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-19255/UKB-b-19255_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19255/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:41:06 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-19255/UKB-b-19255_data.vcf.gz ...
Read summary statistics for 4810335 SNPs.
Dropped 1251 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, 1088871 SNPs remain.
After merging with regression SNP LD, 1088871 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0034 (0.0011)
Lambda GC: 1.0402
Mean Chi^2: 1.044
Intercept: 1.0113 (0.0077)
Ratio: 0.2566 (0.1743)
Analysis finished at Thu Oct 17 14:42:06 2019
Total time elapsed: 59.99s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9018,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 6.0507e-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": 40654,
    "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": 1088871,
    "ldsc_nsnp_merge_regression_ld": 1088871,
    "ldsc_observed_scale_h2_beta": 0.0034,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0113,
    "ldsc_intercept_se": 0.0077,
    "ldsc_lambda_gc": 1.0402,
    "ldsc_mean_chisq": 1.044,
    "ldsc_ratio": 0.2568
}

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 4809093 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 4810335 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 8.667509e+00 5.767113e+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 7.857351e+07 5.665745e+07 828.0000000 3.185715e+07 6.893074e+07 1.146405e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 6.000000e-07 2.764000e-04 -0.0021145 -1.767000e-04 0.000000e+00 1.776000e-04 2.295300e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.653000e-04 5.430000e-05 0.0002025 2.190000e-04 2.461000e-04 3.006000e-04 7.690000e-04 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.939731e-01 2.906102e-01 0.0000001 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 4.939725e-01 2.905850e-01 0.0000001 2.409899e-01 4.917049e-01 7.457386e-01 9.999996e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.597712e-01 2.343728e-01 0.0742470 1.575160e-01 2.975480e-01 5.255690e-01 9.257530e-01 ▇▅▃▂▂
numeric AF_reference 40654 0.9915486 NA NA NA NA NA NA NA 3.523715e-01 2.322113e-01 0.0000000 1.607430e-01 2.987220e-01 5.145770e-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 -0.0005546 0.0003726 0.1400000 0.1366344 0.623788 0.7821490 NA
1 54676 rs2462492 C T -0.0000889 0.0003691 0.8100000 0.8096588 0.400410 NA NA
1 86028 rs114608975 T C -0.0001554 0.0005902 0.7899998 0.7923235 0.103546 0.0277556 NA
1 91536 rs6702460 G T -0.0000441 0.0003634 0.9000000 0.9035186 0.456857 0.4207270 NA
1 234313 rs8179466 C T -0.0006641 0.0007166 0.3500000 0.3541034 0.074507 NA NA
1 534192 rs6680723 C T 0.0002442 0.0004152 0.5600000 0.5564055 0.240959 NA NA
1 546697 rs12025928 A G -0.0004686 0.0005180 0.3700002 0.3656060 0.913490 NA NA
1 693731 rs12238997 A G -0.0002006 0.0003479 0.5600000 0.5642528 0.116342 0.1417730 NA
1 706368 rs55727773 A G -0.0001945 0.0002577 0.4500005 0.4503493 0.515584 0.2751600 NA
1 722670 rs116030099 T C 0.0003673 0.0004252 0.3900004 0.3876337 0.101206 0.0413339 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51202748 rs9616963 A G -0.0003240 0.0003998 0.4199997 0.4177238 0.075574 0.0391374 NA
22 51208537 rs72619593 G A 0.0006483 0.0003436 0.0589997 0.0591870 0.120739 0.1142170 NA
22 51210289 rs112565862 C T 0.0002500 0.0003423 0.4700002 0.4651963 0.129921 0.1018370 NA
22 51211106 rs9628250 T C -0.0002529 0.0002548 0.3200000 0.3209629 0.271589 0.1671330 NA
22 51211392 rs3888396 T C 0.0002441 0.0003392 0.4700002 0.4717726 0.132595 0.1641370 NA
22 51212875 rs2238837 A C 0.0002279 0.0002421 0.3500000 0.3466077 0.331467 0.3724040 NA
22 51213613 rs34726907 C T -0.0002864 0.0003190 0.3700002 0.3693392 0.127800 0.1727240 NA
22 51216564 rs9616970 T C -0.0002641 0.0003177 0.4100001 0.4057142 0.128317 0.1563500 NA
22 51219006 rs28729663 G A -0.0002476 0.0003109 0.4299995 0.4259063 0.137943 0.2052720 NA
22 51237063 rs3896457 T C 0.0004164 0.0002479 0.0929994 0.0929711 0.298005 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623788 ES:SE:LP:AF:ID  -0.000554577:0.000372589:0.853872:0.623788:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.40041  ES:SE:LP:AF:ID  -8.89066e-05:0.000369112:0.091515:0.40041:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103546 ES:SE:LP:AF:ID  -0.000155392:0.000590183:0.102373:0.103546:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456857 ES:SE:LP:AF:ID  -4.40533e-05:0.000363423:0.0457575:0.456857:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074507 ES:SE:LP:AF:ID  -0.000664084:0.000716643:0.455932:0.074507:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240959 ES:SE:LP:AF:ID  0.000244209:0.000415188:0.251812:0.240959:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.91349  ES:SE:LP:AF:ID  -0.000468648:0.000517995:0.431798:0.91349:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116342 ES:SE:LP:AF:ID  -0.000200581:0.000347907:0.251812:0.116342:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515584 ES:SE:LP:AF:ID  -0.000194531:0.000257714:0.346787:0.515584:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101206 ES:SE:LP:AF:ID  0.000367346:0.00042521:0.408935:0.101206:rs116030099
