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-9596/UKB-b-9596_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9596/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:50 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-9596/UKB-b-9596_data.vcf.gz ...
Read summary statistics for 5774772 SNPs.
Dropped 2438 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, 1197829 SNPs remain.
After merging with regression SNP LD, 1197829 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.004 (0.0012)
Lambda GC: 1.0561
Mean Chi^2: 1.0518
Intercept: 1.0145 (0.0074)
Ratio: 0.2794 (0.1422)
Analysis finished at Thu Oct 17 14:43:57 2019
Total time elapsed: 1.0m:6.52s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9212,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 2.5517e-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": 51581,
    "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": 1197829,
    "ldsc_nsnp_merge_regression_ld": 1197829,
    "ldsc_observed_scale_h2_beta": 0.004,
    "ldsc_observed_scale_h2_se": 0.0012,
    "ldsc_intercept_beta": 1.0145,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.0561,
    "ldsc_mean_chisq": 1.0518,
    "ldsc_ratio": 0.2799
}

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 5772350 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 5774772 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 8.670496e+00 5.762428e+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 7.859522e+07 5.654637e+07 828.0000000 3.199257e+07 6.903138e+07 1.145218e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.600000e-06 4.374000e-04 -0.0038529 -2.638000e-04 1.100000e-06 2.673000e-04 3.612400e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 4.084000e-04 1.259000e-04 0.0002764 3.041000e-04 3.602000e-04 4.831000e-04 1.325200e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.910297e-01 2.907332e-01 0.0000000 2.399999e-01 4.899999e-01 7.400005e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.910292e-01 2.907079e-01 0.0000000 2.377097e-01 4.881360e-01 7.427306e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.204063e-01 2.507844e-01 0.0394910 1.069790e-01 2.420090e-01 4.866620e-01 9.605080e-01 ▇▃▂▂▁
numeric AF_reference 51581 0.9910679 NA NA NA NA NA NA NA 3.163256e-01 2.444891e-01 0.0000000 1.152160e-01 2.484030e-01 4.766370e-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 -0.0003442 0.0005087 0.5000000 0.4986333 0.623763 0.7821490 NA
1 54676 rs2462492 C T -0.0000902 0.0005040 0.8600001 0.8578732 0.400432 NA NA
1 86028 rs114608975 T C -0.0000504 0.0008058 0.9500000 0.9501101 0.103549 0.0277556 NA
1 91536 rs6702460 G T 0.0002021 0.0004963 0.6800001 0.6838111 0.456866 0.4207270 NA
1 234313 rs8179466 C T 0.0010784 0.0009783 0.2700001 0.2703485 0.074519 NA NA
1 534192 rs6680723 C T 0.0000400 0.0005669 0.9400001 0.9436977 0.240923 NA NA
1 546697 rs12025928 A G -0.0007756 0.0007070 0.2700001 0.2726399 0.913452 NA NA
1 693731 rs12238997 A G 0.0008285 0.0004749 0.0810009 0.0810876 0.116339 0.1417730 NA
1 705882 rs72631875 G A 0.0007303 0.0006960 0.2900000 0.2940991 0.067289 0.0315495 NA
1 706368 rs55727773 A G -0.0003012 0.0003519 0.3900004 0.3919780 0.515638 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C -0.0002347 0.0005499 0.6700003 0.6695599 0.073612 0.0826677 NA
22 51219006 rs28729663 G A -0.0004287 0.0004244 0.3100002 0.3124855 0.137972 0.2052720 NA
22 51219387 rs9616832 T C -0.0002992 0.0005510 0.5900000 0.5870930 0.073734 0.0654952 NA
22 51219704 rs147475742 G A -0.0008984 0.0007384 0.2200002 0.2236968 0.041941 0.0473243 NA
22 51221190 rs369304721 G A -0.0002431 0.0007371 0.7400005 0.7415263 0.049723 NA NA
22 51221731 rs115055839 T C -0.0002510 0.0005513 0.6499995 0.6489485 0.073224 0.0625000 NA
22 51222100 rs114553188 G T -0.0005044 0.0006488 0.4400003 0.4368900 0.054493 0.0880591 NA
22 51223637 rs375798137 G A -0.0005577 0.0006519 0.3900004 0.3923098 0.054122 0.0788738 NA
22 51229805 rs9616985 T C -0.0002513 0.0005533 0.6499995 0.6496769 0.073060 0.0730831 NA
22 51237063 rs3896457 T C 0.0004584 0.0003384 0.1800002 0.1755916 0.297978 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  -0.000344211:0.000508705:0.30103:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400432 ES:SE:LP:AF:ID  -9.02497e-05:0.000503957:0.0655015:0.400432:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103549 ES:SE:LP:AF:ID  -5.04195e-05:0.000805829:0.0222764:0.103549:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456866 ES:SE:LP:AF:ID  0.000202108:0.000496253:0.167491:0.456866:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074519 ES:SE:LP:AF:ID  0.00107836:0.000978317:0.568636:0.074519:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240923 ES:SE:LP:AF:ID  4.0035e-05:0.000566882:0.0268721:0.240923:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913452 ES:SE:LP:AF:ID  -0.000775622:0.000707037:0.568636:0.913452:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116339 ES:SE:LP:AF:ID  0.000828504:0.000474948:1.09151:0.116339:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067289 ES:SE:LP:AF:ID  0.000730254:0.000696029:0.537602:0.067289:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515638 ES:SE:LP:AF:ID  -0.000301221:0.000351879:0.408935:0.515638:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.10121  ES:SE:LP:AF:ID  -9.22575e-05:0.000580443:0.0604807:0.10121:rs116030099
