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-16207/UKB-b-16207_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16207/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:44:57 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-16207/UKB-b-16207_data.vcf.gz ...
Read summary statistics for 5596645 SNPs.
Dropped 2151 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, 1182247 SNPs remain.
After merging with regression SNP LD, 1182247 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0121 (0.0013)
Lambda GC: 1.1071
Mean Chi^2: 1.1215
Intercept: 1.0073 (0.0074)
Ratio: 0.0602 (0.0611)
Analysis finished at Thu Oct 17 14:46:03 2019
Total time elapsed: 1.0m:5.51s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9182,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 4.7412e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 1,
    "n_p_sig": 1,
    "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": 49401,
    "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": 1182247,
    "ldsc_nsnp_merge_regression_ld": 1182247,
    "ldsc_observed_scale_h2_beta": 0.0121,
    "ldsc_observed_scale_h2_se": 0.0013,
    "ldsc_intercept_beta": 1.0073,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.1071,
    "ldsc_mean_chisq": 1.1215,
    "ldsc_ratio": 0.0601
}

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 5594510 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 5596645 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 8.672330e+00 5.763052e+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 7.858921e+07 5.655869e+07 828.0000000 3.199062e+07 6.901923e+07 1.145205e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 4.700000e-06 4.089000e-04 -0.0028860 -2.478000e-04 3.200000e-06 2.540000e-04 3.506900e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.735000e-04 1.073000e-04 0.0002591 2.841000e-04 3.331000e-04 4.380000e-04 1.225500e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.837247e-01 2.935098e-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 4.837244e-01 2.934834e-01 0.0000000 2.257009e-01 4.784477e-01 7.379019e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.274197e-01 2.484365e-01 0.0446210 1.153330e-01 2.518540e-01 4.941340e-01 9.553770e-01 ▇▃▂▂▁
numeric AF_reference 49401 0.9911731 NA NA NA NA NA NA NA 3.228517e-01 2.426674e-01 0.0000000 1.232030e-01 2.573880e-01 4.840260e-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 -0.0005322 0.0004769 0.2599998 0.2643732 0.623775 0.7821490 NA
1 54676 rs2462492 C T -0.0001764 0.0004724 0.7099994 0.7088861 0.400400 NA NA
1 86028 rs114608975 T C -0.0006249 0.0007553 0.4100001 0.4079879 0.103554 0.0277556 NA
1 91536 rs6702460 G T -0.0003762 0.0004651 0.4199997 0.4185816 0.456851 0.4207270 NA
1 234313 rs8179466 C T -0.0001889 0.0009171 0.8400000 0.8368143 0.074510 NA NA
1 534192 rs6680723 C T 0.0010883 0.0005313 0.0409996 0.0405401 0.240953 NA NA
1 546697 rs12025928 A G -0.0011205 0.0006627 0.0909997 0.0908798 0.913457 NA NA
1 693731 rs12238997 A G 0.0010098 0.0004452 0.0230001 0.0233350 0.116345 0.1417730 NA
1 705882 rs72631875 G A 0.0016067 0.0006524 0.0140001 0.0137939 0.067291 0.0315495 NA
1 706368 rs55727773 A G -0.0005412 0.0003298 0.1000000 0.1008390 0.515623 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218224 rs9616975 C A -0.0008148 0.0005161 0.1100001 0.1144275 0.073316 0.0619010 NA
22 51218377 rs2519461 G C -0.0007680 0.0005155 0.1400000 0.1362932 0.073604 0.0826677 NA
22 51219006 rs28729663 G A -0.0005315 0.0003979 0.1800002 0.1816625 0.137929 0.2052720 NA
22 51219387 rs9616832 T C -0.0008091 0.0005166 0.1199999 0.1172507 0.073728 0.0654952 NA
22 51221190 rs369304721 G A -0.0015136 0.0006911 0.0290001 0.0285078 0.049721 NA NA
22 51221731 rs115055839 T C -0.0008005 0.0005169 0.1199999 0.1214330 0.073218 0.0625000 NA
22 51222100 rs114553188 G T -0.0002334 0.0006084 0.6999999 0.7012221 0.054458 0.0880591 NA
22 51223637 rs375798137 G A -0.0002534 0.0006114 0.6800001 0.6785076 0.054087 0.0788738 NA
22 51229805 rs9616985 T C -0.0007667 0.0005188 0.1400000 0.1394310 0.073054 0.0730831 NA
22 51237063 rs3896457 T C 0.0001555 0.0003172 0.6200004 0.6240462 0.297980 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623775 ES:SE:LP:AF:ID  -0.000532237:0.000476866:0.585027:0.623775:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.4004   ES:SE:LP:AF:ID  -0.000176359:0.000472366:0.148742:0.4004:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103554 ES:SE:LP:AF:ID  -0.000624947:0.000755278:0.387216:0.103554:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456851 ES:SE:LP:AF:ID  -0.000376217:0.000465106:0.376751:0.456851:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.07451  ES:SE:LP:AF:ID  -0.00018889:0.000917075:0.0757207:0.07451:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240953 ES:SE:LP:AF:ID  0.00108828:0.000531334:1.38722:0.240953:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913457 ES:SE:LP:AF:ID  -0.00112048:0.000662702:1.04096:0.913457:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116345 