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-8024/UKB-b-8024_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8024/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:08 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-8024/UKB-b-8024_data.vcf.gz ...
Read summary statistics for 2757652 SNPs.
Dropped 339 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, 692151 SNPs remain.
After merging with regression SNP LD, 692151 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0009 (0.0013)
Lambda GC: 1.1242
Mean Chi^2: 1.1176
Intercept: 1.1077 (0.0105)
Ratio: 0.9164 (0.0896)
Analysis finished at Thu Oct 17 14:41:49 2019
Total time elapsed: 40.63s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.7959,
    "inflation_factor": 1.1474,
    "mean_EFFECT": 7.3192e-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": 21891,
    "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": 692151,
    "ldsc_nsnp_merge_regression_ld": 692151,
    "ldsc_observed_scale_h2_beta": 0.0009,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.1077,
    "ldsc_intercept_se": 0.0105,
    "ldsc_lambda_gc": 1.1242,
    "ldsc_mean_chisq": 1.1176,
    "ldsc_ratio": 0.9158
}

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 TRUE
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 2757316 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 2757652 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 8.660716e+00 5.769771e+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 7.854217e+07 5.663807e+07 5687.0000000 3.170078e+07 6.894119e+07 1.147172e+08 2.492013e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 7.000000e-07 1.419000e-04 -0.0006849 -9.520000e-05 3.000000e-07 9.570000e-05 7.447000e-04 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.338000e-04 8.700000e-06 0.0001198 1.263000e-04 1.312000e-04 1.399000e-04 2.734000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.810870e-01 2.932493e-01 0.0000006 2.200002e-01 4.700002e-01 7.300002e-01 1.000000e+00 ▇▇▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.810876e-01 2.932263e-01 0.0000006 2.218840e-01 4.743052e-01 7.348002e-01 9.999998e-01 ▇▇▇▇▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.439873e-01 1.640635e-01 0.2104640 2.997538e-01 4.171900e-01 5.740820e-01 7.895360e-01 ▇▆▅▃▃
numeric AF_reference 21891 0.9920617 NA NA NA NA NA NA NA 4.267035e-01 1.844042e-01 0.0001997 2.797520e-01 4.073480e-01 5.619010e-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 -0.0001998 0.0002205 0.3599996 0.3649932 0.623765 0.7821490 NA
1 54676 rs2462492 C T -0.0001898 0.0002185 0.3800004 0.3848315 0.400401 NA NA
1 91536 rs6702460 G T -0.0002038 0.0002151 0.3400001 0.3433184 0.456846 0.4207270 NA
1 534192 rs6680723 C T 0.0001760 0.0002457 0.4700002 0.4739132 0.240959 NA NA
1 706368 rs55727773 A G -0.0000993 0.0001525 0.5199996 0.5151693 0.515645 0.2751600 NA
1 763394 rs369924889 G A -0.0000525 0.0001788 0.7700005 0.7692560 0.706753 0.6176120 NA
1 768253 rs2977608 A C -0.0000291 0.0001460 0.8400000 0.8420465 0.761297 0.4894170 NA
1 776546 rs12124819 A G -0.0001987 0.0001630 0.2200002 0.2229956 0.265385 0.0756789 NA
1 808631 rs11240779 G A -0.0000508 0.0001482 0.7300002 0.7316752 0.772619 0.4534740 NA
1 808928 rs11240780 C T -0.0000620 0.0001484 0.6800001 0.6762706 0.772847 0.4522760 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C 0.0000051 0.0001436 0.9699999 0.9718515 0.713656 0.6369810 NA
22 51181919 rs9616825 G C -0.0000619 0.0001429 0.6600001 0.6648931 0.695470 0.6194090 NA
22 51182485 rs6009961 A G -0.0000064 0.0001440 0.9599999 0.9644652 0.715502 0.6383790 NA
22 51186143 rs2879914 T C -0.0000795 0.0001336 0.5500004 0.5518202 0.381825 0.2733630 NA
22 51186228 rs3865766 C T -0.0000983 0.0001302 0.4500005 0.4501638 0.451061 0.4532750 NA
22 51197266 rs61290853 A G -0.0001885 0.0001344 0.1600000 0.1608606 0.386333 0.4229230 NA
22 51198027 rs34939255 A G 0.0000871 0.0001522 0.5700002 0.5669650 0.254562 0.0984425 NA
22 51211106 rs9628250 T C 0.0001321 0.0001509 0.3800004 0.3813381 0.271547 0.1671330 NA
22 51212875 rs2238837 A C -0.0000745 0.0001433 0.5999997 0.6034184 0.331457 0.3724040 NA
22 51237063 rs3896457 T C -0.0000617 0.0001467 0.6700003 0.6741553 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  -0.00019976:0.000220512:0.443698:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.000189848:0.00021846:0.420216:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  -0.000203835:0.0002151:0.468521:0.456846:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240959 ES:SE:LP:AF:ID  0.000175953:0.000245701:0.327902:0.240959:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -9.92654e-05:0.000152526:0.283997:0.515645:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -5.24574e-05:0.000178823:0.113509:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761297 ES:SE:LP:AF:ID  -2.90846e-05:0.000145951:0.0757207:0.761297:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265385 ES:SE:LP:AF:ID  -0.000198671:0.000163032:0.657577:0.265385:rs12124819
