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-2399/UKB-b-2399_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2399/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:43 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2399/UKB-b-2399_data.vcf.gz ...
Read summary statistics for 5351042 SNPs.
Dropped 1827 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, 1157732 SNPs remain.
After merging with regression SNP LD, 1157732 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0027 (0.0011)
Lambda GC: 1.0378
Mean Chi^2: 1.0385
Intercept: 1.0132 (0.0072)
Ratio: 0.3416 (0.1869)
Analysis finished at Thu Oct 17 14:43:47 2019
Total time elapsed: 1.0m:3.92s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9138,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 7.9221e-07,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 18,
    "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": 46516,
    "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": 1157732,
    "ldsc_nsnp_merge_regression_ld": 1157732,
    "ldsc_observed_scale_h2_beta": 0.0027,
    "ldsc_observed_scale_h2_se": 0.0011,
    "ldsc_intercept_beta": 1.0132,
    "ldsc_intercept_se": 0.0072,
    "ldsc_lambda_gc": 1.0378,
    "ldsc_mean_chisq": 1.0385,
    "ldsc_ratio": 0.3429
}

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 5349229 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 5351042 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 8.673300e+00 5.762871e+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 7.853415e+07 5.656366e+07 828.0000000 3.192561e+07 6.895513e+07 1.144766e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 8.000000e-07 3.514000e-04 -0.0026017 -2.188000e-04 2.000000e-07 2.207000e-04 3.029300e-03 ▁▂▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.344000e-04 8.690000e-05 0.0002396 2.615000e-04 3.023000e-04 3.879000e-04 1.132800e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.938218e-01 2.895187e-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 4.938196e-01 2.894948e-01 0.0000000 2.418798e-01 4.921669e-01 7.434885e-01 9.999998e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.373025e-01 2.447120e-01 0.0526080 1.276062e-01 2.659645e-01 5.040840e-01 9.473920e-01 ▇▃▂▂▂
numeric AF_reference 46516 0.9913071 NA NA NA NA NA NA NA 3.319448e-01 2.398342e-01 0.0000000 1.343850e-01 2.699680e-01 4.938100e-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 -0.0004399 0.0004409 0.3200000 0.3183467 0.623762 0.7821490 NA
1 54676 rs2462492 C T 0.0002073 0.0004368 0.6400000 0.6350623 0.400372 NA NA
1 86028 rs114608975 T C 0.0004631 0.0006984 0.5099998 0.5072467 0.103543 0.0277556 NA
1 91536 rs6702460 G T -0.0001986 0.0004300 0.6400000 0.6441487 0.456820 0.4207270 NA
1 234313 rs8179466 C T 0.0003221 0.0008479 0.6999999 0.7040493 0.074517 NA NA
1 534192 rs6680723 C T 0.0003190 0.0004913 0.5199996 0.5160672 0.240953 NA NA
1 546697 rs12025928 A G 0.0002684 0.0006127 0.6600001 0.6614201 0.913465 NA NA
1 693731 rs12238997 A G -0.0001115 0.0004116 0.7899998 0.7865563 0.116341 0.1417730 NA
1 705882 rs72631875 G A -0.0004558 0.0006032 0.4500005 0.4498802 0.067294 0.0315495 NA
1 706368 rs55727773 A G -0.0000950 0.0003049 0.7600007 0.7552565 0.515612 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51217954 rs9616974 G A -0.0007835 0.0004769 0.1000000 0.1004189 0.073303 0.0621006 NA
22 51218224 rs9616975 C A -0.0007791 0.0004771 0.1000000 0.1024982 0.073325 0.0619010 NA
22 51218377 rs2519461 G C -0.0007769 0.0004765 0.1000000 0.1030239 0.073614 0.0826677 NA
22 51219006 rs28729663 G A -0.0007267 0.0003679 0.0479999 0.0482061 0.137937 0.2052720 NA
22 51219387 rs9616832 T C -0.0008116 0.0004775 0.0890000 0.0891868 0.073738 0.0654952 NA
22 51221731 rs115055839 T C -0.0007729 0.0004778 0.1100001 0.1057341 0.073227 0.0625000 NA
22 51222100 rs114553188 G T -0.0006857 0.0005625 0.2200002 0.2228175 0.054455 0.0880591 NA
22 51223637 rs375798137 G A -0.0007215 0.0005652 0.2000000 0.2018261 0.054084 0.0788738 NA
22 51229805 rs9616985 T C -0.0007853 0.0004795 0.1000000 0.1014864 0.073062 0.0730831 NA
22 51237063 rs3896457 T C 0.0002255 0.0002933 0.4400003 0.4419871 0.297965 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623762 ES:SE:LP:AF:ID  -0.000439939:0.000440882:0.49485:0.623762:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400372 ES:SE:LP:AF:ID  0.000207317:0.000436812:0.19382:0.400372:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103543 ES:SE:LP:AF:ID  0.000463128:0.000698396:0.29243:0.103543:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.45682  ES:SE:LP:AF:ID  -0.000198627:0.000430016:0.19382:0.45682:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074517 ES:SE:LP:AF:ID  0.000322089:0.000847915:0.154902:0.074517:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240953 ES:SE:LP:AF:ID  0.000319028:0.000491251:0.283997:0.240953:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913465 ES:SE:LP:AF:ID  0.000268355:0.000612748:0.180456:0.913465:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116341 