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-1164/ieu-a-1164.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-1164/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Wed Feb  5 08:37:44 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1164/ieu-a-1164.vcf.gz ...
Read summary statistics for 8567706 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, 1282206 SNPs remain.
After merging with regression SNP LD, 1282206 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0066 (0.0197)
Lambda GC: 1.0094
Mean Chi^2: 1.0082
Intercept: 1.0112 (0.0061)
Ratio: 1.3642 (0.7357)
Analysis finished at Wed Feb  5 08:39:10 2020
Total time elapsed: 1.0m:25.68s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9436,
    "inflation_factor": 1.0054,
    "mean_EFFECT": 0.0038,
    "n": 23059,
    "n_snps": 8567706,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 3344,
    "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": 238481,
    "n_est": 22591.6585,
    "ratio_se_n": 0.9898,
    "mean_diff": -0.0026,
    "ratio_diff": 6.9796,
    "sd_y_est1": 4.7166,
    "sd_y_est2": 4.6685,
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": 1282206,
    "ldsc_nsnp_merge_regression_ld": 1282206,
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": 1.0112,
    "ldsc_intercept_se": 0.0061,
    "ldsc_lambda_gc": 1.0094,
    "ldsc_mean_chisq": 1.0082,
    "ldsc_ratio": 1.3659
}

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 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 numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 59 0 8567704 0 NA NA NA NA NA NA NA NA
character REF 0 1.0000000 1 26 0 540 0 NA NA NA NA NA NA NA NA
character ALT 0 1.0000000 1 41 0 287 0 NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA 9.038487e+00 6.124341e+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 7.860786e+07 5.620913e+07 1.01330e+04 3.234505e+07 6.952492e+07 1.145982e+08 2.492225e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.805700e-03 1.126223e-01 -2.20059e+00 -4.608570e-02 2.412000e-03 5.236270e-02 1.282410e+00 ▁▁▁▇▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.415490e-02 6.186760e-02 4.72060e-03 4.851800e-02 6.681840e-02 1.225050e-01 9.529680e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.991522e-01 2.889162e-01 7.00000e-07 2.487729e-01 4.988374e-01 7.494782e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.991522e-01 2.889162e-01 7.00000e-07 2.487729e-01 4.988373e-01 7.494795e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA 2.507727e-01 2.615189e-01 1.00001e-02 3.845750e-02 1.437760e-01 3.963648e-01 9.899990e-01 ▇▂▂▁▁
numeric AF_reference 238481 0.9721651 NA NA NA NA NA 2.542595e-01 2.549923e-01 0.00000e+00 4.472840e-02 1.627400e-01 3.991610e-01 1.000000e+00 ▇▃▂▁▁
numeric N 0 1.0000000 NA NA NA NA NA 2.305900e+04 0.000000e+00 2.30590e+04 2.305900e+04 2.305900e+04 2.305900e+04 2.305900e+04 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 767811 rs140378911 G C -0.0050074 0.240564 0.9833930 0.9833930 0.0193137 NA 23059
1 810777 rs143204076 C G 0.1521840 0.299814 0.6117374 0.6117376 0.0146101 0.0053914 23059
1 823790 rs143626389 G A -0.2416070 0.236313 0.3065900 0.3065904 0.0252184 0.0101837 23059
1 834830 rs116452738 G A 0.0733326 0.267433 0.7839241 0.7839238 0.0134023 0.0069888 23059
1 837214 rs72631888 G C 0.0645895 0.325575 0.8427431 0.8427431 0.0123877 0.0029952 23059
1 839682 rs189624598 G A -0.1814260 0.218569 0.4065032 0.4065033 0.0286703 0.0039936 23059
1 848223 rs4246504 G A 0.3897700 0.208589 0.0616794 0.0616781 0.0201596 0.0081869 23059
1 851390 rs72631889 G T -0.0184545 0.209620 0.9298459 0.9298466 0.0282621 0.0115815 23059
1 870873 rs114397781 G A -0.2561750 0.300307 0.3936353 0.3936351 0.0102905 0.0043930 23059
1 871800 rs7520955 G A -0.3484730 0.276125 0.2069431 0.2069446 0.0162360 NA 23059
