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/dev/ieu-a-import/processed/ieu-a-798/ieu-a-798.vcf.gz \
--ref-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-798/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Tue Feb  4 18:53:05 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-798/ieu-a-798.vcf.gz ...
Read summary statistics for 8328109 SNPs.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1285887 SNPs remain.
After merging with regression SNP LD, 1285887 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0557 (0.0043)
Lambda GC: 1.0235
Mean Chi^2: 1.0881
Intercept: 0.9006 (0.0074)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Feb  4 18:54:29 2020
Total time elapsed: 1.0m:24.0s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9619,
    "inflation_factor": 0.9976,
    "mean_EFFECT": 0.0005,
    "n": 171875,
    "n_snps": 8328109,
    "n_clumped_hits": 26,
    "n_p_sig": 1027,
    "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": 196161,
    "n_est": 163153.9941,
    "ratio_se_n": 0.9743,
    "mean_diff": -0.0004,
    "ratio_diff": 67.2421,
    "sd_y_est1": 3.1964,
    "sd_y_est2": 3.1143,
    "r2_sum1": 0.0891,
    "r2_sum2": 0.0087,
    "r2_sum3": 0.0092,
    "r2_sum4": 0.0091,
    "ldsc_nsnp_merge_refpanel_ld": 1285887,
    "ldsc_nsnp_merge_regression_ld": 1285887,
    "ldsc_observed_scale_h2_beta": 0.0557,
    "ldsc_observed_scale_h2_se": 0.0043,
    "ldsc_intercept_beta": 0.9006,
    "ldsc_intercept_se": 0.0074,
    "ldsc_lambda_gc": 1.0235,
    "ldsc_mean_chisq": 1.0881,
    "ldsc_ratio": -1.1283
}

Flags

name value
af_correlation FALSE
inflation_factor FALSE
n FALSE
is_snpid_non_unique FALSE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq FALSE
n_p_sig TRUE
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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 59 0 8328107 0 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
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 8.675818e+00 5.747532e+00 1.00000e+00 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.862617e+07 5.616331e+07 8.28000e+02 3.248398e+07 6.929150e+07 1.142321e+08 2.492223e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.237000e-04 2.713120e-02 -3.54653e-01 -1.156840e-02 3.267000e-04 1.228950e-02 5.298520e-01 ▁▇▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 2.290860e-02 1.575530e-02 1.00481e-02 1.169840e-02 1.600640e-02 2.848050e-02 1.929760e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.992052e-01 2.901914e-01 0.00000e+00 2.478655e-01 5.005057e-01 7.507892e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.992052e-01 2.901914e-01 0.00000e+00 2.478656e-01 5.005051e-01 7.507895e-01 9.999999e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.402643e-01 2.430356e-01 6.13790e-03 4.119970e-02 1.433750e-01 3.821700e-01 9.914010e-01 ▇▂▂▁▁
numeric AF_reference 196161 0.9764459 NA NA NA NA NA 2.534460e-01 2.545229e-01 0.00000e+00 4.512780e-02 1.611420e-01 3.973640e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 1.718750e+05 0.000000e+00 1.71875e+05 1.718750e+05 1.718750e+05 1.718750e+05 1.718750e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 752566 rs3094315 G A 0.0035691 0.0169975 0.8336856 0.8336854 0.737335 0.718251 171875
1 752721 rs3131972 A G 0.0052243 0.0167411 0.7549931 0.7549925 0.719646 0.653355 171875
1 752894 rs3131971 T C 0.0146587 0.0173851 0.3991297 0.3991300 0.721558 0.753195 171875
1 753474 rs2073814 C G 0.0098651 0.0169405 0.5603392 0.5603381 0.697507 0.611422 171875
1 753541 rs2073813 G A -0.0046864 0.0181366 0.7961020 0.7961019 0.182621 0.301917 171875
1 754182 rs3131969 A G -0.0013511 0.0179176 0.9398897 0.9398897 0.737245 0.678514 171875
1 754192 rs3131968 A G -0.0008736 0.0179248 0.9611286 0.9611287 0.736783 0.678514 171875
1 754334 rs3131967 T C -0.0067541 0.0181215 0.7093621 0.7093616 0.723818 0.684305 171875
