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-14342/UKB-b-14342_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14342/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:43:24 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14342/UKB-b-14342_data.vcf.gz ...
Read summary statistics for 3616178 SNPs.
Dropped 592 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, 878409 SNPs remain.
After merging with regression SNP LD, 878409 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0033 (0.0015)
Lambda GC: 1.1894
Mean Chi^2: 1.199
Intercept: 1.1654 (0.0099)
Ratio: 0.8311 (0.0497)
Analysis finished at Thu Oct 17 14:44:13 2019
Total time elapsed: 48.93s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8578,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 1.0731e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 9,
    "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": 29162,
    "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": 878409,
    "ldsc_nsnp_merge_regression_ld": 878409,
    "ldsc_observed_scale_h2_beta": 0.0033,
    "ldsc_observed_scale_h2_se": 0.0015,
    "ldsc_intercept_beta": 1.1654,
    "ldsc_intercept_se": 0.0099,
    "ldsc_lambda_gc": 1.1894,
    "ldsc_mean_chisq": 1.199,
    "ldsc_ratio": 0.8312
}

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 3615589 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 3616178 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 8.661550e+00 5.771600e+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 7.854173e+07 5.674914e+07 828.0000000 3.157877e+07 6.888844e+07 1.147161e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.100000e-06 1.876000e-04 -0.0010917 -1.232000e-04 1.000000e-07 1.252000e-04 1.063100e-03 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.707000e-04 1.900000e-05 0.0001450 1.542000e-04 1.647000e-04 1.840000e-04 5.304000e-04 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.728535e-01 2.957774e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.728553e-01 2.957539e-01 0.0000000 2.097796e-01 4.632475e-01 7.289673e-01 9.999998e-01 ▇▇▆▆▆
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 4.103281e-01 1.998093e-01 0.1432080 2.353880e-01 3.693470e-01 5.615120e-01 8.567920e-01 ▇▅▃▃▂
numeric AF_reference 29162 0.9919357 NA NA NA NA NA NA NA 3.972856e-01 2.080194e-01 0.0000000 2.270370e-01 3.636180e-01 5.489220e-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 -0.0000330 0.0002668 0.9000000 0.9016143 0.623771 0.782149 NA
1 54676 rs2462492 C T -0.0005116 0.0002643 0.0530005 0.0529063 0.400405 NA NA
1 91536 rs6702460 G T -0.0000824 0.0002603 0.7499995 0.7514688 0.456840 0.420727 NA
1 534192 rs6680723 C T 0.0001558 0.0002973 0.5999997 0.6002250 0.240957 NA NA
1 706368 rs55727773 A G -0.0001010 0.0001845 0.5800000 0.5841789 0.515616 0.275160 NA
1 729679 rs4951859 C G 0.0000626 0.0002159 0.7700005 0.7720306 0.843203 0.639976 NA
1 752566 rs3094315 G A 0.0001559 0.0002091 0.4600002 0.4557928 0.838942 0.718251 NA
1 752721 rs3131972 A G 0.0001504 0.0002089 0.4700002 0.4715075 0.838571 0.653355 NA
1 754503 rs3115859 G A 0.0001675 0.0002083 0.4199997 0.4211877 0.838022 0.663938 NA
1 754964 rs3131966 C T 0.0001795 0.0002089 0.3900004 0.3900094 0.838652 0.663339 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51182485 rs6009961 A G -0.0000825 0.0001743 0.6400000 0.6359643 0.715487 0.6383790 NA
22 51186143 rs2879914 T C 0.0001258 0.0001617 0.4400003 0.4365185 0.381784 0.2733630 NA
