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-58/ieu-a-58.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-58/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 11:58:29 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-58/ieu-a-58.vcf.gz ...
Read summary statistics for 2188762 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, 1046135 SNPs remain.
After merging with regression SNP LD, 1046135 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.19 (0.0141)
Lambda GC: 1.0441
Mean Chi^2: 1.1038
Intercept: 0.8783 (0.0086)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Feb  4 11:58:56 2020
Total time elapsed: 27.11s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9072,
    "inflation_factor": 1.0475,
    "mean_EFFECT": -0.0001,
    "n": 99563,
    "n_snps": 2188762,
    "n_clumped_hits": 32,
    "n_p_sig": 516,
    "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": 8003,
    "n_miss_AF_reference": 17137,
    "n_est": 97481.129,
    "ratio_se_n": 0.9895,
    "mean_diff": 0,
    "ratio_diff": 4.1824,
    "sd_y_est1": 1.5098,
    "sd_y_est2": 1.4939,
    "r2_sum1": 0.0201,
    "r2_sum2": 0.0088,
    "r2_sum3": 0.009,
    "r2_sum4": 0.0159,
    "ldsc_nsnp_merge_refpanel_ld": 1046135,
    "ldsc_nsnp_merge_regression_ld": 1046135,
    "ldsc_observed_scale_h2_beta": 0.19,
    "ldsc_observed_scale_h2_se": 0.0141,
    "ldsc_intercept_beta": 0.8783,
    "ldsc_intercept_se": 0.0086,
    "ldsc_lambda_gc": 1.0441,
    "ldsc_mean_chisq": 1.1038,
    "ldsc_ratio": -1.1724
}

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 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 42 0 2188762 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 8.520765e+00 5.614971e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.899917e+07 5.540126e+07 1.3034e+04 3.306450e+07 7.051374e+07 1.142605e+08 2.491747e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA -1.326000e-04 1.016390e-02 -1.2000e-01 -6.000000e-03 -1.000000e-04 5.900000e-03 1.100000e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 9.329800e-03 3.558400e-03 4.9000e-03 7.000000e-03 8.000000e-03 1.000000e-02 4.900000e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.925313e-01 2.923253e-01 0.0000e+00 2.399999e-01 4.899999e-01 7.499995e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.925898e-01 2.921204e-01 0.0000e+00 2.372779e-01 4.908932e-01 7.462943e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 8003 0.9963436 NA NA NA NA NA 3.725429e-01 2.643901e-01 8.3000e-03 1.417000e-01 3.167000e-01 5.667000e-01 9.917000e-01 ▇▆▃▃▂
numeric AF_reference 17137 0.9921705 NA NA NA NA NA 3.737650e-01 2.477275e-01 1.9970e-04 1.653350e-01 3.182910e-01 5.549120e-01 1.000000e+00 ▇▇▅▃▂
numeric N 0 1.0000000 NA NA NA NA NA 5.757664e+04 8.149754e+03 5.0000e+04 5.644500e+04 5.694400e+04 5.701600e+04 9.956300e+04 ▇▁▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 785050 rs2905062 G A -0.0110 0.0095 0.2399999 0.2469070 NA 0.626997 59657
1 1003629 rs4075116 C T -0.0066 0.0085 0.4400003 0.4374712 0.7373 0.720647 54114
1 1017170 rs3766193 C G -0.0045 0.0078 0.5700002 0.5639914 0.5667 0.575479 54665
1 1017197 rs3766192 C T -0.0042 0.0074 0.5700002 0.5703286 0.5763 0.511182 54930
1 1018562 rs9442371 C T -0.0053 0.0073 0.4700002 0.4678220 0.5917 0.530152 54974
1 1018704 rs9442372 A G -0.0040 0.0074 0.5900000 0.5888243 0.6017 0.611022 54980
1 1021415 rs3737728 A G 0.0016 0.0081 0.8400000 0.8434121 0.7167 0.812700 55256
1 1021695 rs9442398 A G -0.0007 0.0083 0.9299999 0.9327882 0.7250 0.727236 55131