1   729679  rs4951859   C   G   .   PASS    AF=0.843178 ES:SE:LP:AF:ID  0.000206964:0.000301518:0.309804:0.843178:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122324 ES:SE:LP:AF:ID  -0.000282976:0.000330029:0.408935:0.122324:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121567 ES:SE:LP:AF:ID  -0.00030104:0.000330162:0.443698:0.121567:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132371 ES:SE:LP:AF:ID  -0.00010374:0.000325409:0.124939:0.132371:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838923 ES:SE:LP:AF:ID  0.0002003:0.000292001:0.309804:0.838923:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838551 ES:SE:LP:AF:ID  0.000212898:0.000291687:0.327902:0.838551:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869773 ES:SE:LP:AF:ID  0.000278357:0.000312992:0.431798:0.869773:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129876 ES:SE:LP:AF:ID  -0.000281473:0.000313631:0.431798:0.129876:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869115 ES:SE:LP:AF:ID  0.000294323:0.000312381:0.455932:0.869115:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869212 ES:SE:LP:AF:ID  0.000299744:0.000312505:0.468521:0.869212:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  0.000285186:0.000312374:0.443698:0.869117:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838004 ES:SE:LP:AF:ID  0.000218531:0.000290881:0.346787:0.838004:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838637 ES:SE:LP:AF:ID  0.00022437:0.000291701:0.356547:0.838637:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839752 ES:SE:LP:AF:ID  0.000210536:0.00029564:0.318759:0.839752:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869397 ES:SE:LP:AF:ID  0.000264612:0.000312012:0.39794:0.869397:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868944 ES:SE:LP:AF:ID  0.000250936:0.000311226:0.376751:0.868944:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867895 ES:SE:LP:AF:ID  0.000319353:0.00031063:0.522879:0.867895:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869087 ES:SE:LP:AF:ID  0.000267199:0.000311481:0.408935:0.869087:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  0.000264746:0.000311505:0.39794:0.869095:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869103 ES:SE:LP:AF:ID  0.000266994:0.000311512:0.408935:0.869103:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869581 ES:SE:LP:AF:ID  0.000269703:0.000312367:0.408935:0.869581:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838285 ES:SE:LP:AF:ID  0.00022937:0.000290327:0.366532:0.838285:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838406 ES:SE:LP:AF:ID  0.000237295:0.000290532:0.387216:0.838406:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862249 ES:SE:LP:AF:ID  0.000277759:0.000310393:0.431798:0.862249:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706771 ES:SE:LP:AF:ID  -8.23366e-05:0.000302161:0.102373:0.706771:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105159 ES:SE:LP:AF:ID  -9.68258e-05:0.000348072:0.107905:0.105159:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761255 ES:SE:LP:AF:ID  4.67027e-05:0.000246616:0.0705811:0.761255:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106528 ES:SE:LP:AF:ID  0.000263196:0.000339899:0.356547:0.106528:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129582 ES:SE:LP:AF:ID  -0.000247176:0.000313442:0.366532:0.129582:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868903 ES:SE:LP:AF:ID  0.000280811:0.000311769:0.431798:0.868903:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129683 ES:SE:LP:AF:ID  -0.000249721:0.000313238:0.366532:0.129683:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868913 ES:SE:LP:AF:ID  0.000280161:0.000311775:0.431798:0.868913:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265374 ES:SE:LP:AF:ID  0.000244996:0.000275497:0.431798:0.265374:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870033 ES:SE:LP:AF:ID  0.000289567:0.000312411:0.455932:0.870033:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095179 ES:SE:LP:AF:ID  0.000341587:0.000362053:0.455932:0.095179:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128585 ES:SE:LP:AF:ID  -0.00025738:0.000313642:0.387216:0.128585:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128883 ES:SE:LP:AF:ID  -0.000269251:0.000313109:0.408935:0.128883:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868775 ES:SE:LP:AF:ID  0.00030487:0.000311581:0.481486:0.868775:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.101898 ES:SE:LP:AF:ID  -0.00016547:0.000353025:0.19382:0.101898:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.129523 ES:SE:LP:AF:ID  -0.000292607:0.000313011:0.455932:0.129523:rs6594026