ES:SE:LP:AF:ID  0.00100978:0.000445248:1.63827:0.116345:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067291 ES:SE:LP:AF:ID  0.0016067:0.000652444:1.85387:0.067291:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515623 ES:SE:LP:AF:ID  -0.000541208:0.000329844:1:0.515623:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101232 ES:SE:LP:AF:ID  -0.000225342:0.000544106:0.167491:0.101232:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.053254 ES:SE:LP:AF:ID  -0.00244364:0.00104016:1.72125:0.053254:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843205 ES:SE:LP:AF:ID  -0.000543074:0.000385894:0.79588:0.843205:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055924 ES:SE:LP:AF:ID  0.00164185:0.000624753:2.0655:0.055924:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122325 ES:SE:LP:AF:ID  0.000880072:0.000422369:1.4318:0.122325:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121569 ES:SE:LP:AF:ID  0.000882153:0.000422545:1.4318:0.121569:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132336 ES:SE:LP:AF:ID  0.000362408:0.000416484:0.420216:0.132336:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.83894  ES:SE:LP:AF:ID  -0.000547971:0.000373712:0.853872:0.83894:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838567 ES:SE:LP:AF:ID  -0.000566492:0.000373308:0.886057:0.838567:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869759 ES:SE:LP:AF:ID  -0.000986006:0.000400569:1.85387:0.869759:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129892 ES:SE:LP:AF:ID  0.000958955:0.000401385:1.76955:0.129892:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869101 ES:SE:LP:AF:ID  -0.00101096:0.000399784:1.95861:0.869101:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869199 ES:SE:LP:AF:ID  -0.00101678:0.000399943:1.95861:0.869199:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869104 ES:SE:LP:AF:ID  -0.00102225:0.000399776:1.95861:0.869104:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.83802  ES:SE:LP:AF:ID  -0.00055219:0.000372273:0.853872:0.83802:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.83865  ES:SE:LP:AF:ID  -0.000590911:0.000373319:0.958607:0.83865:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839764 ES:SE:LP:AF:ID  -0.000618806:0.000378366:1:0.839764:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869384 ES:SE:LP:AF:ID  -0.000979217:0.000399315:1.85387:0.869384:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868931 ES:SE:LP:AF:ID  -0.000972067:0.00039831:1.82391:0.868931:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867883 ES:SE:LP:AF:ID  -0.000962104:0.000397545:1.79588:0.867883:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869075 ES:SE:LP:AF:ID  -0.000957536:0.000398636:1.79588:0.869075:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869083 ES:SE:LP:AF:ID  -0.000958373:0.000398667:1.79588:0.869083:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869091 ES:SE:LP:AF:ID  -0.000958477:0.000398676:1.79588:0.869091:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869568 ES:SE:LP:AF:ID  -0.000968883:0.00039977:1.82391:0.869568:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838301 ES:SE:LP:AF:ID  -0.000505805:0.000371568:0.769551:0.838301:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838422 ES:SE:LP:AF:ID  -0.000505293:0.00037183:0.769551:0.838422:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862245 ES:SE:LP:AF:ID  -0.000870158:0.000397243:1.55284:0.862245:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706732 ES:SE:LP:AF:ID  -0.000526435:0.000386702:0.769551:0.706732:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105154 ES:SE:LP:AF:ID  0.000854968:0.000445481:1.25964:0.105154:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761315 ES:SE:LP:AF:ID  -0.00071904:0.000315641:1.63827:0.761315:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106459 ES:SE:LP:AF:ID  0.000303367:0.000435086:0.309804:0.106459:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129596 ES:SE:LP:AF:ID  0.000876225:0.000401145:1.5376:0.129596:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868891 ES:SE:LP:AF:ID  -0.000965552:0.000399005:1.79588:0.868891:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129697 ES:SE:LP:AF:ID  0.000877057:0.000400886:1.5376:0.129697:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868901 ES:SE:LP:AF:ID  -0.000969982:0.000399013:1.82391:0.868901:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265394 ES:SE:LP:AF:ID  0.000173412:0.000352539:0.207608:0.265394:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870021 ES:SE:LP:AF:ID  -0.000961003:0.000399825:1.79588:0.870021:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095119 ES:SE:LP:AF:ID  0.000176252:0.000463446:0.154902:0.095119:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128598 ES:SE:LP:AF:ID  0.000883407:0.000401402:1.55284:0.128598:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128894 ES:SE:LP:AF:ID  0.000895214:0.000400722:1.60206:0.128894:rs4040617