1 1022037 rs6701114 C T -0.0067 0.0082 0.4100001 0.4138866 0.5667 0.586661 50047
1 1089262 rs4970358 A G -0.0080 0.0180 0.6600001 0.6567213 0.9661 0.991014 50163
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51151350 rs6009951 C T -0.0092 0.0073 0.2099999 0.2075705 0.4000 0.5559110 55967
22 51151724 rs6010061 C T -0.0078 0.0075 0.2999998 0.2983399 0.3833 0.6098240 55804
22 51158017 rs6010065 G C -0.0027 0.0071 0.6999999 0.7037363 0.4417 0.5475240 55550
22 51163138 rs715586 C T 0.0007 0.0077 0.9299999 0.9275648 0.1500 0.0902556 90793
22 51165664 rs8137951 G A 0.0007 0.0055 0.9000000 0.8987245 0.2750 0.4063500 96896
22 51178090 rs2285395 G A 0.0110 0.0110 0.3300000 0.3173105 0.0667 0.0666933 93007
23 35921591 rs2204667 C G -0.0032 0.0092 0.7300002 0.7279708 0.1667 NA 56966
23 51666786 rs14115 A G 0.0039 0.0150 0.8000000 0.7948638 0.0250 NA 51606
23 70163799 rs1626496 A C -0.0140 0.0130 0.2999998 0.2815146 0.0750 NA 56974
23 118495837 rs12882977 G A -0.0058 0.0066 0.3800004 0.3795163 0.5167 0.2307280 56902

bcf preview

1   785050  rs2905062   G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.011:0.0095:0.619789:59657:rs2905062
1   1003629 rs4075116   C   T   .   PASS    AF=0.7373   ES:SE:LP:AF:SS:ID   -0.0066:0.0085:0.356547:0.7373:54114:rs4075116
1   1017170 rs3766193   C   G   .   PASS    AF=0.5667   ES:SE:LP:AF:SS:ID   -0.0045:0.0078:0.244125:0.5667:54665:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5763   ES:SE:LP:AF:SS:ID   -0.0042:0.0074:0.244125:0.5763:54930:rs3766192
1   1018562 rs9442371   C   T   .   PASS    AF=0.5917   ES:SE:LP:AF:SS:ID   -0.0053:0.0073:0.327902:0.5917:54974:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.6017   ES:SE:LP:AF:SS:ID   -0.004:0.0074:0.229148:0.6017:54980:rs9442372
1   1021415 rs3737728   A   G   .   PASS    AF=0.7167   ES:SE:LP:AF:SS:ID   0.0016:0.0081:0.0757207:0.7167:55256:rs3737728
1   1021695 rs9442398   A   G   .   PASS    AF=0.725    ES:SE:LP:AF:SS:ID   -0.0007:0.0083:0.0315171:0.725:55131:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.5667   ES:SE:LP:AF:SS:ID   -0.0067:0.0082:0.387216:0.5667:50047:rs6701114
1   1089262 rs4970358   A   G   .   PASS    AF=0.9661   ES:SE:LP:AF:SS:ID   -0.008:0.018:0.180456:0.9661:50163:rs4970358
1   1097335 rs9442385   T   G   .   PASS    AF=0.94167  ES:SE:LP:AF:SS:ID   -0.007:0.014:0.21467:0.94167:52002:rs9442385
1   1099342 rs9660710   A   C   .   PASS    AF=0.94068  ES:SE:LP:AF:SS:ID   -0.0015:0.013:0.0409586:0.94068:54669:rs9660710
1   1100217 rs1891905   C   T   .   PASS    AF=0.95833  ES:SE:LP:AF:SS:ID   -0.0029:0.018:0.0604807:0.95833:54433:rs1891905
1   1124663 rs6684820   G   A   .   PASS    AF=0.2667   ES:SE:LP:AF:SS:ID   -0.0045:0.0086:0.221849:0.2667:54502:rs6684820
1   1125553 rs10907174  A   T   .   PASS    AF=0.225    ES:SE:LP:AF:SS:ID   -0.007:0.009:0.356547:0.225:53649:rs10907174
1   1130727 rs10907175  A   C   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.01:0.013:0.376751:0.1:55369:rs10907175
1   1135242 rs9729550   A   C   .   PASS    AF=0.275    ES:SE:LP:AF:SS:ID   -0.0024:0.0084:0.113509:0.275:54484:rs9729550
1   1138913 rs3819001   T   C   .   PASS    AF=0.0431   ES:SE:LP:AF:SS:ID   0.0074:0.019:0.161151:0.0431:52487:rs3819001
1   1140435 rs1815606   G   T   .   PASS    AF=0.3103   ES:SE:LP:AF:SS:ID   -0.009:0.0063:0.823909:0.3103:78032:rs1815606
1   1143657 rs3753348   C   G   .   PASS    AF=0.03333  ES:SE:LP:AF:SS:ID   -0.0017:0.021:0.0315171:0.03333:52472:rs3753348
