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-13183/UKB-b-13183_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13183/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:19 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-13183/UKB-b-13183_data.vcf.gz ...
Read summary statistics for 5352799 SNPs.
Dropped 1831 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, 1157905 SNPs remain.
After merging with regression SNP LD, 1157905 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0061 (0.001)
Lambda GC: 1.0852
Mean Chi^2: 1.0907
Intercept: 1.0337 (0.0068)
Ratio: 0.3716 (0.0754)
Analysis finished at Thu Oct 17 14:43:24 2019
Total time elapsed: 1.0m:5.45s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9138,
    "inflation_factor": 1.0966,
    "mean_EFFECT": 9.2952e-07,
    "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": 46536,
    "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": 1157905,
    "ldsc_nsnp_merge_regression_ld": 1157905,
    "ldsc_observed_scale_h2_beta": 0.0061,
    "ldsc_observed_scale_h2_se": 0.001,
    "ldsc_intercept_beta": 1.0337,
    "ldsc_intercept_se": 0.0068,
    "ldsc_lambda_gc": 1.0852,
    "ldsc_mean_chisq": 1.0907,
    "ldsc_ratio": 0.3716
}

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 5350982 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 5352799 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 8.673342e+00 5.762879e+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 7.853406e+07 5.656332e+07 828.0000000 3.192650e+07 6.895560e+07 1.144757e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 9.000000e-07 3.586000e-04 -0.0027797 -2.244000e-04 -4.000000e-07 2.240000e-04 2.756900e-03 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.343000e-04 8.690000e-05 0.0002394 2.613000e-04 3.022000e-04 3.878000e-04 1.132200e-03 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.869132e-01 2.916759e-01 0.0000001 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 4.869138e-01 2.916507e-01 0.0000001 2.315531e-01 4.823244e-01 7.389681e-01 9.999996e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 3.372352e-01 2.447473e-01 0.0525450 1.275185e-01 2.658590e-01 5.040160e-01 9.474550e-01 ▇▃▂▂▂
numeric AF_reference 46536 0.9913062 NA NA NA NA NA NA NA 3.318816e-01 2.398603e-01 0.0000000 1.341850e-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 -0.0009844 0.0004406 0.0250000 0.0254748 0.623763 0.7821490 NA
1 54676 rs2462492 C T 0.0000192 0.0004365 0.9599999 0.9648900 0.400429 NA NA
1 86028 rs114608975 T C 0.0005219 0.0006980 0.4500005 0.4546843 0.103544 0.0277556 NA
1 91536 rs6702460 G T -0.0010563 0.0004298 0.0140001 0.0139874 0.456864 0.4207270 NA
1 234313 rs8179466 C T -0.0005331 0.0008477 0.5300002 0.5294616 0.074493 NA NA
1 534192 rs6680723 C T -0.0000370 0.0004910 0.9400001 0.9399240 0.240983 NA NA
1 546697 rs12025928 A G 0.0008040 0.0006124 0.1900002 0.1892025 0.913457 NA NA
1 693731 rs12238997 A G 0.0005619 0.0004114 0.1700000 0.1720081 0.116329 0.1417730 NA
1 705882 rs72631875 G A -0.0006311 0.0006029 0.2999998 0.2951936 0.067286 0.0315495 NA
1 706368 rs55727773 A G -0.0002954 0.0003048 0.3300000 0.3324191 0.515666 0.2751600 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51217954 rs9616974 G A 0.0002045 0.0004767 0.6700003 0.6679599 0.073312 0.0621006 NA
22 51218224 rs9616975 C A 0.0001997 0.0004769 0.6800001 0.6754458 0.073335 0.0619010 NA
22 51218377 rs2519461 G C 0.0002505 0.0004763 0.5999997 0.5989548 0.073623 0.0826677 NA
22 51219006 rs28729663 G A 0.0004604 0.0003676 0.2099999 0.2104574 0.137955 0.2052720 NA
22 51219387 rs9616832 T C 0.0001460 0.0004772 0.7600007 0.7596225 0.073746 0.0654952 NA
22 51221731 rs115055839 T C 0.0001665 0.0004776 0.7300002 0.7273879 0.073236 0.0625000 NA
22 51222100 rs114553188 G T 0.0003348 0.0005622 0.5500004 0.5514460 0.054465 0.0880591 NA
22 51223637 rs375798137 G A 0.0003059 0.0005649 0.5900000 0.5881832 0.054095 0.0788738 NA
22 51229805 rs9616985 T C 0.0001641 0.0004793 0.7300002 0.7320056 0.073073 0.0730831 NA
22 51237063 rs3896457 T C -0.0003431 0.0002931 0.2399999 0.2418451 0.297958 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623763 ES:SE:LP:AF:ID  -0.000984414:0.000440626:1.60206:0.623763:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400429 ES:SE:LP:AF:ID  1.92136e-05:0.000436493:0.0177288:0.400429:rs2462492
1   86028   rs114608975 T   C   .   PASS    AF=0.103544 ES:SE:LP:AF:ID  0.000521882:0.00069805:0.346787:0.103544:rs114608975
1   91536   rs6702460   G   T   .   PASS    AF=0.456864 ES:SE:LP:AF:ID  -0.00105632:0.00042982:1.85387:0.456864:rs6702460
1   234313  rs8179466   C   T   .   PASS    AF=0.074493 ES:SE:LP:AF:ID  -0.000533062:0.000847707:0.275724:0.074493:rs8179466
1   534192  rs6680723   C   T   .   PASS    AF=0.240983 ES:SE:LP:AF:ID  -3.70011e-05:0.000490956:0.0268721:0.240983:rs6680723
1   546697  rs12025928  A   G   .   PASS    AF=0.913457 ES:SE:LP:AF:ID  0.000803997:0.000612363:0.721246:0.913457:rs12025928
