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-20549/UKB-b-20549_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20549/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20549/UKB-b-20549_data.vcf.gz ...
Read summary statistics for 4061180 SNPs.
Dropped 779 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, 964115 SNPs remain.
After merging with regression SNP LD, 964115 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0038 (0.0076)
Lambda GC: 1.0106
Mean Chi^2: 1.0064
Intercept: 1.001 (0.0085)
Ratio: 0.1607 (1.3444)
Analysis finished at Thu Oct 17 14:43:01 2019
Total time elapsed: 49.83s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.878,
    "inflation_factor": 1,
    "mean_EFFECT": 8.4859e-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": 33195,
    "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": 964115,
    "ldsc_nsnp_merge_regression_ld": 964115,
    "ldsc_observed_scale_h2_beta": 0.0038,
    "ldsc_observed_scale_h2_se": 0.0076,
    "ldsc_intercept_beta": 1.001,
    "ldsc_intercept_se": 0.0085,
    "ldsc_lambda_gc": 1.0106,
    "ldsc_mean_chisq": 1.0064,
    "ldsc_ratio": 0.1562
}

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 4060406 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 4061180 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 8.657316e+00 5.766815e+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 7.858100e+07 5.675009e+07 828.0000000 3.162994e+07 6.893375e+07 1.146910e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 8.500000e-06 1.403100e-03 -0.0085364 -9.210000e-04 8.900000e-06 9.325000e-04 8.498100e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.382700e-03 1.959000e-04 0.0011350 1.212800e-03 1.318200e-03 1.517000e-03 4.171200e-03 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.978808e-01 2.890995e-01 0.0000007 2.500000e-01 5.000000e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.978803e-01 2.890735e-01 0.0000007 2.465667e-01 4.965511e-01 7.482592e-01 9.999994e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.917072e-01 2.147269e-01 0.1143800 2.047070e-01 3.428945e-01 5.502930e-01 8.856200e-01 ▇▅▃▃▂
numeric AF_reference 33195 0.9918263 NA NA NA NA NA NA NA 3.809894e-01 2.182160e-01 0.0000000 2.014780e-01 3.396570e-01 5.383390e-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 -0.0010120 0.0020916 0.6300007 0.6284974 0.623812 0.782149 NA
1 54676 rs2462492 C T 0.0014613 0.0020856 0.4799997 0.4834989 0.399144 NA NA
1 91536 rs6702460 G T -0.0023716 0.0020513 0.2500000 0.2476342 0.455916 0.420727 NA
1 534192 rs6680723 C T -0.0015010 0.0023363 0.5199996 0.5205630 0.242057 NA NA
1 693731 rs12238997 A G 0.0008483 0.0019481 0.6600001 0.6632221 0.117313 0.141773 NA
1 706368 rs55727773 A G -0.0011670 0.0014460 0.4199997 0.4196538 0.513304 0.275160 NA
1 729679 rs4951859 C G -0.0015770 0.0016848 0.3500000 0.3492659 0.841441 0.639976 NA
1 731718 rs142557973 T C 0.0008056 0.0018505 0.6600001 0.6633139 0.123078 0.154353 NA
1 734349 rs141242758 T C 0.0008134 0.0018511 0.6600001 0.6603460 0.122330 0.152556 NA
1 736289 rs79010578 T A 0.0020262 0.0018171 0.2599998 0.2648195 0.134139 0.139577 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G -0.0000393 0.0014413 0.9800000 0.9782237 0.254586 0.0984425 NA
22 51208537 rs72619593 G A 0.0028790 0.0019261 0.1299999 0.1349849 0.120936 0.1142170 NA
22 51210289 rs112565862 C T 0.0006001 0.0019210 0.7499995 0.7547583 0.129762 0.1018370 NA
22 51211106 rs9628250 T C -0.0005029 0.0014298 0.7300002 0.7250596 0.271468 0.1671330 NA
22 51211392 rs3888396 T C 0.0004246 0.0019038 0.8200001 0.8235194 0.132383 0.1641370 NA
22 51212875 rs2238837 A C -0.0004513 0.0013591 0.7400005 0.7398527 0.331351 0.3724040 NA
22 51213613 rs34726907 C T 0.0003051 0.0018036 0.8700001 0.8656859 0.126422 0.1727240 NA
22 51216564 rs9616970 T C 0.0000669 0.0017965 0.9699999 0.9702853 0.126887 0.1563500 NA
22 51219006 rs28729663 G A -0.0003401 0.0017588 0.8499999 0.8466729 0.136315 0.2052720 NA
22 51237063 rs3896457 T C 0.0003530 0.0013885 0.8000000 0.7993141 0.298393 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623812 ES:SE:LP:AF:ID  -0.00101203:0.00209165:0.200659:0.623812:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.399144 ES:SE:LP:AF:ID  0.00146133:0.00208557:0.318759:0.399144:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.455916 ES:SE:LP:AF:ID  -0.00237155:0.00205131:0.60206:0.455916:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.242057 ES:SE:LP:AF:ID  -0.00150104:0.00233633:0.283997:0.242057:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.117313 ES:SE:LP:AF:ID  0.000848337:0.0019481:0.180456:0.117313:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.513304 ES:SE:LP:AF:ID  -0.00116697:0.00144602:0.376751:0.513304:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.841441 ES:SE:LP:AF:ID  -0.00157695:0.00168475:0.455932:0.841441:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.123078 ES:SE:LP:AF:ID  0.000805588:0.00185047:0.180456:0.123078:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12233  