1   723891  rs2977670   G   C   .   PASS    AF=0.959108 ES:SE:LP:AF:ID  -7.98102e-05:0.000768576:0.0362122:0.959108:rs2977670
1   725060  rs865924913 A   T   .   PASS    AF=0.053259 ES:SE:LP:AF:ID  -0.000207917:0.00110968:0.0705811:0.053259:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843209 ES:SE:LP:AF:ID  -0.000730127:0.00041163:1.11919:0.843209:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055938 ES:SE:LP:AF:ID  0.000423722:0.000666358:0.283997:0.055938:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122328 ES:SE:LP:AF:ID  0.000838594:0.000450518:1.20066:0.122328:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121572 ES:SE:LP:AF:ID  0.000864112:0.000450706:1.25964:0.121572:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132346 ES:SE:LP:AF:ID  0.000595958:0.000444243:0.744727:0.132346:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838925 ES:SE:LP:AF:ID  -0.000543581:0.000398627:0.769551:0.838925:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838557 ES:SE:LP:AF:ID  -0.00059852:0.000398201:0.886057:0.838557:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869744 ES:SE:LP:AF:ID  -0.000759987:0.000427267:1.12494:0.869744:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129904 ES:SE:LP:AF:ID  0.000827952:0.000428139:1.27572:0.129904:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869089 ES:SE:LP:AF:ID  -0.000819824:0.000426436:1.25964:0.869089:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869185 ES:SE:LP:AF:ID  -0.000798495:0.000426604:1.21467:0.869185:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869092 ES:SE:LP:AF:ID  -0.000820929:0.000426427:1.26761:0.869092:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838009 ES:SE:LP:AF:ID  -0.000580502:0.000397092:0.853872:0.838009:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.83864  ES:SE:LP:AF:ID  -0.000604025:0.00039821:0.886057:0.83864:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.83975  ES:SE:LP:AF:ID  -0.000515115:0.000403593:0.69897:0.83975:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869368 ES:SE:LP:AF:ID  -0.00073857:0.000425927:1.08092:0.869368:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868914 ES:SE:LP:AF:ID  -0.000782411:0.000424854:1.18046:0.868914:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867871 ES:SE:LP:AF:ID  -0.000790799:0.000424045:1.20761:0.867871:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869058 ES:SE:LP:AF:ID  -0.000752564:0.000425204:1.11351:0.869058:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869067 ES:SE:LP:AF:ID  -0.000751832:0.000425236:1.11351:0.869067:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869075 ES:SE:LP:AF:ID  -0.000754203:0.000425246:1.11919:0.869075:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869552 ES:SE:LP:AF:ID  -0.000744504:0.000426415:1.09151:0.869552:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838286 ES:SE:LP:AF:ID  -0.000493463:0.000396337:0.677781:0.838286:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838406 ES:SE:LP:AF:ID  -0.000483783:0.000396615:0.657577:0.838406:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862234 ES:SE:LP:AF:ID  -0.000749859:0.000423723:1.11351:0.862234:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706713 ES:SE:LP:AF:ID  -0.000522697:0.000412476:0.677781:0.706713:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105176 ES:SE:LP:AF:ID  0.000666053:0.000475147:0.79588:0.105176:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761305 ES:SE:LP:AF:ID  -0.000569221:0.000336709:1.04096:0.761305:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106457 ES:SE:LP:AF:ID  0.000201144:0.000464172:0.180456:0.106457:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.12961  ES:SE:LP:AF:ID  0.000736788:0.000427875:1.07058:0.12961:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868878 ES:SE:LP:AF:ID  -0.00076158:0.0004256:1.13077:0.868878:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129711 ES:SE:LP:AF:ID  0.000716984:0.0004276:1.02687:0.129711:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868888 ES:SE:LP:AF:ID  -0.000765673:0.000425609:1.14267:0.868888:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265378 ES:SE:LP:AF:ID  -0.000406173:0.000376091:0.552842:0.265378:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870014 ES:SE:LP:AF:ID  -0.000757421:0.000426482:1.11919:0.870014:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095125 ES:SE:LP:AF:ID  -0.000135451:0.00049439:0.107905:0.095125:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128606 ES:SE:LP:AF:ID  0.000691656:0.000428158:0.958607:0.128606:rs1055606