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-17371/UKB-b-17371_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-17371/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-17371/UKB-b-17371_data.vcf.gz ...
Read summary statistics for 2575136 SNPs.
Dropped 305 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, 650429 SNPs remain.
After merging with regression SNP LD, 650429 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0022 (0.0013)
Lambda GC: 1.0252
Mean Chi^2: 1.0249
Intercept: 1.0007 (0.0102)
Ratio: 0.0293 (0.4083)
Analysis finished at Thu Oct 17 14:40:56 2019
Total time elapsed: 37.92s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.777,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -3.4531e-07,
    "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": 20435,
    "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": 650429,
    "ldsc_nsnp_merge_regression_ld": 650429,
    "ldsc_observed_scale_h2_beta": 0.0022,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0007,
    "ldsc_intercept_se": 0.0102,
    "ldsc_lambda_gc": 1.0252,
    "ldsc_mean_chisq": 1.0249,
    "ldsc_ratio": 0.0281
}
 

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 4 58 0 2574834 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 2575136 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 8.657648e+00 5.767072e+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 7.855332e+07 5.661964e+07 5687.0000000 3.169623e+07 6.897015e+07 1.147498e+08 2.491917e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -3.000000e-07 1.298000e-04 -0.0007201 -8.780000e-05 -8.000000e-07 8.670000e-05 6.342000e-04 ▁▁▇▃▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.280000e-04 7.300000e-06 0.0001157 1.217000e-04 1.258000e-04 1.331000e-04 2.509000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.958327e-01 2.893552e-01 0.0000015 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.958323e-01 2.893325e-01 0.0000015 2.449332e-01 4.949389e-01 7.468120e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.506517e-01 1.553395e-01 0.2263910 3.140520e-01 4.271700e-01 5.748570e-01 7.736080e-01 ▇▆▅▃▃
numeric AF_reference 20435 0.9920645 NA NA NA NA NA NA NA 4.326356e-01 1.787292e-01 0.0001997 2.911340e-01 4.159350e-01 5.634980e-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 0.0001336 0.0002130 0.5300002 0.5303935 0.623763 0.7821490 NA
1 54676 rs2462492 C T 0.0000760 0.0002110 0.7199992 0.7186120 0.400401 NA NA
1 91536 rs6702460 G T 0.0001066 0.0002077 0.6100002 0.6078534 0.456851 0.4207270 NA
1 534192 rs6680723 C T -0.0000897 0.0002373 0.7099994 0.7052950 0.240960 NA NA
1 706368 rs55727773 A G -0.0001557 0.0001473 0.2900000 0.2906229 0.515650 0.2751600 NA
1 763394 rs369924889 G A -0.0000095 0.0001727 0.9599999 0.9561525 0.706753 0.6176120 NA
1 768253 rs2977608 A C -0.0002017 0.0001409 0.1499999 0.1523228 0.761304 0.4894170 NA
1 776546 rs12124819 A G 0.0000451 0.0001574 0.7700005 0.7743608 0.265390 0.0756789 NA
1 808631 rs11240779 G A -0.0001081 0.0001431 0.4500005 0.4500194 0.772626 0.4534740 NA
1 808928 rs11240780 C T -0.0001080 0.0001433 0.4500005 0.4511702 0.772854 0.4522760 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C 0.0000208 0.0001386 0.8800001 0.8806084 0.713658 0.6369810 NA
22 51181919 rs9616825 G C 0.0000571 0.0001379 0.6800001 0.6787619 0.695471 0.6194090 NA
22 51182485 rs6009961 A G 0.0000185 0.0001391 0.8900000 0.8940318 0.715505 0.6383790 NA
22 51186143 rs2879914 T C 0.0001399 0.0001290 0.2800000 0.2779108 0.381826 0.2733630 NA
22 51186228 rs3865766 C T 0.0000956 0.0001257 0.4500005 0.4466971 0.451063 0.4532750 NA
22 51197266 rs61290853 A G 0.0001371 0.0001298 0.2900000 0.2906536 0.386333 0.4229230 NA
22 51198027 rs34939255 A G -0.0000869 0.0001469 0.5500004 0.5539880 0.254557 0.0984425 NA
22 51211106 rs9628250 T C -0.0001373 0.0001456 0.3500000 0.3458978 0.271547 0.1671330 NA
22 51212875 rs2238837 A C 0.0001631 0.0001384 0.2399999 0.2385057 0.331455 0.3724040 NA
22 51237063 rs3896457 T C 0.0001512 0.0001417 0.2900000 0.2859343 0.297971 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  0.000133606:0.00021295:0.275724:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  7.60141e-05:0.000210966:0.142668:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  0.000106592:0.000207725:0.21467:0.456851:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.24096  ES:SE:LP:AF:ID  -8.97325e-05:0.000237273:0.148742:0.24096:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.51565  ES:SE:LP:AF:ID  -0.000155657:0.000147297:0.537602:0.51565:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -9.49496e-06:0.000172691:0.0177288:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761304 ES:SE:LP:AF:ID  -0.000201748:0.000140947:0.823909:0.761304:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  4.51342e-05:0.00015744:0.113509:0.26539:rs12124819