1 754503 rs3115859 G A 0.0055649 0.0169780 0.7430842 0.7430837 0.720544 0.663938 171875
1 754964 rs3131966 C T 0.0086355 0.0173293 0.6182612 0.6182608 0.704225 0.663339 171875
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51199281 rs4040021 T C -0.0450413 0.0157925 0.0043437 0.0043436 0.3741220 0.4612620 171875
22 51208568 rs148425445 G T -0.0570085 0.0307635 0.0638646 0.0638650 0.0556741 0.1160140 171875
22 51210268 rs2341018 T G -0.0029953 0.0163947 0.8550327 0.8550330 0.4366380 0.4468850 171875
22 51211031 rs9616968 A G 0.1014080 0.0348938 0.0036586 0.0036586 0.0496070 0.0373403 171875
22 51213613 rs34726907 C T 0.0055617 0.0210100 0.7912286 0.7912287 0.1248190 0.1727240 171875
22 51216731 rs5771014 T C -0.0266800 0.0438771 0.5431478 0.5431463 0.2344990 0.2593850 171875
22 51217954 rs9616974 G A 0.0787826 0.0346872 0.0231329 0.0231331 0.0534883 0.0621006 171875
22 51218224 rs9616975 C A 0.0789983 0.0346925 0.0227803 0.0227802 0.0534639 0.0619010 171875
22 51219006 rs28729663 G A 0.0138824 0.0200041 0.4876969 0.4876962 0.1641880 0.2052720 171875
23 100784211 rs188350543 C A 0.0173642 0.0151730 0.2524527 0.2524518 0.7554700 0.6498010 171875

bcf preview

1   752566  rs3094315   G   A   .   PASS    AF=0.737335 ES:SE:LP:AF:SS:ID   0.00356909:0.0169975:0.0789977:0.737335:171875:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.719646 ES:SE:LP:AF:SS:ID   0.00522428:0.0167411:0.122057:0.719646:171875:rs3131972
1   752894  rs3131971   T   C   .   PASS    AF=0.721558 ES:SE:LP:AF:SS:ID   0.0146587:0.0173851:0.398886:0.721558:171875:rs3131971
1   753474  rs2073814   C   G   .   PASS    AF=0.697507 ES:SE:LP:AF:SS:ID   0.00986512:0.0169405:0.251549:0.697507:171875:rs2073814
1   753541  rs2073813   G   A   .   PASS    AF=0.182621 ES:SE:LP:AF:SS:ID   -0.00468641:0.0181366:0.0990313:0.182621:171875:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.737245 ES:SE:LP:AF:SS:ID   -0.00135114:0.0179176:0.0269231:0.737245:171875:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.736783 ES:SE:LP:AF:SS:ID   -0.000873605:0.0179248:0.0172185:0.736783:171875:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.723818 ES:SE:LP:AF:SS:ID   -0.00675413:0.0181215:0.149132:0.723818:171875:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.720544 ES:SE:LP:AF:SS:ID   0.00556492:0.016978:0.128962:0.720544:171875:rs3115859
1   754964  rs3131966   C   T   .   PASS    AF=0.704225 ES:SE:LP:AF:SS:ID   0.00863548:0.0173293:0.208828:0.704225:171875:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.694935 ES:SE:LP:AF:SS:ID   0.0139023:0.0174783:0.370205:0.694935:171875:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.753327 ES:SE:LP:AF:SS:ID   -0.00255459:0.0182108:0.051372:0.753327:171875:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.734494 ES:SE:LP:AF:SS:ID   0.00483204:0.0180032:0.103257:0.734494:171875:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.726492 ES:SE:LP:AF:SS:ID   -0.00341857:0.0181846:0.0701305:0.726492:171875:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.759458 ES:SE:LP:AF:SS:ID   -0.00650752:0.018211:0.142163:0.759458:171875:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.758914 ES:SE:LP:AF:SS:ID   -0.00726146:0.0182175:0.161032:0.758914:171875:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.74543  ES:SE:LP:AF:SS:ID   -0.000876101:0.017502:0.0176938:0.74543:171875:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.758047 ES:SE:LP:AF:SS:ID   -0.00401645:0.0183242:0.0827553:0.758047:171875:rs3131954
1   760912  rs1048488   C   T   .   PASS    AF=0.714422 ES:SE:LP:AF:SS:ID   0.00946897:0.0175149:0.230057:0.714422:171875:rs1048488
1   761147  rs3115850   T   C   .   PASS    AF=0.718099 ES:SE:LP:AF:SS:ID   0.00698109:0.0175724:0.160418:0.718099:171875:rs3115850
1   761732  rs2286139   C   T   .   PASS    AF=0.69795  ES:SE:LP:AF:SS:ID   0.00723688:0.0184294:0.158293:0.69795:171875:rs2286139
