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-1539/UKB-b-1539_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1539/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:10 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-1539/UKB-b-1539_data.vcf.gz ...
Read summary statistics for 3318864 SNPs.
Dropped 485 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, 816664 SNPs remain.
After merging with regression SNP LD, 816664 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0015 (0.0015)
Lambda GC: 1.0928
Mean Chi^2: 1.1043
Intercept: 1.0885 (0.0104)
Ratio: 0.8484 (0.0998)
Analysis finished at Thu Oct 17 14:44:59 2019
Total time elapsed: 48.85s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8402,
    "inflation_factor": 1.0966,
    "mean_EFFECT": -1.0588e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 2,
    "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": 26595,
    "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": 816664,
    "ldsc_nsnp_merge_regression_ld": 816664,
    "ldsc_observed_scale_h2_beta": 0.0015,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.0885,
    "ldsc_intercept_se": 0.0104,
    "ldsc_lambda_gc": 1.0928,
    "ldsc_mean_chisq": 1.1043,
    "ldsc_ratio": 0.8485
}

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 3 58 0 3318382 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 3318864 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 8.662654e+00 5.773221e+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 7.853968e+07 5.672219e+07 828.0000000 3.157377e+07 6.891536e+07 1.147774e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -1.100000e-06 1.648000e-04 -0.0009275 -1.104000e-04 -7.000000e-07 1.080000e-04 9.799000e-04 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.560000e-04 1.450000e-05 0.0001353 1.434000e-04 1.515000e-04 1.664000e-04 3.346000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.855955e-01 2.931535e-01 0.0000000 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 4.855995e-01 2.931308e-01 0.0000000 2.279054e-01 4.816797e-01 7.395369e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.225983e-01 1.885395e-01 0.1650170 2.573010e-01 3.869080e-01 5.677253e-01 8.349830e-01 ▇▆▅▃▂
numeric AF_reference 26595 0.9919867 NA NA NA NA NA NA NA 4.080852e-01 2.003325e-01 0.0000000 2.454070e-01 3.795930e-01 5.547120e-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 -0.0003971 0.0002489 0.1100001 0.1106793 0.623765 0.7821490 NA
1 54676 rs2462492 C T 0.0004621 0.0002466 0.0610000 0.0609715 0.400401 NA NA
1 91536 rs6702460 G T -0.0001970 0.0002428 0.4199997 0.4171197 0.456846 0.4207270 NA
1 534192 rs6680723 C T -0.0000928 0.0002774 0.7400005 0.7380067 0.240959 NA NA
1 706368 rs55727773 A G -0.0001687 0.0001722 0.3300000 0.3273167 0.515645 0.2751600 NA
1 763394 rs369924889 G A -0.0000632 0.0002019 0.7499995 0.7541852 0.706753 0.6176120 NA
1 768253 rs2977608 A C 0.0000378 0.0001648 0.8200001 0.8187525 0.761297 0.4894170 NA
1 776546 rs12124819 A G -0.0001352 0.0001840 0.4600002 0.4626992 0.265385 0.0756789 NA
1 798400 rs10900604 A G 0.0001635 0.0001758 0.3500000 0.3522584 0.206591 0.4105430 NA
1 798959 rs11240777 G A 0.0001601 0.0001758 0.3599996 0.3625759 0.206420 0.4099440 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51182485 rs6009961 A G -0.0000480 0.0001626 0.7700005 0.7679862 0.715502 0.6383790 NA
22 51186143 rs2879914 T C -0.0000739 0.0001508 0.6200004 0.6238359 0.381825 0.2733630 NA
22 51186228 rs3865766 C T -0.0000043 0.0001470 0.9800000 0.9765747 0.451061 0.4532750 NA
22 51192586 rs5771006 G A -0.0001537 0.0001980 0.4400003 0.4376225 0.167627 0.0848642 NA
22 51193227 rs34608236 T G -0.0001234 0.0002024 0.5400003 0.5421939 0.168490 0.0692891 NA
22 51197266 rs61290853 A G -0.0000785 0.0001517 0.5999997 0.6047650 0.386333 0.4229230 NA
22 51198027 rs34939255 A G -0.0000451 0.0001718 0.7899998 0.7927990 0.254562 0.0984425 NA
22 51211106 rs9628250 T C -0.0000078 0.0001703 0.9599999 0.9634920 0.271547 0.1671330 NA
22 51212875 rs2238837 A C -0.0001378 0.0001618 0.3900004 0.3945832 0.331457 0.3724040 NA
22 51237063 rs3896457 T C -0.0001817 0.0001656 0.2700001 0.2726207 0.297974 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623765 ES:SE:LP:AF:ID  -0.000397072:0.000248925:0.958607:0.623765:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400401 ES:SE:LP:AF:ID  0.00046207:0.000246608:1.21467:0.400401:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456846 ES:SE:LP:AF:ID  -0.000197027:0.000242815:0.376751:0.456846:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240959 ES:SE:LP:AF:ID  -9.27753e-05:0.00027736:0.130768:0.240959:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515645 ES:SE:LP:AF:ID  -0.000168655:0.000172179:0.481486:0.515645:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.706753 ES:SE:LP:AF:ID  -6.32088e-05:0.000201864:0.124939:0.706753:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761297 ES:SE:LP:AF:ID  3.77538e-05:0.000164756:0.0861861:0.761297:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265385 ES:SE:LP:AF:ID  -0.00013516:0.000184039:0.337242:0.265385:rs12124819