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154918624 rs5940558 A G 0.1642730 0.1165440 0.1586752 0.1586766 0.0537415 0.1290070 23059
23 154921127 rs58486544 T C 0.1540960 0.1153360 0.1815290 0.1815291 0.0540152 0.1451660 23059
23 154923311 rs141127553 C T 0.1825310 0.1219710 0.1345210 0.1345204 0.0512868 0.0309934 23059
23 154925045 rs509981 C T -0.0026435 0.0480436 0.9561200 0.9561204 0.2362900 0.3634440 23059
23 154925895 rs538470 C T 0.0013696 0.0501997 0.9782340 0.9782341 0.2357770 0.3634440 23059
23 154927185 rs185685661 T C -0.0880461 0.0808897 0.2763879 0.2763872 0.1362590 0.1796030 23059
23 154927199 rs645904 C T -0.0037660 0.0480495 0.9375279 0.9375276 0.2355950 0.3674170 23059
23 154927581 rs644138 G A 0.0219265 0.0466883 0.6386163 0.6386152 0.2888990 0.4635760 23059
23 154929412 rs557132 C T -0.0032828 0.0481321 0.9456229 0.9456231 0.2358630 0.3568210 23059
23 154930230 rs781880 A G -0.0008239 0.0483415 0.9864020 0.9864017 0.2350840 0.3618540 23059

bcf preview

1   767811  rs140378911 G   C   .   PASS    AF=0.0193137    ES:SE:LP:AF:SS:ID   -0.0050074:0.240564:0.00727289:0.0193137:23059:rs140378911
1   810777  rs143204076 C   G   .   PASS    AF=0.0146101    ES:SE:LP:AF:SS:ID   0.152184:0.299814:0.213435:0.0146101:23059:rs143204076
1   823790  rs143626389 G   A   .   PASS    AF=0.0252184    ES:SE:LP:AF:SS:ID   -0.241607:0.236313:0.513442:0.0252184:23059:rs143626389
1   834830  rs116452738 G   A   .   PASS    AF=0.0134023    ES:SE:LP:AF:SS:ID   0.0733326:0.267433:0.105726:0.0134023:23059:rs116452738
1   837214  rs72631888  G   C   .   PASS    AF=0.0123877    ES:SE:LP:AF:SS:ID   0.0645895:0.325575:0.0743048:0.0123877:23059:rs72631888
1   839682  rs189624598 G   A   .   PASS    AF=0.0286703    ES:SE:LP:AF:SS:ID   -0.181426:0.218569:0.390936:0.0286703:23059:rs189624598
1   848223  rs4246504   G   A   .   PASS    AF=0.0201596    ES:SE:LP:AF:SS:ID   0.38977:0.208589:1.20986:0.0201596:23059:rs4246504
1   851390  rs72631889  G   T   .   PASS    AF=0.0282621    ES:SE:LP:AF:SS:ID   -0.0184545:0.20962:0.031589:0.0282621:23059:rs72631889
1   870873  rs114397781 G   A   .   PASS    AF=0.0102905    ES:SE:LP:AF:SS:ID   -0.256175:0.300307:0.404906:0.0102905:23059:rs114397781
1   871800  rs7520955   G   A   .   PASS    AF=0.016236 ES:SE:LP:AF:SS:ID   -0.348473:0.276125:0.684149:0.016236:23059:rs7520955
1   879911  rs143853699 G   A   .   PASS    AF=0.0201563    ES:SE:LP:AF:SS:ID   0.21988:0.258395:0.403623:0.0201563:23059:rs143853699
1   881918  rs35471880  G   A   .   PASS    AF=0.0496391    ES:SE:LP:AF:SS:ID   0.0375169:0.15393:0.0928887:0.0496391:23059:rs35471880
1   885765  rs114631528 G   A   .   PASS    AF=0.0144017    ES:SE:LP:AF:SS:ID   0.204446:0.302262:0.302078:0.0144017:23059:rs114631528
1   886409  rs77573237  G   C   .   PASS    AF=0.0336437    ES:SE:LP:AF:SS:ID   -0.0979705:0.193394:0.212933:0.0336437:23059:rs77573237
1   892569  rs41285806  C   T   .   PASS    AF=0.0102779    ES:SE:LP:AF:SS:ID   -0.250005:0.298741:0.395051:0.0102779:23059:rs41285806
1   894519  rs115438739 G   A   .   PASS    AF=0.021799 ES:SE:LP:AF:SS:ID   -0.272557:0.230605:0.624818:0.021799:23059:rs115438739
1   903245  rs28690976  A   G   .   PASS    AF=0.529703 ES:SE:LP:AF:SS:ID   -0.00661992:0.0680061:0.0350553:0.529703:23059:rs28690976
1   909221  rs62639985  T   C   .   PASS    AF=0.0378943    ES:SE:LP:AF:SS:ID   0.233718:0.189304:0.663596:0.0378943:23059:rs62639985
1   913889  rs2340596   G   A   .   PASS    AF=0.569606 ES:SE:LP:AF:SS:ID   -0.0404506:0.060146:0.299955:0.569606:23059:rs2340596
1   914333  rs13302979  C   G   .   PASS    AF=0.583105 ES:SE:LP:AF:SS:ID   -0.0488368:0.0604995:0.377231:0.583105:23059:rs13302979
1   914852  rs13303368  G   C   .   PASS    AF=0.568175 ES:SE:LP:AF:SS:ID   -0.0433243:0.0600905:0.327054:0.568175:23059:rs13303368
