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-5948/UKB-b-5948_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5948/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:45:40 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-5948/UKB-b-5948_data.vcf.gz ...
Read summary statistics for 3170937 SNPs.
Dropped 439 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, 784946 SNPs remain.
After merging with regression SNP LD, 784946 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0035 (0.0012)
Lambda GC: 1.0233
Mean Chi^2: 1.0315
Intercept: 0.9942 (0.0097)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:46:21 2019
Total time elapsed: 40.73s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.83,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 1.052e-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": 25346,
    "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": 784946,
    "ldsc_nsnp_merge_regression_ld": 784946,
    "ldsc_observed_scale_h2_beta": 0.0035,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 0.9942,
    "ldsc_intercept_se": 0.0097,
    "ldsc_lambda_gc": 1.0233,
    "ldsc_mean_chisq": 1.0315,
    "ldsc_ratio": -0.1841
}
 

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 3170501 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 3170937 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 8.662840e+00 5.772715e+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 7.854404e+07 5.670640e+07 828.0000000 3.160183e+07 6.892612e+07 1.147902e+08 2.492013e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.100000e-06 1.529000e-04 -0.0007814 -1.008000e-04 5.000000e-07 1.028000e-04 8.552000e-04 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.497000e-04 1.270000e-05 0.0001310 1.386000e-04 1.458000e-04 1.587000e-04 3.239000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.948793e-01 2.906488e-01 0.0000004 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 4.948806e-01 2.906221e-01 0.0000004 2.413933e-01 4.935392e-01 7.470486e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.283370e-01 1.824349e-01 0.1764120 2.682130e-01 3.949090e-01 5.699670e-01 8.235880e-01 ▇▆▅▃▃
numeric AF_reference 25346 0.9920068 NA NA NA NA NA NA NA 4.131306e-01 1.962616e-01 0.0000000 2.545930e-01 3.871810e-01 5.571090e-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 -0.0000738 0.0002410 0.7600007 0.7594928 0.623765 0.7821490 NA
1 54676 rs2462492 C T -0.0003632 0.0002388 0.1299999 0.1282986 0.400401 NA NA
1 91536 rs6702460 G T -0.0007130 0.0002351 0.0024000 0.0024281 0.456846 0.4207270 NA
1 534192 rs6680723 C T -0.0003149 0.0002686 0.2399999 0.2410052 0.240959 NA NA
1 706368 rs55727773 A G -0.0000794 0.0001667 0.6300007 0.6337895 0.515645 0.2751600 NA
1 763394 rs369924889 G A -0.0000360 0.0001955 0.8499999 0.8540366 0.706753 0.6176120 NA
1 768253 rs2977608 A C -0.0003043 0.0001595 0.0560003 0.0564528 0.761297 0.4894170 NA
1 776546 rs12124819 A G -0.0001491 0.0001782 0.4000000 0.4027875 0.265385 0.0756789 NA
1 798400 rs10900604 A G 0.0003004 0.0001702 0.0779992 0.0775973 0.206591 0.4105430 NA
1 798959 rs11240777 G A 0.0003025 0.0001703 0.0759994 0.0756254 0.206420 0.4099440 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C 0.0003466 0.0001569 0.0269998 0.0271944 0.713656 0.6369810 NA
22 51181919 rs9616825 G C 0.0003359 0.0001561 0.0309999 0.0314480 0.695470 0.6194090 NA
22 51182485 rs6009961 A G 0.0003604 0.0001574 0.0219999 0.0220398 0.715502 0.6383790 NA
22 51186143 rs2879914 T C 0.0001723 0.0001460 0.2399999 0.2377743 0.381825 0.2733630 NA
22 51186228 rs3865766 C T 0.0002674 0.0001423 0.0599998 0.0601252 0.451061 0.4532750 NA
22 51197266 rs61290853 A G 0.0002639 0.0001469 0.0719996 0.0724303 0.386333 0.4229230 NA
22 51198027 rs34939255 A G 0.0000919 0.0001663 0.5800000 0.5805148 0.254562 0.0984425 NA
22 51211106 rs9628250 T C 0.0000244 0.0001649 0.8800001 0.8821491 0.271547 0.1671330 NA
22 51212875 rs2238837 A C 0.0001989 0.0001566 0.2000000 0.2041150 0.331457 0.3724040 NA
22 51237063 rs3896457 T C 0.0001517 0.0001604 0.3400001 0.3441834 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  -7.37967e-05:0.00024105:0.119186:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  -0.000363187:0.000238806:0.886057:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  -0.000712961:0.000235133:2.61979:0.456846:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240959 ES:SE:LP:AF:ID  -0.00031491:0.000268585:0.619789:0.240959:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -7.94311e-05:0.000166732:0.200659:0.515645:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -3.5962e-05:0.000195477:0.0705811:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761297 ES:SE:LP:AF:ID  -0.000304334:0.000159544:1.25181:0.761297:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265385 ES:SE:LP:AF:ID  -0.000149105:0.000178216:0.39794:0.265385:rs12124819
