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-2425/UKB-b-2425_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2425/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/ 

Beginning analysis at Thu Oct 17 14:42:46 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-2425/UKB-b-2425_data.vcf.gz ...
Read summary statistics for 4232462 SNPs.
Dropped 865 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, 994959 SNPs remain.
After merging with regression SNP LD, 994959 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0021 (0.0014)
Lambda GC: 1.206
Mean Chi^2: 1.1998
Intercept: 1.1794 (0.0095)
Ratio: 0.8978 (0.0477)
Analysis finished at Thu Oct 17 14:43:41 2019
Total time elapsed: 54.67s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.8841,
    "inflation_factor": 1.1999,
    "mean_EFFECT": 1.4537e-06,
    "n": "-Inf",
    "n_snps": 9851866,
    "n_clumped_hits": 2,
    "n_p_sig": 2,
    "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": 34795,
    "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": 994959,
    "ldsc_nsnp_merge_regression_ld": 994959,
    "ldsc_observed_scale_h2_beta": 0.0021,
    "ldsc_observed_scale_h2_se": 0.0014,
    "ldsc_intercept_beta": 1.1794,
    "ldsc_intercept_se": 0.0095,
    "ldsc_lambda_gc": 1.206,
    "ldsc_mean_chisq": 1.1998,
    "ldsc_ratio": 0.8979
}

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 TRUE
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 1.000000 3 58 0 4231602 0 NA NA NA NA NA NA NA NA NA NA
character REF 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
character ALT 0 1.000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 4232462 0.000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.000000 NA NA NA NA NA NA NA 8.655209e+00 5.765387e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▃▂▂
numeric POS 0 1.000000 NA NA NA NA NA NA NA 7.859560e+07 5.673439e+07 828.0000000 3.167476e+07 6.897254e+07 1.146799e+08 2.492385e+08 ▇▆▅▂▁
numeric EFFECT 0 1.000000 NA NA NA NA NA NA NA 1.500000e-06 2.316000e-04 -0.0014516 -1.519000e-04 1.700000e-06 1.534000e-04 1.680900e-03 ▁▂▇▁▁
numeric SE 0 1.000000 NA NA NA NA NA NA NA 2.093000e-04 3.240000e-05 0.0001692 1.813000e-04 1.984000e-04 2.312000e-04 6.185000e-04 ▇▁▁▁▁
numeric PVAL 0 1.000000 NA NA NA NA NA NA NA 4.708635e-01 2.953827e-01 0.0000000 2.099999e-01 4.600002e-01 7.300002e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.000000 NA NA NA NA NA NA NA 4.708626e-01 2.953580e-01 0.0000000 2.086377e-01 4.582449e-01 7.260982e-01 9.999999e-01 ▇▇▆▆▆
numeric AF 0 1.000000 NA NA NA NA NA NA NA 3.842950e-01 2.197513e-01 0.1042910 1.932360e-01 3.321510e-01 5.450430e-01 8.957090e-01 ▇▅▃▂▂
numeric AF_reference 34795 0.991779 NA NA NA NA NA NA NA 3.744319e-01 2.216709e-01 0.0000000 1.918930e-01 3.302720e-01 5.331470e-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 -0.0004767 0.0003111 0.1299999 0.1254593 0.623761 0.782149 NA
1 54676 rs2462492 C T -0.0003883 0.0003083 0.2099999 0.2078046 0.400407 NA NA
1 91536 rs6702460 G T -0.0004772 0.0003035 0.1199999 0.1158867 0.456863 0.420727 NA
1 534192 rs6680723 C T -0.0002968 0.0003467 0.3900004 0.3919603 0.240956 NA NA
1 693731 rs12238997 A G -0.0000756 0.0002905 0.7899998 0.7946681 0.116333 0.141773 NA
1 706368 rs55727773 A G -0.0000178 0.0002152 0.9299999 0.9340268 0.515654 0.275160 NA
1 729679 rs4951859 C G -0.0000474 0.0002518 0.8499999 0.8508209 0.843210 0.639976 NA
1 731718 rs142557973 T C 0.0000296 0.0002756 0.9100000 0.9145051 0.122316 0.154353 NA
1 734349 rs141242758 T C 0.0000106 0.0002757 0.9699999 0.9694274 0.121560 0.152556 NA