1   914940  rs13303033  T   C   .   PASS    AF=0.553378 ES:SE:LP:AF:SS:ID   -0.0391804:0.0594916:0.292293:0.553378:23059:rs13303033
1   916549  rs6660139   A   G   .   PASS    AF=0.73417  ES:SE:LP:AF:SS:ID   0.0402818:0.0712295:0.242817:0.73417:23059:rs6660139
1   916834  rs6694632   G   A   .   PASS    AF=0.58139  ES:SE:LP:AF:SS:ID   -0.0257077:0.0597233:0.175958:0.58139:23059:rs6694632
1   917640  rs41285816  G   A   .   PASS    AF=0.22358  ES:SE:LP:AF:SS:ID   -0.049699:0.0766705:0.286639:0.22358:23059:rs41285816
1   918384  rs13303118  G   T   .   PASS    AF=0.55875  ES:SE:LP:AF:SS:ID   -0.0360623:0.0588446:0.267621:0.55875:23059:rs13303118
1   918573  rs2341354   A   G   .   PASS    AF=0.578113 ES:SE:LP:AF:SS:ID   -0.034856:0.0590135:0.255896:0.578113:23059:rs2341354
1   919501  rs4970414   G   T   .   PASS    AF=0.575173 ES:SE:LP:AF:SS:ID   0.0133198:0.0621206:0.0808063:0.575173:23059:rs4970414
1   920503  rs28896913  G   A   .   PASS    AF=0.147996 ES:SE:LP:AF:SS:ID   0.036736:0.0898427:0.165822:0.147996:23059:rs28896913
1   920640  rs28869591  C   T   .   PASS    AF=0.163062 ES:SE:LP:AF:SS:ID   0.0325343:0.0873643:0.148989:0.163062:23059:rs28869591
1   920977  rs55692389  T   C   .   PASS    AF=0.159429 ES:SE:LP:AF:SS:ID   0.0314479:0.0879349:0.142292:0.159429:23059:rs55692389
1   921660  rs6703008   C   T   .   PASS    AF=0.216578 ES:SE:LP:AF:SS:ID   -0.025833:0.0739523:0.138555:0.216578:23059:rs6703008
1   921716  rs13303278  C   A   .   PASS    AF=0.513045 ES:SE:LP:AF:SS:ID   0.0573392:0.0581631:0.489168:0.513045:23059:rs13303278
1   922009  rs6693747   G   A   .   PASS    AF=0.213853 ES:SE:LP:AF:SS:ID   -0.0344636:0.0744127:0.191611:0.213853:23059:rs6693747
1   922011  rs185011518 G   A   .   PASS    AF=0.0103216    ES:SE:LP:AF:SS:ID   0.338966:0.31863:0.541498:0.0103216:23059:rs185011518
1   922483  rs114583033 T   C   .   PASS    AF=0.159608 ES:SE:LP:AF:SS:ID   0.0290309:0.087843:0.130162:0.159608:23059:rs114583033
1   923457  rs147869918 C   T   .   PASS    AF=0.0100995    ES:SE:LP:AF:SS:ID   0.350069:0.29577:0.626024:0.0100995:23059:rs147869918
1   924111  rs28447224  T   A   .   PASS    AF=0.235395 ES:SE:LP:AF:SS:ID   -0.0670554:0.0727851:0.447449:0.235395:23059:rs28447224
1   924528  rs34712273  C   A   .   PASS    AF=0.55348  ES:SE:LP:AF:SS:ID   0.0590141:0.0561546:0.532695:0.55348:23059:rs34712273
1   926968  rs140144962 C   T   .   PASS    AF=0.15759  ES:SE:LP:AF:SS:ID   0.0308473:0.0884965:0.13822:0.15759:23059:rs140144962
1   927741  rs6665587   G   A   .   PASS    AF=0.22044  ES:SE:LP:AF:SS:ID   -0.0461899:0.0736443:0.275293:0.22044:23059:rs6665587
1   928416  rs111754459 G   A   .   PASS    AF=0.23235  ES:SE:LP:AF:SS:ID   -0.0572009:0.0725433:0.366128:0.23235:23059:rs111754459
1   929550  rs138560419 A   C   .   PASS    AF=0.0116605    ES:SE:LP:AF:SS:ID   -0.0566095:0.268881:0.0792257:0.0116605:23059:rs138560419
1   930329  rs3128108   C   T   .   PASS    AF=0.230466 ES:SE:LP:AF:SS:ID   -0.0588287:0.0728167:0.377634:0.230466:23059:rs3128108
1   930377  rs3128109   C   T   .   PASS    AF=0.230466 ES:SE:LP:AF:SS:ID   -0.058834:0.0728159:0.377682:0.230466:23059:rs3128109
1   930533  rs3128110   C   G   .   PASS    AF=0.393408 ES:SE:LP:AF:SS:ID   -0.0380414:0.0595382:0.281614:0.393408:23059:rs3128110
1   930567  rs3121574   A   G   .   PASS    AF=0.393633 ES:SE:LP:AF:SS:ID   -0.0383675:0.059512:0.284732:0.393633:23059:rs3121574
1   930751  rs3128111   C   G   .   PASS    AF=0.380087 ES:SE:LP:AF:SS:ID   -0.0154625:0.0598098:0.0990869:0.380087:23059:rs3128111
1   930923  rs2710882   A   G   .   PASS    AF=0.796305 ES:SE:LP:AF:SS:ID   0.00902553:0.0794232:0.0411858:0.796305:23059:rs2710882
1   931166  rs2710880   A   G   .   PASS    AF=0.390581 ES:SE:LP:AF:SS:ID   -0.0263494:0.0598081:0.180767:0.390581:23059:rs2710880