1   808631  rs11240779  G   A   .   PASS    AF=0.772619 ES:SE:LP:AF:ID  -5.08096e-05:0.000148177:0.136677:0.772619:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772847 ES:SE:LP:AF:ID  -6.19764e-05:0.000148426:0.167491:0.772847:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340396 ES:SE:LP:AF:ID  0.000291333:0.00020914:0.79588:0.340396:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697255 ES:SE:LP:AF:ID  -0.000218959:0.000139926:0.920819:0.697255:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705397 ES:SE:LP:AF:ID  -0.000176151:0.000137393:0.69897:0.705397:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705442 ES:SE:LP:AF:ID  -0.000177348:0.000137389:0.69897:0.705442:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705627 ES:SE:LP:AF:ID  -0.000179428:0.000137395:0.721246:0.705627:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705655 ES:SE:LP:AF:ID  -0.000180084:0.000137409:0.721246:0.705655:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730129 ES:SE:LP:AF:ID  -0.000231541:0.000141154:1:0.730129:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294377 ES:SE:LP:AF:ID  0.000179413:0.000137403:0.721246:0.294377:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236703 ES:SE:LP:AF:ID  0.000239467:0.000146287:1:0.236703:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236691 ES:SE:LP:AF:ID  0.000240006:0.000146288:1:0.236691:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.23975  ES:SE:LP:AF:ID  0.000256202:0.000145819:1.10237:0.23975:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236693 ES:SE:LP:AF:ID  0.00023992:0.000146287:1:0.236693:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212421 ES:SE:LP:AF:ID  0.000314192:0.000152046:1.40894:0.212421:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212316 ES:SE:LP:AF:ID  0.000310052:0.000152072:1.38722:0.212316:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237178 ES:SE:LP:AF:ID  0.000256102:0.000146175:1.09691:0.237178:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.212962 ES:SE:LP:AF:ID  0.000329139:0.000151856:1.52288:0.212962:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212924 ES:SE:LP:AF:ID  0.000330296:0.000151887:1.52288:0.212924:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241162 ES:SE:LP:AF:ID  0.000241393:0.000145155:1.01773:0.241162:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213543 ES:SE:LP:AF:ID  0.000344026:0.000151663:1.63827:0.213543:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269511 ES:SE:LP:AF:ID  0.000134893:0.000140063:0.468521:0.269511:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213513 ES:SE:LP:AF:ID  0.000344446:0.000151682:1.63827:0.213513:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214587 ES:SE:LP:AF:ID  0.00033634:0.00015139:1.58503:0.214587:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246204 ES:SE:LP:AF:ID  0.00018859:0.000144156:0.721246:0.246204:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270019 ES:SE:LP:AF:ID  0.000151176:0.000140162:0.552842:0.270019:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400124 ES:SE:LP:AF:ID  -2.91629e-05:0.000126734:0.0861861:0.400124:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237102 ES:SE:LP:AF:ID  0.000204563:0.000147206:0.79588:0.237102:rs1574243
1   842013  rs7419119   T   G   .   PASS    AF=0.215391 ES:SE:LP:AF:ID  0.00031683:0.000151491:1.4437:0.215391:rs7419119
1   842362  rs28540380  C   T   .   PASS    AF=0.235323 ES:SE:LP:AF:ID  0.000359234:0.000149411:1.79588:0.235323:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362606 ES:SE:LP:AF:ID  -0.00021008:0.000157322:0.744727:0.362606:rs11516185
1   845938  rs57760052  G   A   .   PASS    AF=0.210864 ES:SE:LP:AF:ID  2.15084e-05:0.000152585:0.05061:0.210864:rs57760052
1   847491  rs28407778  G   A   .   PASS    AF=0.214198 ES:SE:LP:AF:ID  0.000143651:0.000151567:0.468521:0.214198:rs28407778
1   848090  rs4246505   G   A   .   PASS    AF=0.212513 ES:SE:LP:AF:ID  0.000150381:0.000151965:0.49485:0.212513:rs4246505
1   848738  rs3829741   C   T   .   PASS    AF=0.212338 ES:SE:LP:AF:ID  0.000150082:0.000152102:0.49485:0.212338:rs3829741
1   850062  rs28723578  A   T   .   PASS    AF=0.214408 ES:SE:LP:AF:ID  0.000144006:0.000151427:0.468521:0.214408:rs28723578
1   850123  rs28622257  C   T   .   PASS    AF=0.212773 ES:SE:LP:AF:ID  0.000149546:0.000151812:0.49485:0.212773:rs28622257
1   850218  rs6664536   T   A   .   PASS    AF=0.590331 ES:SE:LP:AF:ID  -0.000219898:0.000126364:1.08619:0.590331:rs6664536
1   850371  rs6679046   G   T   .   PASS    AF=0.603723 ES:SE:LP:AF:ID  -0.000288419:0.000127073:1.63827:0.603723:rs6679046
1   850780  rs6657440   C   T   .   PASS    AF=0.603942 ES:SE:LP:AF:ID  -0.000294173:0.000127055:1.67778:0.603942:rs6657440
1   851190  rs28609852  G   A   .   PASS    AF=0.214494 ES:SE:LP:AF:ID  0.000141435:0.000151407:0.455932:0.214494:rs28609852
1   851204  rs28552953  G   C   .   PASS    AF=0.224621 ES:SE:LP:AF:ID  0.00012706:0.000150318:0.39794:0.224621:rs28552953