1   761752  rs1057213   C   T   .   PASS    AF=0.74784  ES:SE:LP:AF:SS:ID   -0.000574972:0.0186678:0.0108045:0.74784:171875:rs1057213
1   762273  rs3115849   G   A   .   PASS    AF=0.726082 ES:SE:LP:AF:SS:ID   -0.00113524:0.0189301:0.0212812:0.726082:171875:rs3115849
1   764191  rs7515915   T   G   .   PASS    AF=0.146556 ES:SE:LP:AF:SS:ID   -0.0106609:0.0197605:0.22949:0.146556:171875:rs7515915
1   766007  rs61768174  A   C   .   PASS    AF=0.106156 ES:SE:LP:AF:SS:ID   -0.0163152:0.0223932:0.331372:0.106156:171875:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.637052 ES:SE:LP:AF:SS:ID   -0.00103533:0.0159814:0.0230331:0.637052:171875:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.121163 ES:SE:LP:AF:SS:ID   -0.00960306:0.0194931:0.206022:0.121163:171875:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.139286 ES:SE:LP:AF:SS:ID   -0.010402:0.0200822:0.218619:0.139286:171875:rs60320384
1   769963  rs7518545   G   A   .   PASS    AF=0.113179 ES:SE:LP:AF:SS:ID   -0.00680962:0.0207955:0.128822:0.113179:171875:rs7518545
1   771823  rs2977605   T   C   .   PASS    AF=0.757334 ES:SE:LP:AF:SS:ID   -0.000486243:0.019066:0.0089276:0.757334:171875:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.140378 ES:SE:LP:AF:SS:ID   -0.00699387:0.0196803:0.141276:0.140378:171875:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.755364 ES:SE:LP:AF:SS:ID   -0.00371011:0.0188678:0.0736001:0.755364:171875:rs2905039
1   775181  rs61768182  A   G   .   PASS    AF=0.148089 ES:SE:LP:AF:SS:ID   -0.00796122:0.0187968:0.172695:0.148089:171875:rs61768182
1   777122  rs2980319   A   T   .   PASS    AF=0.757678 ES:SE:LP:AF:SS:ID   0.00145264:0.0185792:0.0279453:0.757678:171875:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.0593552    ES:SE:LP:AF:SS:ID   0.00700971:0.0323782:0.0816539:0.0593552:171875:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.140488 ES:SE:LP:AF:SS:ID   -0.011032:0.0191539:0.248231:0.140488:171875:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.145742 ES:SE:LP:AF:SS:ID   -0.0107488:0.0188321:0.245532:0.145742:171875:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.739373 ES:SE:LP:AF:SS:ID   0.00460703:0.0179827:0.0981045:0.739373:171875:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.0891142    ES:SE:LP:AF:SS:ID   -0.026082:0.0241017:0.554117:0.0891142:171875:rs61768199
1   782981  rs6594026   C   T   .   PASS    AF=0.181202 ES:SE:LP:AF:SS:ID   -0.0157235:0.0181992:0.41161:0.181202:171875:rs6594026
1   783318  rs6686696   A   G   .   PASS    AF=0.131641 ES:SE:LP:AF:SS:ID   -0.0163356:0.0199122:0.385103:0.131641:171875:rs6686696
1   785050  rs2905062   G   A   .   PASS    AF=0.734027 ES:SE:LP:AF:SS:ID   0.00416882:0.0176868:0.0895551:0.734027:171875:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.721883 ES:SE:LP:AF:SS:ID   0.00053736:0.0175573:0.0107356:0.721883:171875:rs2980300
1   786995  rs61768202  G   A   .   PASS    AF=0.144764 ES:SE:LP:AF:SS:ID   -0.0106469:0.0193709:0.234652:0.144764:171875:rs61768202
1   787121  rs12077234  T   A   .   PASS    AF=0.14758  ES:SE:LP:AF:SS:ID   -0.0203125:0.0201237:0.504744:0.14758:171875:rs12077234
1   787151  rs2519065   G   A   .   PASS    AF=0.156929 ES:SE:LP:AF:SS:ID   -0.00913152:0.0202939:0.185262:0.156929:171875:rs2519065
1   787399  rs2905055   G   T   .   PASS    AF=0.723059 ES:SE:LP:AF:SS:ID   0.00500787:0.0184402:0.104605:0.723059:171875:rs2905055
1   787606  rs3863622   G   T   .   PASS    AF=0.143823 ES:SE:LP:AF:SS:ID   -0.017643:0.0197665:0.429354:0.143823:171875:rs3863622
1   787685  rs2905054   G   T   .   PASS    AF=0.713448 ES:SE:LP:AF:SS:ID   0.00309417:0.0181995:0.0629841:0.713448:171875:rs2905054
1   787844  rs2905053   C   T   .   PASS    AF=0.739368 ES:SE:LP:AF:SS:ID   0.00508425:0.0185343:0.105771:0.739368:171875:rs2905053