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-299/ieu-a-299.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-299/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 10:57:00 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-299/ieu-a-299.vcf.gz ...
Read summary statistics for 2424035 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, 1132846 SNPs remain.
After merging with regression SNP LD, 1132846 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2575 (0.0543)
Lambda GC: 1.1563
Mean Chi^2: 1.3765
Intercept: 0.975 (0.009)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Wed Feb  5 10:57:29 2020
Total time elapsed: 29.27s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9292,
    "inflation_factor": 1.0145,
    "mean_EFFECT": 0,
    "n": 187167,
    "n_snps": 2424035,
    "n_clumped_hits": 89,
    "n_p_sig": 3481,
    "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": 367263,
    "n_miss_AF_reference": 19261,
    "n_est": 185644.9537,
    "ratio_se_n": 0.9959,
    "mean_diff": -0,
    "ratio_diff": 13.0049,
    "sd_y_est1": 1.4865,
    "sd_y_est2": 1.4804,
    "r2_sum1": 0.0646,
    "r2_sum2": 0.0293,
    "r2_sum3": 0.0295,
    "r2_sum4": 0.0554,
    "ldsc_nsnp_merge_refpanel_ld": 1132846,
    "ldsc_nsnp_merge_regression_ld": 1132846,
    "ldsc_observed_scale_h2_beta": 0.2575,
    "ldsc_observed_scale_h2_se": 0.0543,
    "ldsc_intercept_beta": 0.975,
    "ldsc_intercept_se": 0.009,
    "ldsc_lambda_gc": 1.1563,
    "ldsc_mean_chisq": 1.3765,
    "ldsc_ratio": -0.0664
}
 

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 TRUE
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 34 0 2424035 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 8.583903e+00 5.647909e+00 1.0000e+00 4.000000e+00 8.000000e+00 1.200000e+01 2.20000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.873718e+07 5.563919e+07 1.1523e+04 3.253019e+07 7.008342e+07 1.141110e+08 2.49219e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 3.110000e-05 9.586800e-03 -3.0710e-01 -4.700000e-03 0.000000e+00 4.800000e-03 2.52800e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 7.593900e-03 4.325800e-03 3.4000e-03 5.100000e-03 5.900000e-03 8.200000e-03 8.56000e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.961791e-01 2.911754e-01 0.0000e+00 2.435998e-01 4.969000e-01 7.484004e-01 1.00000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.765754e-01 2.959455e-01 0.0000e+00 2.147015e-01 4.688144e-01 7.338565e-01 1.00000e+00 ▇▇▆▆▆
numeric AF 367263 0.8484910 NA NA NA NA NA 3.563925e-01 2.699493e-01 1.3190e-03 1.240000e-01 2.902000e-01 5.515000e-01 9.98681e-01 ▇▅▃▂▂
numeric AF_reference 19261 0.9920542 NA NA NA NA NA 3.594604e-01 2.553776e-01 0.0000e+00 1.451680e-01 2.967250e-01 5.427320e-01 1.00000e+00 ▇▆▃▃▂
numeric N 0 1.0000000 NA NA NA NA NA 9.514778e+04 1.777230e+04 5.0000e+04 9.262000e+04 9.429400e+04 9.431100e+04 1.87167e+05 ▁▇▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 721290 rs12565286 G C 0.0175 0.0188 0.4020999 0.3519306 0.04354 0.0371406 58663.6
1 752566 rs3094315 G A -0.0051 0.0086 0.6222000 0.5531656 0.83640 0.7182510 57135.0
1 775659 rs2905035 A G -0.0118 0.0098 0.1687998 0.2285580 NA 0.7450080 54570.0
1 777122 rs2980319 A T -0.0119 0.0099 0.1580000 0.2293557 NA 0.7472040 54570.0
1 779322 rs4040617 A G 0.0083 0.0101 0.2795001 0.4112009 0.12930 0.2264380 52828.0
1 785050 rs2905062 G A -0.0054 0.0070 0.3995002 0.4404529 0.86680 0.6269970 93322.0
1 785989 rs2980300 T C -0.0087 0.0097 0.2454997 0.3697684 0.84960 0.6269970 54393.0
