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-60/ieu-a-60.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-60/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 10:13:09 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-60/ieu-a-60.vcf.gz ...
Read summary statistics for 2533037 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, 1173414 SNPs remain.
After merging with regression SNP LD, 1173414 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1327 (0.006)
Lambda GC: 1.0353
Mean Chi^2: 1.143
Intercept: 0.7612 (0.0065)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Tue Feb  4 10:13:40 2020
Total time elapsed: 31.22s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9179,
    "inflation_factor": 1.0475,
    "mean_EFFECT": 0.0001,
    "n": 244441,
    "n_snps": 2533037,
    "n_clumped_hits": 46,
    "n_p_sig": 999,
    "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": 45300,
    "n_miss_AF_reference": 22356,
    "n_est": 247520.1989,
    "ratio_se_n": 1.0063,
    "mean_diff": -0,
    "ratio_diff": 6.3635,
    "sd_y_est1": 1.5049,
    "sd_y_est2": 1.5143,
    "r2_sum1": 0.0147,
    "r2_sum2": 0.0065,
    "r2_sum3": 0.0064,
    "r2_sum4": 0.0112,
    "ldsc_nsnp_merge_refpanel_ld": 1173414,
    "ldsc_nsnp_merge_regression_ld": 1173414,
    "ldsc_observed_scale_h2_beta": 0.1327,
    "ldsc_observed_scale_h2_se": 0.006,
    "ldsc_intercept_beta": 0.7612,
    "ldsc_intercept_se": 0.0065,
    "ldsc_lambda_gc": 1.0353,
    "ldsc_mean_chisq": 1.143,
    "ldsc_ratio": -1.6699
}

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 2533037 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 8.595283e+00 5.662715e+00 1.0000 4.000000e+00 8.000000e+00 1.200000e+01 2.30000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA 7.880965e+07 5.566604e+07 11523.0000 3.266317e+07 7.020605e+07 1.142381e+08 2.49219e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA 5.520000e-05 9.263600e-03 -0.2300 -4.200000e-03 0.000000e+00 4.200000e-03 2.20000e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA 7.449100e-03 6.345400e-03 0.0032 4.600000e-03 5.400000e-03 7.600000e-03 1.40000e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA 4.929631e-01 2.930227e-01 0.0000 2.399999e-01 4.899999e-01 7.499995e-01 1.00000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA 4.929068e-01 2.929798e-01 0.0000 2.372779e-01 4.932271e-01 7.467584e-01 1.00000e+00 ▇▇▇▇▇
numeric AF 45300 0.9821163 NA NA NA NA NA 3.551732e-01 2.765008e-01 0.0083 1.167000e-01 2.917000e-01 5.583000e-01 9.91700e-01 ▇▅▃▂▂
numeric AF_reference 22356 0.9911742 NA NA NA NA NA 3.598983e-01 2.573112e-01 0.0000 1.433710e-01 2.969250e-01 5.453270e-01 1.00000e+00 ▇▆▃▃▂
numeric N 0 1.0000000 NA NA NA NA NA 1.490108e+05 2.429419e+04 50003.0000 1.436000e+05 1.537770e+05 1.539240e+05 2.44441e+05 ▁▁▇▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 721290 rs12565286 G C 0.0014 0.0160 0.9299999 0.9302741 0.06780 0.0371406 75797
1 723819 rs11804171 T A 0.0140 0.0200 0.4899999 0.4839273 0.03704 0.1345850 57209
1 752566 rs3094315 G A -0.0012 0.0077 0.8800001 0.8761559 0.84480 0.7182510 83973
1 754192 rs3131968 A G -0.0069 0.0100 0.5099998 0.4901942 0.87500 0.6785140 61521
1 768448 rs12562034 G A -0.0060 0.0130 0.6400000 0.6444123 0.09167 0.1918930 57610
1 775659 rs2905035 A G -0.0012 0.0083 0.8900000 0.8850438 0.87500 0.7450080 95427
1 777122 rs2980319 A T -0.0013 0.0083 0.8800001 0.8755392 0.87500 0.7472040 95429
1 779322 rs4040617 A G 0.0039 0.0090 0.6600001 0.6647726 0.12500 0.2264380 83587