1   808631  rs11240779  G   A   .   PASS    AF=0.772626 ES:SE:LP:AF:ID  -0.000108093:0.000143097:0.346787:0.772626:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772854 ES:SE:LP:AF:ID  -0.000108001:0.000143339:0.346787:0.772854:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340397 ES:SE:LP:AF:ID  0.00023128:0.000201972:0.60206:0.340397:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697259 ES:SE:LP:AF:ID  0.000249192:0.000135125:1.18709:0.697259:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705403 ES:SE:LP:AF:ID  0.00018073:0.000132681:0.769551:0.705403:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705448 ES:SE:LP:AF:ID  0.000184656:0.000132676:0.79588:0.705448:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705634 ES:SE:LP:AF:ID  0.000182237:0.000132682:0.769551:0.705634:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705662 ES:SE:LP:AF:ID  0.000181721:0.000132696:0.769551:0.705662:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730134 ES:SE:LP:AF:ID  0.000208893:0.000136312:0.886057:0.730134:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294371 ES:SE:LP:AF:ID  -0.000182321:0.00013269:0.769551:0.294371:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236696 ES:SE:LP:AF:ID  -0.000271482:0.00014127:1.25964:0.236696:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236684 ES:SE:LP:AF:ID  -0.000271381:0.000141271:1.25964:0.236684:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239743 ES:SE:LP:AF:ID  -0.000291853:0.000140818:1.42022:0.239743:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236686 ES:SE:LP:AF:ID  -0.000271405:0.00014127:1.25964:0.236686:rs28484835
1   834832  rs4411087   G   C   .   PASS    AF=0.237171 ES:SE:LP:AF:ID  -0.000272189:0.000141162:1.26761:0.237171:rs4411087
1   835499  rs4422948   A   G   .   PASS    AF=0.241155 ES:SE:LP:AF:ID  -0.000270437:0.000140177:1.26761:0.241155:rs4422948
1   836896  rs28705752  T   C   .   PASS    AF=0.269503 ES:SE:LP:AF:ID  -0.000237563:0.00013526:1.10237:0.269503:rs28705752
1   838555  rs4970383   C   A   .   PASS    AF=0.246197 ES:SE:LP:AF:ID  -0.000268555:0.000139213:1.26761:0.246197:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.27001  ES:SE:LP:AF:ID  -0.000243125:0.000135355:1.14267:0.27001:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400106 ES:SE:LP:AF:ID  -0.00013953:0.000122387:0.60206:0.400106:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237094 ES:SE:LP:AF:ID  -0.000335971:0.000142158:1.74473:0.237094:rs1574243
1   842362  rs28540380  C   T   .   PASS    AF=0.235321 ES:SE:LP:AF:ID  -0.000338378:0.000144285:1.72125:0.235321:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362599 ES:SE:LP:AF:ID  -9.03631e-05:0.00015193:0.259637:0.362599:rs11516185
1   850218  rs6664536   T   A   .   PASS    AF=0.590333 ES:SE:LP:AF:ID  2.06122e-05:0.000122028:0.0604807:0.590333:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603726 ES:SE:LP:AF:ID  5.02541e-05:0.000122713:0.167491:0.603726:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603944 ES:SE:LP:AF:ID  5.43853e-05:0.000122696:0.180456:0.603944:rs6657440
1   852037  rs4970463   G   A   .   PASS    AF=0.589688 ES:SE:LP:AF:ID  1.54611e-05:0.000122227:0.0457575:0.589688:rs4970463
1   852063  rs28436996  G   A   .   PASS    AF=0.589667 ES:SE:LP:AF:ID  1.82134e-05:0.000122172:0.0555173:0.589667:rs28436996
1   852875  rs13303369  C   T   .   PASS    AF=0.607674 ES:SE:LP:AF:ID  2.39783e-05:0.00012297:0.0705811:0.607674:rs13303369
1   853954  rs1806509   C   A   .   PASS    AF=0.607833 ES:SE:LP:AF:ID  2.77767e-05:0.000122987:0.0861861:0.607833:rs1806509
1   854777  rs13303019  A   G   .   PASS    AF=0.610318 ES:SE:LP:AF:ID  4.38119e-05:0.000123108:0.142668:0.610318:rs13303019
1   854978  rs13303057  A   C   .   PASS    AF=0.603286 ES:SE:LP:AF:ID  5.02049e-05:0.000122743:0.167491:0.603286:rs13303057
1   855075  rs6673914   C   G   .   PASS    AF=0.610338 ES:SE:LP:AF:ID  4.31962e-05:0.00012311:0.136677:0.610338:rs6673914
1   856099  rs28534711  T   G   .   PASS    AF=0.389935 ES:SE:LP:AF:ID  -4.38297e-05:0.000123134:0.142668:0.389935:rs28534711
1   856108  rs28742275  A   G   .   PASS    AF=0.389918 ES:SE:LP:AF:ID  -4.38282e-05:0.00012314:0.142668:0.389918:rs28742275
1   856476  rs4040605   A   G   .   PASS    AF=0.350351 ES:SE:LP:AF:ID  -8.76192e-05:0.0001265:0.309804:0.350351:rs4040605
1   858801  rs7418179   A   G   .   PASS    AF=0.765845 ES:SE:LP:AF:ID  0.000230904:0.000142002:1:0.765845:rs7418179
1   860416  rs61464428  G   A   .   PASS    AF=0.766637 ES:SE:LP:AF:ID  0.000250934:0.000142072:1.11351:0.766637:rs61464428
1   860688  rs60837925  G   A   .   PASS    AF=0.766103 ES:SE:LP:AF:ID  0.000238846:0.000141975:1.03152:0.766103:rs60837925
1   861630  rs2879816   G   A   .   PASS    AF=0.766255 ES:SE:LP:AF:ID  0.000235326:0.000142009:1.01323:0.766255:rs2879816
1   862866  rs3892970   C   T   .   PASS    AF=0.763121 ES:SE:LP:AF:ID  0.000249526:0.000141879:1.10237:0.763121:rs3892970
1   864938  rs2340587   G   A   .   PASS    AF=0.760005 ES:SE:LP:AF:ID  0.000265556:0.000140827:1.22915:0.760005:rs2340587