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-9513/UKB-b-9513_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9513/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:46 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9513/UKB-b-9513_data.vcf.gz ...
Read summary statistics for 3118974 SNPs.
Dropped 431 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, 773583 SNPs remain.
After merging with regression SNP LD, 773583 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0017 (0.0011)
Lambda GC: 1.0163
Mean Chi^2: 1.0167
Intercept: 0.9989 (0.0092)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Thu Oct 17 14:43:23 2019
Total time elapsed: 37.51s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8262,
    "inflation_factor": 1,
    "mean_EFFECT": -5.8927e-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": 24921,
    "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": 773583,
    "ldsc_nsnp_merge_regression_ld": 773583,
    "ldsc_observed_scale_h2_beta": 0.0017,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 0.9989,
    "ldsc_intercept_se": 0.0092,
    "ldsc_lambda_gc": 1.0163,
    "ldsc_mean_chisq": 1.0167,
    "ldsc_ratio": -0.0659
}
 

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 3118546 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 3118974 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 8.664170e+00 5.772426e+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 7.854839e+07 5.670803e+07 828.0000000 3.159032e+07 6.893717e+07 1.147891e+08 2.492013e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA -6.000000e-07 1.496000e-04 -0.0007667 -1.008000e-04 -4.000000e-07 9.930000e-05 8.339000e-04 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.481000e-04 1.220000e-05 0.0001300 1.375000e-04 1.444000e-04 1.568000e-04 3.144000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.980212e-01 2.892622e-01 0.0000011 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.980221e-01 2.892380e-01 0.0000011 2.466395e-01 4.970621e-01 7.489695e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.303749e-01 1.802457e-01 0.1805060 2.721580e-01 3.978260e-01 5.706760e-01 8.194940e-01 ▇▆▅▃▃
numeric AF_reference 24921 0.9920099 NA NA NA NA NA NA NA 4.149155e-01 1.948052e-01 0.0000000 2.577880e-01 3.897760e-01 5.579070e-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 0.0003545 0.0002393 0.1400000 0.1384293 0.623777 0.7821490 NA
1 54676 rs2462492 C T -0.0000662 0.0002371 0.7800007 0.7799621 0.400402 NA NA
1 91536 rs6702460 G T 0.0002306 0.0002334 0.3200000 0.3231335 0.456859 0.4207270 NA
1 534192 rs6680723 C T 0.0002063 0.0002666 0.4400003 0.4392034 0.240945 NA NA
1 706368 rs55727773 A G 0.0000679 0.0001655 0.6800001 0.6815024 0.515670 0.2751600 NA
1 763394 rs369924889 G A -0.0000978 0.0001941 0.6100002 0.6141900 0.706760 0.6176120 NA
1 768253 rs2977608 A C -0.0000632 0.0001584 0.6899999 0.6900592 0.761337 0.4894170 NA
1 776546 rs12124819 A G 0.0000282 0.0001769 0.8700001 0.8732584 0.265361 0.0756789 NA
1 798400 rs10900604 A G 0.0000791 0.0001690 0.6400000 0.6395806 0.206543 0.4105430 NA
1 798959 rs11240777 G A 0.0000757 0.0001690 0.6499995 0.6544299 0.206373 0.4099440 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51180501 rs5770999 T C -0.0001592 0.0001558 0.3100002 0.3067724 0.713666 0.6369810 NA
22 51181919 rs9616825 G C -0.0000904 0.0001550 0.5600000 0.5595048 0.695497 0.6194090 NA
22 51182485 rs6009961 A G -0.0001555 0.0001563 0.3200000 0.3195858 0.715511 0.6383790 NA
22 51186143 rs2879914 T C 0.0000425 0.0001449 0.7700005 0.7693997 0.381821 0.2733630 NA
22 51186228 rs3865766 C T 0.0000679 0.0001412 0.6300007 0.6309155 0.451066 0.4532750 NA
22 51197266 rs61290853 A G 0.0001348 0.0001458 0.3599996 0.3552270 0.386353 0.4229230 NA
22 51198027 rs34939255 A G -0.0002198 0.0001651 0.1800002 0.1829861 0.254570 0.0984425 NA
22 51211106 rs9628250 T C -0.0003447 0.0001637 0.0350002 0.0351779 0.271566 0.1671330 NA
22 51212875 rs2238837 A C 0.0000408 0.0001555 0.7899998 0.7928247 0.331449 0.3724040 NA
22 51237063 rs3896457 T C 0.0001665 0.0001592 0.2999998 0.2956108 0.297976 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623777 ES:SE:LP:AF:ID  0.00035453:0.000239278:0.853872:0.623777:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400402 ES:SE:LP:AF:ID  -6.62405e-05:0.000237108:0.107905:0.400402:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456859 ES:SE:LP:AF:ID  0.000230634:0.000233426:0.49485:0.456859:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240945 ES:SE:LP:AF:ID  0.000206258:0.000266642:0.356547:0.240945:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.51567  ES:SE:LP:AF:ID  6.79395e-05:0.000165539:0.167491:0.51567:rs12029736
1   763394  rs3115847   G   A   .   PASS    AF=0.70676  ES:SE:LP:AF:ID  -9.78315e-05:0.000194071:0.21467:0.70676:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761337 ES:SE:LP:AF:ID  -6.31691e-05:0.000158408:0.161151:0.761337:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265361 ES:SE:LP:AF:ID  2.82239e-05:0.000176929:0.0604807:0.265361:rs12124819