22 51186228 rs3865766 C T 0.0000255 0.0001576 0.8700001 0.8714436 0.451014 0.4532750 NA
22 51192586 rs5771006 G A 0.0004306 0.0002123 0.0430002 0.0425340 0.167599 0.0848642 NA
22 51193227 rs34608236 T G -0.0000088 0.0002170 0.9699999 0.9677770 0.168510 0.0692891 NA
22 51197266 rs61290853 A G -0.0000728 0.0001627 0.6499995 0.6547272 0.386293 0.4229230 NA
22 51198027 rs34939255 A G -0.0000771 0.0001841 0.6800001 0.6755094 0.254602 0.0984425 NA
22 51211106 rs9628250 T C -0.0000410 0.0001826 0.8200001 0.8224456 0.271576 0.1671330 NA
22 51212875 rs2238837 A C 0.0001031 0.0001735 0.5500004 0.5524261 0.331413 0.3724040 NA
22 51237063 rs3896457 T C 0.0000610 0.0001776 0.7300002 0.7312907 0.297939 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623771 ES:SE:LP:AF:ID  -3.29874e-05:0.00026684:0.0457575:0.623771:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400405 ES:SE:LP:AF:ID  -0.00051165:0.000264325:1.27572:0.400405:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.45684  ES:SE:LP:AF:ID  -8.24293e-05:0.000260273:0.124939:0.45684:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240957 ES:SE:LP:AF:ID  0.000155795:0.000297275:0.221849:0.240957:rs6680723
1   706368  rs12029736  A   G   .   PASS    AF=0.515616 ES:SE:LP:AF:ID  -0.000101002:0.000184549:0.236572:0.515616:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.843203 ES:SE:LP:AF:ID  6.25534e-05:0.00021591:0.113509:0.843203:rs4951859
1   752566  rs3094315   G   A   .   PASS    AF=0.838942 ES:SE:LP:AF:ID  0.000155937:0.000209089:0.337242:0.838942:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838571 ES:SE:LP:AF:ID  0.000150388:0.000208864:0.327902:0.838571:rs3131972
1   754503  rs3115859   G   A   .   PASS    AF=0.838022 ES:SE:LP:AF:ID  0.000167535:0.000208283:0.376751:0.838022:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838652 ES:SE:LP:AF:ID  0.000179543:0.000208868:0.408935:0.838652:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839764 ES:SE:LP:AF:ID  0.000165473:0.000211692:0.366532:0.839764:rs3131965
1   760912  rs1048488   C   T   .   PASS    AF=0.838301 ES:SE:LP:AF:ID  0.000152171:0.000207887:0.337242:0.838301:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838422 ES:SE:LP:AF:ID  0.000151429:0.000208034:0.327902:0.838422:rs3115850
1   763394  rs3115847   G   A   .   PASS    AF=0.70674  ES:SE:LP:AF:ID  0.000259314:0.000216373:0.638272:0.70674:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.761286 ES:SE:LP:AF:ID  0.000217919:0.000176591:0.657577:0.761286:rs2977608
1   776546  rs12124819  A   G   .   PASS    AF=0.265363 ES:SE:LP:AF:ID  0.000138002:0.000197276:0.318759:0.265363:rs12124819
1   798400  rs10900604  A   G   .   PASS    AF=0.206582 ES:SE:LP:AF:ID  -0.000194593:0.000188394:0.522879:0.206582:rs10900604
1   798959  rs11240777  G   A   .   PASS    AF=0.206411 ES:SE:LP:AF:ID  -0.000195021:0.000188476:0.522879:0.206411:rs11240777
1   808631  rs11240779  G   A   .   PASS    AF=0.772616 ES:SE:LP:AF:ID  0.000213191:0.000179293:0.638272:0.772616:rs11240779
1   808928  rs11240780  C   T   .   PASS    AF=0.772843 ES:SE:LP:AF:ID  0.000223131:0.000179595:0.677781:0.772843:rs11240780
1   814495  rs74461805  C   A   .   PASS    AF=0.340377 ES:SE:LP:AF:ID  -0.000351202:0.000253073:0.769551:0.340377:rs74461805
1   830181  rs28444699  A   G   .   PASS    AF=0.6972   ES:SE:LP:AF:ID  -0.000187348:0.000169297:0.568636:0.6972:rs28444699