1   693731  rs12238997  A   G   .   PASS    AF=0.116329 ES:SE:LP:AF:ID  0.00056192:0.000411428:0.769551:0.116329:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.067286 ES:SE:LP:AF:ID  -0.000631081:0.000602869:0.522879:0.067286:rs72631875
1   706368  rs12029736  A   G   .   PASS    AF=0.515666 ES:SE:LP:AF:ID  -0.000295405:0.000304776:0.481486:0.515666:rs12029736
1   722670  rs116030099 T   C   .   PASS    AF=0.101219 ES:SE:LP:AF:ID  -0.000293948:0.000502754:0.251812:0.101219:rs116030099
1   725060  rs865924913 A   T   .   PASS    AF=0.053258 ES:SE:LP:AF:ID  -0.000143011:0.000961264:0.0555173:0.053258:rs865924913
1   729679  rs4951859   C   G   .   PASS    AF=0.843242 ES:SE:LP:AF:ID  -0.000489157:0.000356591:0.769551:0.843242:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.055934 ES:SE:LP:AF:ID  0.000472728:0.000577213:0.387216:0.055934:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.122304 ES:SE:LP:AF:ID  0.000504246:0.00039029:0.69897:0.122304:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.121547 ES:SE:LP:AF:ID  0.000491276:0.000390456:0.677781:0.121547:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132324 ES:SE:LP:AF:ID  0.000536706:0.000384828:0.79588:0.132324:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.838976 ES:SE:LP:AF:ID  -0.000374272:0.000345334:0.552842:0.838976:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838607 ES:SE:LP:AF:ID  -0.000369285:0.000344963:0.552842:0.838607:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869792 ES:SE:LP:AF:ID  -0.000453275:0.000370161:0.657577:0.869792:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129856 ES:SE:LP:AF:ID  0.000448402:0.000370917:0.638272:0.129856:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869137 ES:SE:LP:AF:ID  -0.000455897:0.000369438:0.657577:0.869137:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869235 ES:SE:LP:AF:ID  -0.000449679:0.000369585:0.657577:0.869235:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869139 ES:SE:LP:AF:ID  -0.00044492:0.00036943:0.638272:0.869139:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838059 ES:SE:LP:AF:ID  -0.000345592:0.000344004:0.49485:0.838059:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.83869  ES:SE:LP:AF:ID  -0.000357686:0.000344971:0.522879:0.83869:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839797 ES:SE:LP:AF:ID  -0.000340352:0.000349633:0.481486:0.839797:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869416 ES:SE:LP:AF:ID  -0.000460126:0.000369003:0.677781:0.869416:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868963 ES:SE:LP:AF:ID  -0.000429305:0.000368075:0.619789:0.868963:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867921 ES:SE:LP:AF:ID  -0.000442545:0.000367375:0.638272:0.867921:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869107 ES:SE:LP:AF:ID  -0.00044138:0.000368377:0.638272:0.869107:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869115 ES:SE:LP:AF:ID  -0.000440567:0.000368405:0.638272:0.869115:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869123 ES:SE:LP:AF:ID  -0.000440627:0.000368414:0.638272:0.869123:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.8696   ES:SE:LP:AF:ID  -0.000474223:0.000369425:0.69897:0.8696:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838336 ES:SE:LP:AF:ID  -0.000331548:0.000343351:0.481486:0.838336:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838457 ES:SE:LP:AF:ID  -0.000334137:0.000343594:0.481486:0.838457:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862284 ES:SE:LP:AF:ID  -0.000431749:0.000367088:0.619789:0.862284:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.70677  ES:SE:LP:AF:ID  -0.000232642:0.000357353:0.283997:0.70677:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.105151 ES:SE:LP:AF:ID  0.000582581:0.000411622:0.79588:0.105151:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761357 ES:SE:LP:AF:ID  -0.000738698:0.000291677:1.95861:0.761357:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106453 ES:SE:LP:AF:ID  0.000832251:0.000402038:1.42022:0.106453:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129565 ES:SE:LP:AF:ID  0.000392335:0.000370695:0.537602:0.129565:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868925 ES:SE:LP:AF:ID  -0.000463309:0.000368719:0.677781:0.868925:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129664 ES:SE:LP:AF:ID  0.000446717:0.000370457:0.638272:0.129664:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868935 ES:SE:LP:AF:ID  -0.000476086:0.000368726:0.69897:0.868935:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.265415 ES:SE:LP:AF:ID  -0.000404989:0.000325772:0.677781:0.265415:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870057 ES:SE:LP:AF:ID  -0.000535399:0.000369474:0.823909:0.870057:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.095127 ES:SE:LP:AF:ID  0.000977337:0.000428224:1.65758:0.095127:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.128564 ES:SE:LP:AF:ID  0.000490222:0.000370931:0.721246:0.128564:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128862 ES:SE:LP:AF:ID  0.000501658:0.000370302:0.744727:0.128862:rs4040617