1 990380 rs3121561 C T 0.0261 0.0103 0.0343700 0.0112775 0.29550 0.3434500 64740.0
1 998501 rs3813193 G C 0.0181 0.0110 0.1365001 0.0998761 NA 0.2066690 56178.0
1 1003629 rs4075116 C T 0.0011 0.0068 0.6773997 0.8714911 0.73610 0.7206470 80848.0
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51151724 rs6010061 C T 0.0023 0.0059 0.6724005 0.6966619 0.42080 0.6098240 92817
22 51156933 rs6010063 A G -0.0022 0.0050 0.7780007 0.6599371 0.40770 0.4960060 90402
22 51158017 rs6010065 G C -0.0009 0.0049 0.9612001 0.8542696 NA 0.5475240 92096
22 51163138 rs715586 C T 0.0034 0.0052 0.7567998 0.5132109 0.12140 0.0902556 181860
22 51165664 rs8137951 G A 0.0014 0.0038 0.4960997 0.7125593 0.28100 0.4063500 184202
22 51171693 rs756638 G A 0.0111 0.0065 0.1863001 0.0876935 0.25990 0.3049120 83565
22 51175626 rs3810648 A G -0.0042 0.0101 0.6790004 0.6775259 0.05277 0.1084270 90377
22 51178090 rs2285395 G A -0.0053 0.0075 0.4979996 0.4797736 0.05145 0.0666933 177551
22 51196164 rs8136603 A T -0.0036 0.0125 0.6729999 0.7733467 NA 0.1427720 92096
22 51212875 rs2238837 A C -0.0035 0.0078 0.7878000 0.6536351 0.22690 0.3724040 74471

bcf preview

1   721290  rs12565286  G   C   .   PASS    AF=0.04354  ES:SE:LP:AF:SS:ID   0.0175:0.0188:0.395666:0.04354:58663.6:rs12565286
1   752566  rs3094315   G   A   .   PASS    AF=0.8364   ES:SE:LP:AF:SS:ID   -0.0051:0.0086:0.20607:0.8364:57135:rs3094315
1   775659  rs2905035   A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0118:0.0098:0.772628:54570:rs2905035
1   777122  rs2980319   A   T   .   PASS    .   ES:SE:LP:SS:ID  -0.0119:0.0099:0.801343:54570:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.1293   ES:SE:LP:AF:SS:ID   0.0083:0.0101:0.553618:0.1293:52828:rs4040617
1   785050  rs2905062   G   A   .   PASS    AF=0.8668   ES:SE:LP:AF:SS:ID   -0.0054:0.007:0.398483:0.8668:93322:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.8496   ES:SE:LP:AF:SS:ID   -0.0087:0.0097:0.609949:0.8496:54393:rs2980300
1   990380  rs3121561   C   T   .   PASS    AF=0.2955   ES:SE:LP:AF:SS:ID   0.0261:0.0103:1.46382:0.2955:64740:rs3121561
1   998501  rs3813193   G   C   .   PASS    .   ES:SE:LP:SS:ID  0.0181:0.011:0.864867:56178:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.7361   ES:SE:LP:AF:SS:ID   0.0011:0.0068:0.169155:0.7361:80848:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.1596   ES:SE:LP:AF:SS:ID   0.0116:0.0099:0.5157:0.1596:56178:rs3934834
1   1017170 rs3766193   C   G   .   PASS    .   ES:SE:LP:SS:ID  -0.0116:0.0065:1.30539:90312:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5488   ES:SE:LP:AF:SS:ID   -0.0086:0.0062:0.980884:0.5488:90312:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.1504   ES:SE:LP:AF:SS:ID   0.0186:0.0109:0.825068:0.1504:56178:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.562    ES:SE:LP:AF:SS:ID   -0.0073:0.0061:0.799697:0.562:90312:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.562    ES:SE:LP:AF:SS:ID   -0.0069:0.006:0.774949:0.562:90285:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.1636   ES:SE:LP:AF:SS:ID   0.0197:0.0115:0.834756:0.1636:56178:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.7203   ES:SE:LP:AF:SS:ID   -0.0009:0.0062:0.258927:0.7203:89209:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.157    ES:SE:LP:AF:SS:ID   0.0206:0.0112:0.88706:0.157:56178:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.7203   ES:SE:LP:AF:SS:ID   -0.0018:0.0065:0.369979:0.7203:90312:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.5633   ES:SE:LP:AF:SS:ID   -0.0134:0.0065:1.39567:0.5633:89434:rs6701114