1   798400  rs10900604  A   G   .   PASS    AF=0.206543 ES:SE:LP:AF:ID  7.91299e-05:0.000168978:0.19382:0.206543:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206373 ES:SE:LP:AF:ID  7.56696e-05:0.00016905:0.187087:0.206373:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.77267  ES:SE:LP:AF:ID  -0.000182941:0.000160814:0.585027:0.77267:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772899 ES:SE:LP:AF:ID  -0.000165787:0.000161084:0.522879:0.772899:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340384 ES:SE:LP:AF:ID  -0.00019559:0.000226971:0.408935:0.340384:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.697218 ES:SE:LP:AF:ID  0.000304891:0.000151846:1.34679:0.697218:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705356 ES:SE:LP:AF:ID  0.000252896:0.000149099:1.04576:0.705356:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705401 ES:SE:LP:AF:ID  0.000253701:0.000149094:1.05061:0.705401:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705586 ES:SE:LP:AF:ID  0.000255308:0.000149101:1.06048:0.705586:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705615 ES:SE:LP:AF:ID  0.000254858:0.000149116:1.06048:0.705615:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.730081 ES:SE:LP:AF:ID  0.000237204:0.00015318:0.920819:0.730081:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294418 ES:SE:LP:AF:ID  -0.00025539:0.00014911:1.06048:0.294418:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236739 ES:SE:LP:AF:ID  -0.000344225:0.000158743:1.52288:0.236739:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236727 ES:SE:LP:AF:ID  -0.000344227:0.000158745:1.52288:0.236727:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239785 ES:SE:LP:AF:ID  -0.000362254:0.000158234:1.65758:0.239785:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236729 ES:SE:LP:AF:ID  -0.000344191:0.000158744:1.52288:0.236729:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212464 ES:SE:LP:AF:ID  -0.000338949:0.000164991:1.39794:0.212464:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.21236  ES:SE:LP:AF:ID  -0.000336158:0.00016502:1.37675:0.21236:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.237213 ES:SE:LP:AF:ID  -0.000339209:0.000158623:1.49485:0.237213:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.213004 ES:SE:LP:AF:ID  -0.000334544:0.000164786:1.37675:0.213004:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212966 ES:SE:LP:AF:ID  -0.000331353:0.00016482:1.35655:0.212966:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241195 ES:SE:LP:AF:ID  -0.000324987:0.000157516:1.40894:0.241195:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213588 ES:SE:LP:AF:ID  -0.000320843:0.000164576:1.29243:0.213588:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269535 ES:SE:LP:AF:ID  -0.000240805:0.00015199:0.958607:0.269535:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213557 ES:SE:LP:AF:ID  -0.000316637:0.000164596:1.26761:0.213557:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214632 ES:SE:LP:AF:ID  -0.000306782:0.000164279:1.20761:0.214632:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246236 ES:SE:LP:AF:ID  -0.000206915:0.000156432:0.721246:0.246236:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270038 ES:SE:LP:AF:ID  -0.000228906:0.000152098:0.886057:0.270038:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400161 ES:SE:LP:AF:ID  -0.000124284:0.000137533:0.431798:0.400161:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237133 ES:SE:LP:AF:ID  -0.000265923:0.000159742:1.01773:0.237133:rs1574243
1   842013  rs7419119   T   G   .   PASS    AF=0.215438 ES:SE:LP:AF:ID  -0.000337803:0.000164388:1.39794:0.215438:rs7419119
1   842362  rs28540380  C   T   .   PASS    AF=0.235376 ES:SE:LP:AF:ID  -0.000272203:0.00016213:1.03152:0.235376:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362587 ES:SE:LP:AF:ID  0.000163675:0.000170721:0.468521:0.362587:rs11516185
1   844300  rs61769713  C   G   .   PASS    AF=0.818838 ES:SE:LP:AF:ID  -9.18849e-05:0.000175475:0.221849:0.818838:rs61769713
1   845283  rs7366404   G   T   .   PASS    AF=0.814517 ES:SE:LP:AF:ID  -7.51964e-05:0.000173922:0.173925:0.814517:rs7366404
1   845635  rs117086422 C   T   .   PASS    AF=0.20544  ES:SE:LP:AF:ID  -0.00021814:0.00016719:0.721246:0.20544:rs117086422
1   845938  rs57760052  G   A   .   PASS    AF=0.210879 ES:SE:LP:AF:ID  -0.000214565:0.000165583:0.69897:0.210879:rs57760052
1   846078  rs28612348  C   T   .   PASS    AF=0.196799 ES:SE:LP:AF:ID  -0.000273068:0.000169756:0.958607:0.196799:rs28612348
1   846338  rs4970334   A   G   .   PASS    AF=0.813849 ES:SE:LP:AF:ID  -7.56287e-05:0.000173775:0.180456:0.813849:rs4970334
1   846398  rs58781670  G   A   .   PASS    AF=0.204466 ES:SE:LP:AF:ID  -0.000212153:0.000167761:0.677781:0.204466:rs58781670
1   846489  rs4970333   T   C   .   PASS    AF=0.813941 ES:SE:LP:AF:ID  -8.22363e-05:0.000173895:0.19382:0.813941:rs4970333
1   846808  rs4475691   C   T   .   PASS    AF=0.198393 ES:SE:LP:AF:ID  -0.000281804:0.000169274:1.01773:0.198393:rs4475691