:SE:LP:AF:ID  -8.16304e-05:0.0007381:0.0409586:0.869077:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869086 ES:SE:LP:AF:ID  -7.65532e-05:0.000738157:0.0362122:0.869086:rs4951862