ES:SE:LP:AF:ID  -0.000111466:0.00041164:0.102373:0.116341:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067294 ES:SE:LP:AF:ID  -0.00045578:0.000603191:0.346787:0.067294:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515612 ES:SE:LP:AF:ID  -9.50487e-05:0.000304921:0.119186:0.515612:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101243 ES:SE:LP:AF:ID  -2.59976e-05:0.000503038:0.0177288:0.101243:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.053264 ES:SE:LP:AF:ID  -0.00123128:0.000961654:0.69897:0.053264:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843183 ES:SE:LP:AF:ID  2.5992e-05:0.00035672:0.0268721:0.843183:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055895 ES:SE:LP:AF:ID  -0.00072712:0.000577685:0.677781:0.055895:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122321 ES:SE:LP:AF:ID  -0.000182134:0.000390474:0.19382:0.122321:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121561 ES:SE:LP:AF:ID  -0.000121608:0.000390639:0.119186:0.121561:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132354 ES:SE:LP:AF:ID  -0.00010503:0.000384989:0.107905:0.132354:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838918 ES:SE:LP:AF:ID  2.02038e-05:0.000345459:0.0222764:0.838918:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838545 ES:SE:LP:AF:ID  1.79709e-05:0.000345086:0.0177288:0.838545:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869759 ES:SE:LP:AF:ID  0.000166231:0.000370297:0.187087:0.869759:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129894 ES:SE:LP:AF:ID  -0.000167938:0.00037105:0.187087:0.129894:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869098 ES:SE:LP:AF:ID  0.000160649:0.000369568:0.180456:0.869098:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869196 ES:SE:LP:AF:ID  0.000146696:0.000369715:0.161151:0.869196:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869102 ES:SE:LP:AF:ID  0.000169061:0.000369561:0.187087:0.869102:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.837996 ES:SE:LP:AF:ID  5.43306e-05:0.000344126:0.0604807:0.837996:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838627 ES:SE:LP:AF:ID  3.44197e-05:0.000345093:0.0362122:0.838627:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839743 ES:SE:LP:AF:ID  1.71189e-05:0.000349763:0.0177288:0.839743:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869384 ES:SE:LP:AF:ID  0.000163851:0.000369137:0.180456:0.869384:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868931 ES:SE:LP:AF:ID  0.000136059:0.000368208:0.148742:0.868931:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867881 ES:SE:LP:AF:ID  0.000135988:0.000367501:0.148742:0.867881:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869074 ES:SE:LP:AF:ID  0.000148621:0.000368509:0.161151:0.869074:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869082 ES:SE:LP:AF:ID  0.000149215:0.000368537:0.161151:0.869082:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.86909  ES:SE:LP:AF:ID  0.000147826:0.000368546:0.161151:0.86909:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869568 ES:SE:LP:AF:ID  0.000169458:0.000369558:0.187087:0.869568:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838278 ES:SE:LP:AF:ID  4.80254e-05:0.000343473:0.05061:0.838278:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838399 ES:SE:LP:AF:ID  6.37502e-05:0.000343716:0.0705811:0.838399:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862237 ES:SE:LP:AF:ID  0.000195978:0.000367213:0.229148:0.862237:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706734 ES:SE:LP:AF:ID  0.000273918:0.000357503:0.356547:0.706734:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105152 ES:SE:LP:AF:ID  -0.000292478:0.000411809:0.318759:0.105152:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761288 ES:SE:LP:AF:ID  -0.000256865:0.000291784:0.420216:0.761288:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106487 ES:SE:LP:AF:ID  0.000706155:0.000402189:1.10237:0.106487:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129596 ES:SE:LP:AF:ID  -0.000140107:0.000370833:0.148742:0.129596:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868893 ES:SE:LP:AF:ID  0.000164748:0.000368857:0.180456:0.868893:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129696 ES:SE:LP:AF:ID  -0.00015698:0.000370596:0.173925:0.129696:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868904 ES:SE:LP:AF:ID  0.000163162:0.000368865:0.180456:0.868904:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265373 ES:SE:LP:AF:ID  -0.000301143:0.000325924:0.443698:0.265373:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870026 ES:SE:LP:AF:ID  0.00014936:0.000369618:0.161151:0.870026:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095145 ES:SE:LP:AF:ID  0.000872197:0.000428404:1.37675:0.095145:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128594 ES:SE:LP:AF:ID  -0.000144704:0.000371075:0.154902:0.128594:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.12889  ES:SE:LP:AF:ID  -0.000156104:0.000370446:0.173925:0.12889:rs4040617