1 780785 rs2977612 T A -0.0050 0.0090 0.5800000 0.5785147 0.86610 0.6693290 83687
1 785050 rs2905062 G A -0.0034 0.0066 0.5999997 0.6064471 NA 0.6269970 131930
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51217134 rs117417021 A G 0.0091 0.0077 0.2399999 0.2372779 0.441700 0.2671730 90723
22 51222100 rs114553188 G T -0.0150 0.0130 0.2200002 0.2485632 0.066700 0.0880591 119050
22 51223637 rs375798137 G A -0.0150 0.0130 0.2200002 0.2485632 0.066700 0.0788738 119048
22 51229805 rs9616985 T C 0.0140 0.0150 0.3500000 0.3506479 0.091700 0.0730831 85329
23 35921591 rs2204667 C G 0.0010 0.0059 0.8700001 0.8654100 0.166700 NA 153879
23 51666786 rs14115 A G 0.0140 0.0097 0.1499999 0.1489363 0.025000 NA 141866
23 70163799 rs1626496 A C -0.0026 0.0085 0.7600007 0.7596942 0.075000 NA 153769
23 74963352 rs1053838 T G -0.0420 0.0640 0.5199996 0.5116633 0.991379 NA 54959
23 91415872 rs6562597 G A -0.0110 0.0170 0.4899999 0.5175939 0.008300 0.0021192 135297
23 118495837 rs12882977 G A -0.0007 0.0043 0.8700001 0.8706832 0.516700 0.2307280 153927

bcf preview

1   721290  rs12565286  G   C   .   PASS    AF=0.0678   ES:SE:LP:AF:SS:ID   0.0014:0.016:0.0315171:0.0678:75797:rs12565286
1   723819  rs11804171  T   A   .   PASS    AF=0.03704  ES:SE:LP:AF:SS:ID   0.014:0.02:0.309804:0.03704:57209:rs11804171
1   752566  rs3094315   G   A   .   PASS    AF=0.8448   ES:SE:LP:AF:SS:ID   -0.0012:0.0077:0.0555173:0.8448:83973:rs3094315
1   754192  rs3131968   A   G   .   PASS    AF=0.875    ES:SE:LP:AF:SS:ID   -0.0069:0.01:0.29243:0.875:61521:rs3131968
1   768448  rs12562034  G   A   .   PASS    AF=0.09167  ES:SE:LP:AF:SS:ID   -0.006:0.013:0.19382:0.09167:57610:rs12562034
1   775659  rs2905035   A   G   .   PASS    AF=0.875    ES:SE:LP:AF:SS:ID   -0.0012:0.0083:0.05061:0.875:95427:rs2905035
1   777122  rs2980319   A   T   .   PASS    AF=0.875    ES:SE:LP:AF:SS:ID   -0.0013:0.0083:0.0555173:0.875:95429:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.125    ES:SE:LP:AF:SS:ID   0.0039:0.009:0.180456:0.125:83587:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.8661   ES:SE:LP:AF:SS:ID   -0.005:0.009:0.236572:0.8661:83687:rs2977612
1   785050  rs2905062   G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0034:0.0066:0.221849:131930:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.8729   ES:SE:LP:AF:SS:ID   -0.005:0.009:0.236572:0.8729:83587:rs2980300
1   798026  rs4951864   C   T   .   PASS    AF=0.9  ES:SE:LP:AF:SS:ID   0.0029:0.015:0.0705811:0.9:50146:rs4951864
1   798801  rs12132517  G   A   .   PASS    AF=0.1083   ES:SE:LP:AF:SS:ID   -0.0067:0.015:0.180456:0.1083:50067:rs12132517
1   798959  rs11240777  G   A   .   PASS    AF=0.1667   ES:SE:LP:AF:SS:ID   0.002:0.009:0.0861861:0.1667:76647:rs11240777
1   962210  rs3128126   A   G   .   PASS    AF=0.425    ES:SE:LP:AF:SS:ID   -0.0048:0.0093:0.21467:0.425:60944:rs3128126
1   990380  rs3121561   C   T   .   PASS    AF=0.2667   ES:SE:LP:AF:SS:ID   -0.003:0.0076:0.161151:0.2667:109323:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.15 ES:SE:LP:AF:SS:ID   0.0026:0.0077:0.130768:0.15:101681:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.7373   ES:SE:LP:AF:SS:ID   0.0045:0.0055:0.387216:0.7373:148028:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.1167   ES:SE:LP:AF:SS:ID   0.0042:0.0071:0.259637:0.1167:113607:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.5667   ES:SE:LP:AF:SS:ID   0.0035:0.0052:0.30103:0.5667:149534:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.5763   