1   798400  rs10900604  A   G   .   PASS    AF=0.206591 ES:SE:LP:AF:ID  0.000163496:0.000175761:0.455932:0.206591:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.20642  ES:SE:LP:AF:ID  0.000160093:0.000175836:0.443698:0.20642:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772619 ES:SE:LP:AF:ID  -0.000216294:0.000167269:0.69897:0.772619:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772847 ES:SE:LP:AF:ID  -0.000217057:0.000167551:0.69897:0.772847:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340396 ES:SE:LP:AF:ID  -7.68399e-05:0.000236087:0.130768:0.340396:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697255 ES:SE:LP:AF:ID  3.4167e-05:0.000157955:0.0809219:0.697255:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705397 ES:SE:LP:AF:ID  -2.66301e-05:0.000155096:0.0655015:0.705397:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705442 ES:SE:LP:AF:ID  -2.74876e-05:0.000155091:0.0655015:0.705442:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705627 ES:SE:LP:AF:ID  -3.02994e-05:0.000155098:0.0705811:0.705627:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705655 ES:SE:LP:AF:ID  -3.06162e-05:0.000155114:0.0757207:0.705655:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730129 ES:SE:LP:AF:ID  -1.45676e-05:0.000159341:0.0315171:0.730129:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294377 ES:SE:LP:AF:ID  3.00906e-05:0.000155107:0.0705811:0.294377:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236703 ES:SE:LP:AF:ID  -8.3225e-05:0.000165136:0.21467:0.236703:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236691 ES:SE:LP:AF:ID  -8.34664e-05:0.000165137:0.21467:0.236691:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.23975  ES:SE:LP:AF:ID  -6.27836e-05:0.000164608:0.154902:0.23975:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236693 ES:SE:LP:AF:ID  -8.34901e-05:0.000165136:0.21467:0.236693:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212421 ES:SE:LP:AF:ID  -0.000116251:0.000171636:0.30103:0.212421:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212316 ES:SE:LP:AF:ID  -0.000113077:0.000171667:0.29243:0.212316:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237178 ES:SE:LP:AF:ID  -7.38777e-05:0.000165009:0.187087:0.237178:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.212962 ES:SE:LP:AF:ID  -0.000106392:0.000171422:0.275724:0.212962:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212924 ES:SE:LP:AF:ID  -9.9106e-05:0.000171457:0.251812:0.212924:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241162 ES:SE:LP:AF:ID  -4.37571e-05:0.000163858:0.102373:0.241162:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213543 ES:SE:LP:AF:ID  -9.17239e-05:0.000171205:0.229148:0.213543:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269511 ES:SE:LP:AF:ID  4.57415e-05:0.00015811:0.113509:0.269511:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213513 ES:SE:LP:AF:ID  -9.10074e-05:0.000171226:0.221849:0.213513:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214587 ES:SE:LP:AF:ID  -9.09111e-05:0.000170896:0.229148:0.214587:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246204 ES:SE:LP:AF:ID  3.11868e-05:0.000162731:0.0705811:0.246204:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270019 ES:SE:LP:AF:ID  6.46503e-05:0.000158222:0.167491:0.270019:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400124 ES:SE:LP:AF:ID  5.0543e-05:0.000143063:0.142668:0.400124:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237102 ES:SE:LP:AF:ID  1.14204e-05:0.000166173:0.0222764:0.237102:rs1574243
1   842013  rs7419119   T   G   .   PASS    AF=0.215391 ES:SE:LP:AF:ID  -9.96315e-05:0.00017101:0.251812:0.215391:rs7419119
1   842362  rs28540380  C   T   .   PASS    AF=0.235323 ES:SE:LP:AF:ID  -0.000142811:0.000168662:0.39794:0.235323:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362606 ES:SE:LP:AF:ID  2.72045e-05:0.000177592:0.0555173:0.362606:rs11516185
1   844300  rs61769713  C   G   .   PASS    AF=0.818811 ES:SE:LP:AF:ID  -0.000112023:0.000182521:0.267606:0.818811:rs61769713
1   845283  rs7366404   G   T   .   PASS    AF=0.814497 ES:SE:LP:AF:ID  -7.16393e-05:0.000180913:0.161151:0.814497:rs7366404
1   845635  rs117086422 C   T   .   PASS    AF=0.205429 ES:SE:LP:AF:ID  9.27954e-05:0.000173918:0.229148:0.205429:rs117086422
1   845938  rs57760052  G   A   .   PASS    AF=0.210864 ES:SE:LP:AF:ID  0.000135438:0.000172245:0.366532:0.210864:rs57760052
1   846078  rs28612348  C   T   .   PASS    AF=0.196785 ES:SE:LP:AF:ID  1.79495e-05:0.000176583:0.0362122:0.196785:rs28612348
1   846338  rs4970334   A   G   .   PASS    AF=0.813828 ES:SE:LP:AF:ID  -7.65749e-05:0.000180759:0.173925:0.813828:rs4970334
1   846398  rs58781670  G   A   .   PASS    AF=0.204447 ES:SE:LP:AF:ID  0.000166965:0.000174513:0.468521:0.204447:rs58781670
1   846489  rs4970333   T   C   .   PASS    AF=0.81392  ES:SE:LP:AF:ID  -7.12763e-05:0.000180884:0.161151:0.81392:rs4970333
1   846808  rs4475691   C   T   .   PASS    AF=0.198378 ES:SE:LP:AF:ID  -4.62683e-06:0.000176082:0.00877392:0.198378:rs4475691