1   1152631 rs11721 C   A   .   PASS    AF=0.08333  ES:SE:LP:AF:SS:ID   -0.009:0.013:0.309804:0.08333:54247:rs11721
1   1158277 rs3813199   G   A   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.0099:0.012:0.376751:0.1:55259:rs3813199
1   1162435 rs3766186   C   A   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.0083:0.012:0.30103:0.1:55250:rs3766186
1   1163804 rs7515488   C   T   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   -0.0082:0.01:0.366532:0.15:55208:rs7515488
1   1165310 rs11260562  G   A   .   PASS    AF=0.05172  ES:SE:LP:AF:SS:ID   -0.0054:0.017:0.124939:0.05172:51819:rs11260562
1   1176597 rs6675798   T   C   .   PASS    AF=0.1083   ES:SE:LP:AF:SS:ID   -0.023:0.013:1.10791:0.1083:52492:rs6675798
1   1181751 rs6603783   T   C   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.02:0.013:0.886057:0.1:54266:rs6603783
1   1192515 rs7524470   A   G   .   PASS    AF=0.05833  ES:SE:LP:AF:SS:ID   -0.0013:0.02:0.0222764:0.05833:50253:rs7524470
1   1194804 rs11804831  T   C   .   PASS    AF=0.2083   ES:SE:LP:AF:SS:ID   -0.014:0.0096:0.823909:0.2083:55157:rs11804831
1   1198618 rs12563338  T   A   .   PASS    AF=0.04167  ES:SE:LP:AF:SS:ID   -0.013:0.02:0.30103:0.04167:54010:rs12563338
1   1206343 rs6667923   C   A   .   PASS    AF=0.05833  ES:SE:LP:AF:SS:ID   -0.0087:0.019:0.187087:0.05833:54977:rs6667923
1   1206619 rs6668223   C   A   .   PASS    AF=0.0339   ES:SE:LP:AF:SS:ID   -0.0053:0.022:0.091515:0.0339:54751:rs6668223
1   1211292 rs6685064   C   T   .   PASS    AF=0.1  ES:SE:LP:AF:SS:ID   -0.0034:0.013:0.09691:0.1:54491:rs6685064
1   1474304 rs1571150   C   A   .   PASS    AF=0.3  ES:SE:LP:AF:SS:ID   0.016:0.0073:1.55284:0.3:56791:rs1571150
1   1478153 rs3766180   T   C   .   PASS    AF=0.2417   ES:SE:LP:AF:SS:ID   0.018:0.0075:1.72125:0.2417:56897:rs3766180
1   1478180 rs3766178   T   C   .   PASS    AF=0.2667   ES:SE:LP:AF:SS:ID   0.019:0.0076:1.85387:0.2667:56766:rs3766178
1   1481348 rs3766177   T   C   .   PASS    .   ES:SE:LP:SS:ID  0.019:0.0081:1.72125:55782:rs3766177
1   1483010 rs7517401   G   A   .   PASS    AF=0.2833   ES:SE:LP:AF:SS:ID   0.016:0.0075:1.45593:0.2833:56338:rs7517401
1   1486834 rs3128342   C   A   .   PASS    AF=0.3333   ES:SE:LP:AF:SS:ID   0.0096:0.0077:0.677781:0.3333:51331:rs3128342
1   1489670 rs7531530   C   T   .   PASS    AF=0.25 ES:SE:LP:AF:SS:ID   0.019:0.0078:1.82391:0.25:56396:rs7531530
1   1489928 rs7366884   T   C   .   PASS    AF=0.25 ES:SE:LP:AF:SS:ID   0.019:0.008:1.79588:0.25:56392:rs7366884
1   1497201 rs3766169   A   C   .   PASS    AF=0.2458   ES:SE:LP:AF:SS:ID   0.018:0.0075:1.85387:0.2458:56940:rs3766169
1   1499298 rs9439468   A   G   .   PASS    AF=0.3103   ES:SE:LP:AF:SS:ID   0.016:0.0071:1.55284:0.3103:56865:rs9439468
1   1500941 rs6603791   A   G   .   PASS    AF=0.3  ES:SE:LP:AF:SS:ID   0.015:0.0071:1.52288:0.3:56873:rs6603791
1   1501064 rs6656541   T   G   .   PASS    AF=0.3  ES:SE:LP:AF:SS:ID   0.015:0.0072:1.4437:0.3:56858:rs6656541
1   1505255 rs6603793   C   T   .   PASS    AF=0.3  ES:SE:LP:AF:SS:ID   0.015:0.0072:1.48149:0.3:56833:rs6603793
1   1509034 rs7520996   T   C   .   PASS    AF=0.2797   ES:SE:LP:AF:SS:ID   0.014:0.0074:1.17393:0.2797:56455:rs7520996
1   1510801 rs7519837   C   T   .   PASS    AF=0.2917   ES:SE:LP:AF:SS:ID   0.013:0.0074:1.06048:0.2917:56476:rs7519837
1   1706136 rs6603811   T   C   .   PASS    AF=0.97458  ES:SE:LP:AF:SS:ID   0.0026:0.011:0.091515:0.97458:84766:rs6603811
1   1706160 rs7531583   A   G   .   PASS    AF=0.7833   ES:SE:LP:AF:SS:ID   -0.0019:0.0059:0.130768:0.7833:96830:rs7531583