ES:SE:LP:AF:SS:ID   0.0042:0.0048:0.420216:0.5763:150197:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.09649  ES:SE:LP:AF:SS:ID   0.0039:0.0073:0.229148:0.09649:113439:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.5917   ES:SE:LP:AF:SS:ID   0.0033:0.0048:0.309804:0.5917:150278:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.6017   ES:SE:LP:AF:SS:ID   0.0033:0.0048:0.309804:0.6017:150260:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.1271   ES:SE:LP:AF:SS:ID   0.0047:0.0074:0.275724:0.1271:113395:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.7167   ES:SE:LP:AF:SS:ID   0.0058:0.0052:0.585027:0.7167:150869:rs3737728
1   1021583 rs10907178  A   C   .   PASS    .   ES:SE:LP:SS:ID  0.0045:0.0074:0.267606:111190:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.725    ES:SE:LP:AF:SS:ID   0.0056:0.0053:0.537602:0.725:150618:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.5667   ES:SE:LP:AF:SS:ID   0.0031:0.0053:0.251812:0.5667:138137:rs6701114
1   1026707 rs4074137   C   A   .   PASS    AF=0.6  ES:SE:LP:AF:SS:ID   -0.002:0.0058:0.136677:0.6:111416:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.08333  ES:SE:LP:AF:SS:ID   0.0063:0.0068:0.455932:0.08333:114783:rs6687776
1   1030633 rs6678318   G   A   .   PASS    AF=0.08621  ES:SE:LP:AF:SS:ID   0.004:0.0076:0.221849:0.08621:100316:rs6678318
1   1031540 rs9651273   A   G   .   PASS    AF=0.6583   ES:SE:LP:AF:SS:ID   -0.0001:0.0059:0.00436481:0.6583:111353:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.05 ES:SE:LP:AF:SS:ID   0.0064:0.0081:0.366532:0.05:132784:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.075    ES:SE:LP:AF:SS:ID   0.0057:0.0073:0.366532:0.075:122872:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.06667  ES:SE:LP:AF:SS:ID   0.0071:0.0076:0.455932:0.06667:129134:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.05172  ES:SE:LP:AF:SS:ID   0.006:0.0081:0.337242:0.05172:132694:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.06667  ES:SE:LP:AF:SS:ID   0.0063:0.0075:0.39794:0.06667:129130:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.05 ES:SE:LP:AF:SS:ID   0.0064:0.0085:0.346787:0.05:130536:rs4970409
1   1060174 rs7548798   C   T   .   PASS    AF=0.3981   ES:SE:LP:AF:SS:ID   -0.0009:0.0073:0.0457575:0.3981:84660:rs7548798
1   1060235 rs7540009   G   A   .   PASS    AF=0.01667  ES:SE:LP:AF:SS:ID   -0.0001:0.016:0.00436481:0.01667:104928:rs7540009
1   1060608 rs17160824  G   A   .   PASS    AF=0.05833  ES:SE:LP:AF:SS:ID   0.0059:0.0085:0.309804:0.05833:132644:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.05455  ES:SE:LP:AF:SS:ID   0.0071:0.0085:0.39794:0.05455:132658:rs17160826
1   1061152 rs12748370  T   C   .   PASS    .   ES:SE:LP:SS:ID  0.0073:0.0086:0.39794:130454:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.4123   ES:SE:LP:AF:SS:ID   0.0019:0.0059:0.124939:0.4123:109740:rs11807848
1   1062015 rs9659914   C   T   .   PASS    AF=0.01667  ES:SE:LP:AF:SS:ID   0.0056:0.017:0.124939:0.01667:93183:rs9659914
1   1062638 rs9442373   C   A   .   PASS    AF=0.5517   ES:SE:LP:AF:SS:ID   0.0005:0.0058:0.0315171:0.5517:108942:rs9442373
1   1064535 rs6682475   G   C   .   PASS    AF=0.7542   ES:SE:LP:AF:SS:ID   -0.012:0.0086:0.744727:0.7542:84942:rs6682475
1   1064979 rs2298217   C   T   .   PASS    AF=0.08333  ES:SE:LP:AF:SS:ID   0.0051:0.0076:0.30103:0.08333:103039:rs2298217
1   1066403 rs10907182  T   C   .   PASS    AF=0.675    ES:SE:LP:AF:SS:ID   -0.0003:0.0061:0.0177288:0.675:106305:rs10907182