1 736289 rs79010578 T A 0.0001433 0.0002717 0.5999997 0.5979326 0.132333 0.139577 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51198027 rs34939255 A G -0.0001297 0.0002148 0.5500004 0.5459242 0.254560 0.0984425 NA
22 51208537 rs72619593 G A 0.0005042 0.0002871 0.0790005 0.0789878 0.120741 0.1142170 NA
22 51210289 rs112565862 C T -0.0005494 0.0002859 0.0549997 0.0546379 0.129957 0.1018370 NA
22 51211106 rs9628250 T C -0.0000160 0.0002129 0.9400001 0.9399321 0.271540 0.1671330 NA
22 51211392 rs3888396 T C -0.0004995 0.0002833 0.0779992 0.0779378 0.132637 0.1641370 NA
22 51212875 rs2238837 A C 0.0002598 0.0002023 0.2000000 0.1990632 0.331477 0.3724040 NA
22 51213613 rs34726907 C T 0.0000683 0.0002665 0.8000000 0.7976538 0.127819 0.1727240 NA
22 51216564 rs9616970 T C 0.0000634 0.0002654 0.8100000 0.8110808 0.128334 0.1563500 NA
22 51219006 rs28729663 G A 0.0000231 0.0002598 0.9299999 0.9290309 0.137954 0.2052720 NA
22 51237063 rs3896457 T C 0.0002278 0.0002071 0.2700001 0.2714394 0.297981 0.2050720 NA

bcf preview

1   49298   rs10399793  T   C   .   PASS    AF=0.623761 ES:SE:LP:AF:ID  -0.000476743:0.000311138:0.886057:0.623761:rs10399793
1   54676   rs2462492   C   T   .   PASS    AF=0.400407 ES:SE:LP:AF:ID  -0.000388282:0.000308252:0.677781:0.400407:rs2462492
1   91536   rs6702460   G   T   .   PASS    AF=0.456863 ES:SE:LP:AF:ID  -0.000477206:0.000303513:0.920819:0.456863:rs6702460
1   534192  rs6680723   C   T   .   PASS    AF=0.240956 ES:SE:LP:AF:ID  -0.000296785:0.000346684:0.408935:0.240956:rs6680723
1   693731  rs12238997  A   G   .   PASS    AF=0.116333 ES:SE:LP:AF:ID  -7.56115e-05:0.00029053:0.102373:0.116333:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.515654 ES:SE:LP:AF:ID  -1.78149e-05:0.000215209:0.0315171:0.515654:rs12029736
1   729679  rs4951859   C   G   .   PASS    AF=0.84321  ES:SE:LP:AF:ID  -4.73531e-05:0.000251783:0.0705811:0.84321:rs4951859
1   731718  rs58276399  T   C   .   PASS    AF=0.122316 ES:SE:LP:AF:ID  2.95873e-05:0.000275595:0.0409586:0.122316:rs58276399
1   734349  rs141242758 T   C   .   PASS    AF=0.12156  ES:SE:LP:AF:ID  1.0567e-05:0.00027571:0.0132283:0.12156:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.132333 ES:SE:LP:AF:ID  0.000143307:0.000271736:0.221849:0.132333:rs79010578
1   752566  rs3094315   G   A   .   PASS    AF=0.83895  ES:SE:LP:AF:ID  -6.45711e-05:0.000243834:0.102373:0.83895:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.838579 ES:SE:LP:AF:ID  -6.35055e-05:0.000243571:0.102373:0.838579:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.869772 ES:SE:LP:AF:ID  -0.000102299:0.000261359:0.154902:0.869772:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129881 ES:SE:LP:AF:ID  7.52715e-05:0.000261893:0.113509:0.129881:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.869113 ES:SE:LP:AF:ID  -8.52192e-05:0.000260846:0.130768:0.869113:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.869212 ES:SE:LP:AF:ID  -8.38807e-05:0.00026095:0.124939:0.869212:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.869117 ES:SE:LP:AF:ID  -8.54559e-05:0.000260841:0.130768:0.869117:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.838031 ES:SE:LP:AF:ID  -6.36428e-05:0.000242895:0.102373:0.838031:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.838662 ES:SE:LP:AF:ID  -5.95816e-05:0.000243578:0.091515:0.838662:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.839774 ES:SE:LP:AF:ID  -6.96243e-05:0.000246871:0.107905:0.839774:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.869397 ES:SE:LP:AF:ID  -0.000106785:0.00026054:0.167491:0.869397:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.868943 ES:SE:LP:AF:ID  -0.000117557:0.000259884:0.187087:0.868943:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.867896 ES:SE:LP:AF:ID  -9.94258e-05:0.000259386:0.154902:0.867896:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869087 ES:SE:LP:AF:ID  -0.000115194:0.000260097:0.180456:0.869087:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.869095 ES:SE:LP:AF:ID  -0.000115535:0.000260117:0.180456:0.869095:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869103 ES:SE:LP:AF:ID  -0.000105812:0.000260123:0.167491:0.869103:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.869581 ES:SE:LP:AF:ID  -0.00011141:0.000260838:0.173925:0.869581:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.838311 ES:SE:LP:AF:ID  -6.91251e-05:0.000242435:0.107905:0.838311:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.838432 ES:SE:LP:AF:ID  -7.02757e-05:0.000242606:0.113509:0.838432:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.862253 ES:SE:LP:AF:ID  -0.000112037:0.000259181:0.173925:0.862253:rs2286139
1   763394  rs3115847   G   A   .   PASS    AF=0.706732 ES:SE:LP:AF:ID  -1.96851e-05:0.000252318:0.0268721:0.706732:rs3115847
1   766007  rs61768174  A   C   .   PASS    AF=0.10515  ES:SE:LP:AF:ID  0.000313833:0.000290652:0.552842:0.10515:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.761319 ES:SE:LP:AF:ID  -3.73602e-05:0.000205939:0.0655015:0.761319:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.106464 ES:SE:LP:AF:ID  -5.06789e-05:0.00028387:0.0655015:0.106464:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.129586 ES:SE:LP:AF:ID  6.76322e-05:0.000261737:0.09691:0.129586:rs60320384
1   771823  rs2977605   T   C   .   PASS    AF=0.868902 ES:SE:LP:AF:ID  -0.000120314:0.000260339:0.19382:0.868902:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129685 ES:SE:LP:AF:ID  8.46487e-05:0.000261569:0.124939:0.129685:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.868911 ES:SE:LP:AF:ID  -0.000121024:0.000260344:0.19382:0.868911:rs2905039
1   776546  rs12124819  A   G   .   PASS    AF=0.26539  ES:SE:LP:AF:ID  -0.000277716:0.000230032:0.638272:0.26539:rs12124819
1   777122  rs2980319   A   T   .   PASS    AF=0.870036 ES:SE:LP:AF:ID  -8.11547e-05:0.000260876:0.119186:0.870036:rs2980319
1   778745  rs1055606   A   G   .   PASS    AF=0.128584 ES:SE:LP:AF:ID  3.63089e-05:0.000261906:0.05061:0.128584:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.128881 ES:SE:LP:AF:ID  4.58454e-05:0.000261461:0.0655015:0.128881:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.868776 ES:SE:LP:AF:ID  -7.08082e-05:0.000260179:0.102373:0.868776:rs2977612
1   782981  rs6594026   C   T   .   PASS    AF=0.129522 ES:SE:LP:AF:ID  5.3253e-05:0.000261376:0.0757207:0.129522:rs6594026
1   785050  rs2905062   G   A   .   PASS    AF=0.86853  ES:SE:LP:AF:ID  -6.61153e-05:0.000260118:0.09691:0.86853:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.868471 ES:SE:LP:AF:ID  -6.31225e-05:0.00026028:0.091515:0.868471:rs2980300
1   787399  rs2905055   G   T   .   PASS    AF=0.860774 ES:SE:LP:AF:ID  -6.89556e-05:0.000260104:0.102373:0.860774:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.12847  ES:SE:LP:AF:ID  4.92709e-05:0.000262786:0.0705811:0.12847:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.861488 ES:SE:LP:AF:ID  -4.03581e-05:0.000260274:0.0555173:0.861488:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.869222 ES:SE:LP:AF:ID  -6.77409e-05:0.000261233:0.09691:0.869222:rs2905053