1   831489  rs4970385   C   T   .   PASS    AF=0.705359 ES:SE:LP:AF:ID  -0.000111391:0.000166238:0.30103:0.705359:rs4970385
1   831909  rs9697642   C   T   .   PASS    AF=0.705403 ES:SE:LP:AF:ID  -0.000119238:0.000166233:0.327902:0.705403:rs9697642
1   832066  rs9697380   G   C   .   PASS    AF=0.705589 ES:SE:LP:AF:ID  -0.000122124:0.000166241:0.337242:0.705589:rs9697380
1   832318  rs4500250   C   A   .   PASS    AF=0.705618 ES:SE:LP:AF:ID  -0.000121962:0.000166258:0.337242:0.705618:rs4500250
1   832398  rs4553118   T   C   .   PASS    AF=0.73009  ES:SE:LP:AF:ID  -0.000215271:0.000170786:0.677781:0.73009:rs4553118
1   832918  rs28765502  T   C   .   PASS    AF=0.294415 ES:SE:LP:AF:ID  0.000120987:0.000166251:0.327902:0.294415:rs28765502
1   833223  rs13303211  C   T   .   PASS    AF=0.236717 ES:SE:LP:AF:ID  7.66215e-05:0.000176996:0.173925:0.236717:rs13303211
1   833302  rs28752186  C   T   .   PASS    AF=0.236706 ES:SE:LP:AF:ID  7.8536e-05:0.000176998:0.180456:0.236706:rs28752186
1   833641  rs28594623  T   C   .   PASS    AF=0.239766 ES:SE:LP:AF:ID  5.8944e-05:0.000176431:0.130768:0.239766:rs28594623
1   833824  rs28484835  T   C   .   PASS    AF=0.236707 ES:SE:LP:AF:ID  7.8394e-05:0.000176996:0.180456:0.236707:rs28484835
1   833927  rs28593608  T   C   .   PASS    AF=0.212436 ES:SE:LP:AF:ID  0.000197793:0.000183965:0.552842:0.212436:rs28593608
1   834198  rs28385272  T   C   .   PASS    AF=0.212333 ES:SE:LP:AF:ID  0.000194054:0.000183997:0.537602:0.212333:rs28385272
1   834832  rs4411087   G   C   .   PASS    AF=0.23719  ES:SE:LP:AF:ID  7.32176e-05:0.00017686:0.167491:0.23719:rs4411087
1   834928  rs4422949   A   G   .   PASS    AF=0.212975 ES:SE:LP:AF:ID  0.000197287:0.000183735:0.552842:0.212975:rs4422949
1   834999  rs28570054  G   A   .   PASS    AF=0.212937 ES:SE:LP:AF:ID  0.000193408:0.000183773:0.537602:0.212937:rs28570054
1   835499  rs4422948   A   G   .   PASS    AF=0.241179 ES:SE:LP:AF:ID  8.58394e-05:0.000175624:0.200659:0.241179:rs4422948
1   836529  rs28731045  C   G   .   PASS    AF=0.213555 ES:SE:LP:AF:ID  0.000201959:0.000183503:0.568636:0.213555:rs28731045
1   836896  rs28705752  T   C   .   PASS    AF=0.269512 ES:SE:LP:AF:ID  -1.31986e-05:0.000169467:0.0268721:0.269512:rs28705752
1   836924  rs72890788  G   A   .   PASS    AF=0.213525 ES:SE:LP:AF:ID  0.000203944:0.000183526:0.568636:0.213525:rs72890788
1   838387  rs4970384   T   C   .   PASS    AF=0.214597 ES:SE:LP:AF:ID  0.00018969:0.000183172:0.522879:0.214597:rs4970384
1   838555  rs4970383   C   A   .   PASS    AF=0.246205 ES:SE:LP:AF:ID  9.20358e-05:0.000174422:0.221849:0.246205:rs4970383
1   839103  rs28562941  A   G   .   PASS    AF=0.270021 ES:SE:LP:AF:ID  -1.04698e-05:0.000169587:0.0222764:0.270021:rs28562941
1   840753  rs4970382   T   C   .   PASS    AF=0.400161 ES:SE:LP:AF:ID  -5.44626e-05:0.000153341:0.142668:0.400161:rs4970382
1   841085  rs1574243   C   G   .   PASS    AF=0.237106 ES:SE:LP:AF:ID  5.36905e-05:0.00017811:0.119186:0.237106:rs1574243
1   842013  rs7419119   T   G   .   PASS    AF=0.215404 ES:SE:LP:AF:ID  0.000208488:0.000183294:0.585027:0.215404:rs7419119
1   842362  rs28540380  C   T   .   PASS    AF=0.235335 ES:SE:LP:AF:ID  0.000153077:0.000180779:0.39794:0.235335:rs28540380
1   843405  rs11516185  A   G   .   PASS    AF=0.362582 ES:SE:LP:AF:ID  -0.000252011:0.000190355:0.721246:0.362582:rs11516185
1   844300  rs61769713  C   G   .   PASS    AF=0.818767 ES:SE:LP:AF:ID  7.26711e-05:0.000195628:0.148742:0.818767:rs61769713