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-12885/UKB-b-12885_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12885/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:10 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-12885/UKB-b-12885_data.vcf.gz ...
Read summary statistics for 5570457 SNPs.
Dropped 2117 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, 1179863 SNPs remain.
After merging with regression SNP LD, 1179863 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0063 (0.0011)
Lambda GC: 1.0874
Mean Chi^2: 1.087
Intercept: 1.0279 (0.0068)
Ratio: 0.3203 (0.0787)
Analysis finished at Thu Oct 17 14:43:16 2019
Total time elapsed: 1.0m:5.7s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9178,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 4.0661e-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": 49085,
    "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": 1179863,
    "ldsc_nsnp_merge_regression_ld": 1179863,
    "ldsc_observed_scale_h2_beta": 0.0063,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0279,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.0874,
    "ldsc_mean_chisq": 1.087,
    "ldsc_ratio": 0.3207
}

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 5568356 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 5570457 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 8.672115e+00 5.763309e+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 7.859311e+07 5.656195e+07 828.0000000 3.199425e+07 6.902644e+07 1.145311e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.100000e-06 3.986000e-04 -0.0033120 -2.439000e-04 1.300000e-06 2.481000e-04 2.810400e-03 ▁▁▇▂▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.694000e-04 1.050000e-04 0.0002572 2.818000e-04 3.299000e-04 4.327000e-04 1.216100e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.871658e-01 2.918978e-01 0.0000002 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 4.871661e-01 2.918716e-01 0.0000002 2.309421e-01 4.827288e-01 7.402006e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.284936e-01 2.480888e-01 0.0454020 1.165910e-01 2.533880e-01 4.952410e-01 9.545980e-01 ▇▃▂▂▁
numeric AF_reference 49085 0.9911883 NA NA NA NA NA NA NA 3.238461e-01 2.424039e-01 0.0000000 1.244010e-01 2.587860e-01 4.852240e-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 -0.0007242 0.0004733 0.1299999 0.1259748 0.623778 0.7821490 NA
1 54676 rs2462492 C T 0.0000193 0.0004688 0.9699999 0.9671819 0.400378 NA NA
1 86028 rs114608975 T C 0.0000884 0.0007495 0.9100000 0.9061635 0.103557 0.0277556 NA
1 91536 rs6702460 G T -0.0005426 0.0004616 0.2399999 0.2398643 0.456860 0.4207270 NA
1 234313 rs8179466 C T -0.0004718 0.0009099 0.5999997 0.6041147 0.074523 NA NA
1 534192 rs6680723 C T 0.0005699 0.0005273 0.2800000 0.2797865 0.240951 NA NA
1 546697 rs12025928 A G -0.0007999 0.0006578 0.2200002 0.2239705 0.913472 NA NA
1 693731 rs12238997 A G -0.0004757 0.0004419 0.2800000 0.2816905 0.116347 0.1417730 NA
1 705882 rs72631875 G A 0.0006730 0.0006476 0.2999998 0.2986635 0.067274 0.0315495 NA
1 706368 rs55727773 A G -0.0000532 0.0003273 0.8700001 0.8708787 0.515631 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218224 rs9616975 C A 0.0001780 0.0005122 0.7300002 0.7282226 0.073319 0.0619010 NA
22 51218377 rs2519461 G C 0.0002001 0.0005116 0.6999999 0.6956554 0.073606 0.0826677 NA
22 51219006 rs28729663 G A -0.0003300 0.0003949 0.4000000 0.4033119 0.137948 0.2052720 NA
22 51219387 rs9616832 T C 0.0001706 0.0005127 0.7400005 0.7392694 0.073728 0.0654952 NA
22 51221190 rs369304721 G A 0.0001337 0.0006858 0.8499999 0.8454730 0.049716 NA NA
22 51221731 rs115055839 T C 0.0001672 0.0005130 0.7400005 0.7445063 0.073220 0.0625000 NA
22 51222100 rs114553188 G T -0.0008581 0.0006038 0.1600000 0.1552622 0.054470 0.0880591 NA
22 51223637 rs375798137 G A -0.0009154 0.0006067 0.1299999 0.1313357 0.054101 0.0788738 NA
22 51229805 rs9616985 T C 0.0001339 0.0005148 0.7899998 0.7947691 0.073055 0.0730831 NA
22 51237063 rs3896457 T C 0.0000416 0.0003148 0.8900000 0.8949788 0.297948 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623778 ES:SE:LP:AF:ID  -0.000724165:0.000473258:0.886057:0.623778:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400378 ES:SE:LP:AF:ID  1.92869e-05:0.000468777:0.0132283:0.400378:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103557 ES:SE:LP:AF:ID  8.83549e-05:0.000749539:0.0409586:0.103557:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45686  ES:SE:LP:AF:ID  -0.000542581:0.000461643:0.619789:0.45686:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074523 ES:SE:LP:AF:ID  -0.000471781:0.000909909:0.221849:0.074523:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240951 ES:SE:LP:AF:ID  0.000569887:0.000527283:0.552842:0.240951:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913472 ES:SE:LP:AF:ID  -0.000799855:0.000657755:0.657577:0.913472:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116347 ES:SE:LP:AF:ID  -0.00047567:0.000441855:0.552842:0.116347:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067274 ES:SE:LP:AF:ID  0.000673024:0.000647572:0.522879:0.067274:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515631 ES:SE:LP:AF:ID  -5.32055e-05:0.000327333:0.0604807:0.515631:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101197 ES:SE:LP:AF:ID  -0.00067755:0.000540063:0.677781:0.101197:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.053261 ES:SE:LP:AF:ID  0.000261323:0.00103214:0.09691:0.053261:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843206 ES:SE:LP:AF:ID  0.000132961:0.000382951:0.136677:0.843206:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055925 ES:SE:LP:AF:ID  -0.000546045:0.000620044:0.420216:0.055925:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  -0.000400947:0.000419141:0.468521:0.12233:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121571 ES:SE:LP:AF:ID  -0.00041323:0.000419324:0.49485:0.121571:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132336 ES:SE:LP:AF:ID  -0.000381089:0.000413305:0.443698:0.132336:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838943 ES:SE:LP:AF:ID  0.000239052:0.000370858:0.283997:0.838943:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838571 ES:SE:LP:AF:ID  0.000236882:0.000370459:0.283997:0.838571:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.86976  ES:SE:LP:AF:ID  0.000423703:0.000397512:0.537602:0.86976:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129892 ES:SE:LP:AF:ID  -0.000448174:0.000398316:0.585027:0.129892:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869102 ES:SE:LP:AF:ID  0.000416953:0.000396732:0.537602:0.869102:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869201 ES:SE:LP:AF:ID  0.000419489:0.00039689:0.537602:0.869201:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869105 ES:SE:LP:AF:ID  0.000424152:0.000396724:0.537602:0.869105:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838023 ES:SE:LP:AF:ID  0.00023338:0.000369427:0.275724:0.838023:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838653 ES:SE:LP:AF:ID  0.000225108:0.000370465:0.267606:0.838653:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839766 ES:SE:LP:AF:ID  0.000272503:0.000375474:0.327902:0.839766:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869384 ES:SE:LP:AF:ID  0.000422904:0.000396266:0.537602:0.869384:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868929 ES:SE:LP:AF:ID  0.000423102:0.000395267:0.552842:0.868929:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867885 ES:SE:LP:AF:ID  0.000394887:0.000394512:0.49485:0.867885:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869073 ES:SE:LP:AF:ID  0.000413109:0.000395592:0.522879:0.869073:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869082 ES:SE:LP:AF:ID  0.000413929:0.000395622:0.522879:0.869082:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869089 ES:SE:LP:AF:ID  0.000412491:0.000395631:0.522879:0.869089:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869568 ES:SE:LP:AF:ID  0.00041964:0.000396718:0.537602:0.869568:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838305 ES:SE:LP:AF:ID  0.000241859:0.000368728:0.29243:0.838305:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838424 ES:SE:LP:AF:ID  0.000237861:0.000368985:0.283997:0.838424:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862245 ES:SE:LP:AF:ID  0.000350002:0.000394209:0.431798:0.862245:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706739 ES:SE:LP:AF:ID  0.000318211:0.000383761:0.387216:0.706739:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105159 ES:SE:LP:AF:ID  -0.000598548:0.000442068:0.744727:0.105159:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761308 ES:SE:LP:AF:ID  -0.000253257:0.000313222:0.376751:0.761308:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106471 ES:SE:LP:AF:ID  0.000878777:0.000431785:1.37675:0.106471:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129596 ES:SE:LP:AF:ID  -0.000426575:0.000398081:0.552842:0.129596:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868893 ES:SE:LP:AF:ID  0.000455777:0.000395962:0.60206:0.868893:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129697 ES:SE:LP:AF:ID  -0.000471085:0.000397823:0.619789:0.129697:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868903 ES:SE:LP:AF:ID  0.000464196:0.00039597:0.619789:0.868903:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265404 ES:SE:LP:AF:ID  -0.000240535:0.000349876:0.309804:0.265404:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870025 ES:SE:LP:AF:ID  0.000433823:0.000396777:0.568636:0.870025:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095138 ES:SE:LP:AF:ID  0.000775242:0.000459896:1.03621:0.095138:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128597 ES:SE:LP:AF:ID  -0.000438645:0.000398336:0.568636:0.128597:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128893 ES:SE:LP:AF:ID  -0.000446591:0.000397661:0.585027:0.128893:rs4040617