ES:SE:LP:AF:ID  0.000813426:0.00185107:0.180456:0.12233:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.134139 ES:SE:LP:AF:ID  0.00202622:0.00181712:0.585027:0.134139:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.837029 ES:SE:LP:AF:ID  -0.00110881:0.00162979:0.30103:0.837029:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.836733 ES:SE:LP:AF:ID  -0.00109277:0.00162859:0.30103:0.836733:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.868562 ES:SE:LP:AF:ID  -0.000228124:0.00175001:0.0457575:0.868562:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.131004 ES:SE:LP:AF:ID  0.000401535:0.0017545:0.0861861:0.131004:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.867976 ES:SE:LP:AF:ID  -0.000240912:0.00174719:0.05061:0.867976:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.86805  ES:SE:LP:AF:ID  -0.000274369:0.00174791:0.0555173:0.86805:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.867987 ES:SE:LP:AF:ID  -0.000247087:0.00174715:0.05061:0.867987:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.836159 ES:SE:LP:AF:ID  -0.000994598:0.00162383:0.267606:0.836159:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.836793 ES:SE:LP:AF:ID  -0.00101218:0.00162828:0.275724:0.836793:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.838109 ES:SE:LP:AF:ID  -0.000949143:0.0016512:0.244125:0.838109:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.868228 ES:SE:LP:AF:ID  -0.000211328:0.0017449:0.0457575:0.868228:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.867742 ES:SE:LP:AF:ID  -0.0001102:0.00174028:0.0222764:0.867742:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.866644 ES:SE:LP:AF:ID  -7.76416e-05:0.00173709:0.0177288:0.866644:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.867911 ES:SE:LP:AF:ID  -0.000180089:0.00174204:0.0362122:0.867911:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.867923 ES:SE:LP:AF:ID  -0.0001814:0.00174216:0.0362122:0.867923:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.867932 ES:SE:LP:AF:ID  -0.000162427:0.00174223:0.0315171:0.867932:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.868398 ES:SE:LP:AF:ID  -0.000248339:0.00174681:0.05061:0.868398:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.836369 ES:SE:LP:AF:ID  -0.00109942:0.00161978:0.30103:0.836369:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.836495 ES:SE:LP:AF:ID  -0.00106013:0.00162088:0.29243:0.836495:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.860851 ES:SE:LP:AF:ID  -0.00030356:0.00173605:0.0655015:0.860851:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.705804 ES:SE:LP:AF:ID  -0.00140061:0.00169408:0.387216:0.705804:rs3115847
1   768253  rs2977608   A   C   .   PASS    AF=0.758252 ES:SE:LP:AF:ID  0.000516764:0.00137307:0.148742:0.758252:rs2977608
1   769223  rs60320384  C   G   .   PASS    AF=0.13066  ES:SE:LP:AF:ID  0.000237164:0.00175383:0.05061:0.13066:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.867852 ES:SE:LP:AF:ID  -6.05943e-05:0.00174425:0.0132283:0.867852:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.130756 ES:SE:LP:AF:ID  0.000140353:0.00175266:0.0268721:0.130756:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.867878 ES:SE:LP:AF:ID  -6.69301e-05:0.00174436:0.0132283:0.867878:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.263729 ES:SE:LP:AF:ID  0.000666911:0.00155151:0.173925:0.263729:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.869067 ES:SE:LP:AF:ID  -0.000463084:0.00174895:0.102373:0.869067:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.129594 ES:SE:LP:AF:ID  0.000567538:0.00175562:0.124939:0.129594:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.129863 ES:SE:LP:AF:ID  0.000553955:0.00175263:0.124939:0.129863:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.867843 ES:SE:LP:AF:ID  -0.000339811:0.0017446:0.0705811:0.867843:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.130424 ES:SE:LP:AF:ID  0.000358273:0.00175296:0.0757207:0.130424:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.867493 ES:SE:LP:AF:ID  -0.000355452:0.00174409:0.0757207:0.867493:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.867448 ES:SE:LP:AF:ID  -0.000319863:0.0017453:0.0705811:0.867448:rs2980300
1   787399  rs2905055   G   T   .   PASS    AF=0.859749 ES:SE:LP:AF:ID  -6.65781e-05:0.00174476:0.0132283:0.859749:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.129403 ES:SE:LP:AF:ID  0.000605508:0.00176204:0.136677:0.129403:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.860334 ES:SE:LP:AF:ID  -0.000137911:0.00174574:0.0268721:0.860334:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.868172 ES:SE:LP:AF:ID  -0.000476356:0.00175121:0.102373:0.868172:rs2905053
1   791191  rs111818025 G   A   .   PASS    AF=0.128878 ES:SE:LP:AF:ID  0.000406481:0.00177275:0.0861861:0.128878:rs111818025
1   795988  rs59380221  C   T   .   PASS    AF=0.144405 ES:SE:LP:AF:ID  -0.000162195:0.00180462:0.0315171:0.144405:rs59380221