1   798400  rs10900604  A   G   .   PASS    AF=0.206591 ES:SE:LP:AF:ID  0.000300369:0.0001702:1.10791:0.206591:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.20642  ES:SE:LP:AF:ID  0.000302516:0.000170273:1.11919:0.20642:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772619 ES:SE:LP:AF:ID  -0.000299933:0.000161977:1.19382:0.772619:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772847 ES:SE:LP:AF:ID  -0.000295368:0.00016225:1.16115:0.772847:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340396 ES:SE:LP:AF:ID  1.86981e-05:0.000228618:0.0315171:0.340396:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697255 ES:SE:LP:AF:ID  0.000280207:0.000152957:1.17393:0.697255:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705397 ES:SE:LP:AF:ID  0.000153865:0.000150189:0.508638:0.705397:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705442 ES:SE:LP:AF:ID  0.000158483:0.000150184:0.537602:0.705442:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705627 ES:SE:LP:AF:ID  0.00015605:0.000150191:0.522879:0.705627:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705655 ES:SE:LP:AF:ID  0.000155278:0.000150207:0.522879:0.705655:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730129 ES:SE:LP:AF:ID  0.000245901:0.0001543:0.958607:0.730129:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294377 ES:SE:LP:AF:ID  -0.000156861:0.0001502:0.522879:0.294377:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236703 ES:SE:LP:AF:ID  -4.3112e-05:0.000159911:0.102373:0.236703:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236691 ES:SE:LP:AF:ID  -4.28108e-05:0.000159913:0.102373:0.236691:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.23975  ES:SE:LP:AF:ID  -2.89472e-05:0.0001594:0.0655015:0.23975:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236693 ES:SE:LP:AF:ID  -4.2811e-05:0.000159911:0.102373:0.236693:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212421 ES:SE:LP:AF:ID  -0.000148074:0.000166206:0.431798:0.212421:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212316 ES:SE:LP:AF:ID  -0.000145233:0.000166235:0.420216:0.212316:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237178 ES:SE:LP:AF:ID  -4.34672e-05:0.000159789:0.102373:0.237178:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.212962 ES:SE:LP:AF:ID  -0.000144589:0.000165999:0.420216:0.212962:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212924 ES:SE:LP:AF:ID  -0.000141611:0.000166033:0.408935:0.212924:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241162 ES:SE:LP:AF:ID  -1.56457e-05:0.000158674:0.0362122:0.241162:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213543 ES:SE:LP:AF:ID  -0.000139669:0.000165788:0.39794:0.213543:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269511 ES:SE:LP:AF:ID  -1.42632e-05:0.000153108:0.0315171:0.269511:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213513 ES:SE:LP:AF:ID  -0.000147732:0.000165808:0.431798:0.213513:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214587 ES:SE:LP:AF:ID  -0.000133626:0.000165489:0.376751:0.214587:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246204 ES:SE:LP:AF:ID  -0.000103287:0.000157582:0.29243:0.246204:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270019 ES:SE:LP:AF:ID  -2.09263e-05:0.000153216:0.05061:0.270019:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400124 ES:SE:LP:AF:ID  -6.84176e-05:0.000138537:0.207608:0.400124:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237102 ES:SE:LP:AF:ID  -8.84292e-05:0.000160916:0.236572:0.237102:rs1574243
1   842013  rs7419119   T   G   .   PASS    AF=0.215391 ES:SE:LP:AF:ID  -9.58815e-05:0.0001656:0.251812:0.215391:rs7419119
1   842362  rs28540380  C   T   .   PASS    AF=0.235323 ES:SE:LP:AF:ID  -5.87321e-05:0.000163326:0.142668:0.235323:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362606 ES:SE:LP:AF:ID  0.000192392:0.000171974:0.585027:0.362606:rs11516185
1   844300  rs61769713  C   G   .   PASS    AF=0.818811 ES:SE:LP:AF:ID  2.66487e-05:0.000176746:0.0555173:0.818811:rs61769713
1   845283  rs7366404   G   T   .   PASS    AF=0.814497 ES:SE:LP:AF:ID  6.46511e-05:0.000175189:0.148742:0.814497:rs7366404
1   845635  rs117086422 C   T   .   PASS    AF=0.205429 ES:SE:LP:AF:ID  -5.24808e-05:0.000168416:0.119186:0.205429:rs117086422
1   845938  rs57760052  G   A   .   PASS    AF=0.210864 ES:SE:LP:AF:ID  -3.65805e-05:0.000166796:0.0809219:0.210864:rs57760052
1   846078  rs28612348  C   T   .   PASS    AF=0.196785 ES:SE:LP:AF:ID  -8.38897e-05:0.000170997:0.207608:0.196785:rs28612348
1   846338  rs4970334   A   G   .   PASS    AF=0.813828 ES:SE:LP:AF:ID  7.88052e-05:0.00017504:0.187087:0.813828:rs4970334
1   846398  rs58781670  G   A   .   PASS    AF=0.204447 ES:SE:LP:AF:ID  -9.16633e-05:0.000168991:0.229148:0.204447:rs58781670
1   846489  rs4970333   T   C   .   PASS    AF=0.81392  ES:SE:LP:AF:ID  7.71087e-05:0.000175161:0.180456:0.81392:rs4970333
1   846808  rs4475691   C   T   .   PASS    AF=0.198378 ES:SE:LP:AF:ID  -8.90863e-05:0.000170511:0.221849:0.198378:rs4475691