1   1026707 rs4074137   C   A   .   PASS    AF=0.5976   ES:SE:LP:AF:SS:ID   -0.0098:0.0071:0.578232:0.5976:59297:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.1478   ES:SE:LP:AF:SS:ID   0.0186:0.0087:1.4608:0.1478:59297:rs6687776
1   1031540 rs9651273   A   G   .   PASS    AF=0.719    ES:SE:LP:AF:SS:ID   -0.0054:0.007:0.184289:0.719:59297:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.08971  ES:SE:LP:AF:SS:ID   0.0071:0.0104:0.164436:0.08971:74268:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.1174   ES:SE:LP:AF:SS:ID   0.0108:0.0098:0.441892:0.1174:66427:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.1174   ES:SE:LP:AF:SS:ID   0.01:0.0093:0.366835:0.1174:74268:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.08443  ES:SE:LP:AF:SS:ID   0.0073:0.0101:0.155336:0.08443:76661:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.1174   ES:SE:LP:AF:SS:ID   0.0102:0.0089:0.420559:0.1174:74268:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.08839  ES:SE:LP:AF:SS:ID   0.0068:0.0104:0.153539:0.08839:74268:rs4970409
1   1060235 rs7540009   G   A   .   PASS    AF=0.0277   ES:SE:LP:AF:SS:ID   0.0282:0.0219:0.826231:0.0277:52219:rs7540009
1   1060608 rs17160824  G   A   .   PASS    AF=0.08707  ES:SE:LP:AF:SS:ID   0.0077:0.0104:0.166662:0.08707:74268:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.08575  ES:SE:LP:AF:SS:ID   0.0078:0.0105:0.180719:0.08575:74268:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.08575  ES:SE:LP:AF:SS:ID   0.0105:0.0104:0.284331:0.08575:74268:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.3918   ES:SE:LP:AF:SS:ID   0.0128:0.0075:0.899285:0.3918:59297:rs11807848
1   1062015 rs9659914   C   T   .   PASS    AF=0.0277   ES:SE:LP:AF:SS:ID   0.0281:0.0238:0.760951:0.0277:52219:rs9659914
1   1062638 rs9442373   C   A   .   PASS    AF=0.5607   ES:SE:LP:AF:SS:ID   -0.0149:0.0075:1.26257:0.5607:59297:rs9442373
1   1064535 rs6682475   G   C   .   PASS    .   ES:SE:LP:SS:ID  -0.0092:0.01:0.616903:59297:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.1161   ES:SE:LP:AF:SS:ID   0.0101:0.0096:0.50724:0.1161:59297:rs2298217
1   1066029 rs12145826  G   A   .   PASS    AF=0.06596  ES:SE:LP:AF:SS:ID   0.0413:0.0183:1.09637:0.06596:50146:rs12145826
1   1066403 rs10907182  T   C   .   PASS    AF=0.5897   ES:SE:LP:AF:SS:ID   -0.0131:0.0085:1.0364:0.5897:59297:rs10907182
1   1071118 rs10907183  G   C   .   PASS    .   ES:SE:LP:SS:ID  -0.0105:0.0089:0.775726:59297:rs10907183
1   1077064 rs4970357   C   A   .   PASS    AF=0.91161  ES:SE:LP:AF:SS:ID   0.0041:0.0108:0.017774:0.91161:78206:rs4970357
1   1087683 rs9442380   T   C   .   PASS    AF=0.93404  ES:SE:LP:AF:SS:ID   0.0068:0.0102:0.111821:0.93404:87863:rs9442380
1   1089262 rs4970358   A   G   .   PASS    AF=0.96702  ES:SE:LP:AF:SS:ID   0.0044:0.014:0.0723217:0.96702:86248:rs4970358
1   1094738 rs4970362   A   G   .   PASS    AF=0.6293   ES:SE:LP:AF:SS:ID   -0.0003:0.0096:0.0380097:0.6293:55106:rs4970362
1   1097335 rs9442385   T   G   .   PASS    AF=0.93668  ES:SE:LP:AF:SS:ID   0.0056:0.0098:0.0684913:0.93668:87315:rs9442385
1   1099342 rs9660710   A   C   .   PASS    AF=0.93668  ES:SE:LP:AF:SS:ID   0.0058:0.0096:0.0820746:0.93668:88574:rs9660710
1   1100217 rs1891905   C   T   .   PASS    AF=0.94987  ES:SE:LP:AF:SS:ID   0.0046:0.015:0.0522723:0.94987:86248:rs1891905
1   1106473 rs4970420   G   A   .   PASS    AF=0.19 ES:SE:LP:AF:SS:ID   -0.0033:0.0101:0.158203:0.19:59297:rs4970420