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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    "FORMAT.1": "<ID=ES,Number=A,Type=Float,Description=\"Effect size estimate relative to the alternative allele\">",
    "FORMAT.2": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
    "FORMAT.3": "<ID=ID,Number=1,Type=String,Description=\"Study variant identifier\">",
    "FORMAT.4": "<ID=LP,Number=A,Type=Float,Description=\"-log10 p-value for effect estimate\">",
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    "INFO.1": "<ID=ReverseComplementedAlleles,Number=0,Type=Flag,Description=\"The REF and the ALT alleles have been reverse complemented in liftover since the mapping from the previous reference to the current one was on the negative strand.\">",
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    "META.7": "<ID=VariantsNotRead,Number=1,Type=Integer,Description=\"Number of variants that could not be read\">",
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    "file_date": "2019-10-27T07:19:08.816978",
    "gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005220/EBI-a-GCST005220_data.json --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/hg38/hg38.fa; 1.1.1",
    "reference": "file:/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/b37/human_g1k_v37.fasta",
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    "bcftools_annotateCommand": "annotate -a /mnt/storage/home/gh13047/mr-eve/vcf-reference-datasets/dbsnp/dbsnp.v153.b37.vcf.gz -c ID -o /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005220/EBI-a-GCST005220.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005220/EBI-a-GCST005220_data.vcf.gz; Date=Sun Oct 27 07:23:06 2019",
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    "bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST005220/ebi-a-GCST005220.vcf.gz; Date=Sat May  9 19:39:16 2020"
}

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/ebi_gwas_import/processed/EBI-a-GCST005220/EBI-a-GCST005220.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/ebi_gwas_import/processed/EBI-a-GCST005220/ldsc.txt \
--snplist /data/ref/snplist.gz \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/ 

Beginning analysis at Sun Oct 27 07:45:40 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005220/EBI-a-GCST005220.vcf.gz ...
and extracting SNPs specified in /data/ref/snplist.gz ...
Traceback (most recent call last):
  File "./ldsc/ldsc.py", line 647, in <module>
    sumstats.estimate_h2(args, log)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
    args, log, args.h2)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 246, in _read_ld_sumstats
    sumstats = _read_sumstats(args, log, fh, alleles=alleles, dropna=dropna)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 165, in _read_sumstats
    sumstats = ps.sumstats(fh, alleles=alleles, dropna=dropna, slh=args.snplist)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 85, in sumstats
    x = read_vcf(fh, alleles, slh)
  File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 161, in read_vcf
    with gzip.open(slh) as f:
  File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 34, in open
    return GzipFile(filename, mode, compresslevel)
  File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 94, in __init__
    fileobj = self.myfileobj = __builtin__.open(filename, mode or 'rb')
IOError: [Errno 2] No such file or directory: '/data/ref/snplist.gz'

Analysis finished at Sun Oct 27 07:45:55 2019
Total time elapsed: 15.18s

QC metrics

Metrics

Metrics

{
    "af_correlation": -0.0129,
    "inflation_factor": 1.0106,
    "mean_EFFECT": 0.0003,
    "n": "-Inf",
    "n_snps": 2421853,
    "n_clumped_hits": 0,
    "n_p_sig": 0,
    "n_mono": 0,
    "n_ns": 0,
    "n_mac": 0,
    "is_snpid_unique": false,
    "n_miss_EFFECT": 0,
    "n_miss_SE": 0,
    "n_miss_PVAL": 0,
    "n_miss_AF": 1887,
    "n_miss_AF_reference": 18768,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NaN",
    "sd_y_est2": "NA",
    "r2_sum1": 0,
    "r2_sum2": 0,
    "r2_sum3": 0,
    "r2_sum4": 0,
    "ldsc_nsnp_merge_refpanel_ld": "NA",
    "ldsc_nsnp_merge_regression_ld": "NA",
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": "NA",
    "ldsc_intercept_se": "NA",
    "ldsc_lambda_gc": "NA",
    "ldsc_mean_chisq": "NA",
    "ldsc_ratio": "NA"
}

Flags

name value
af_correlation TRUE
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq TRUE
n_p_sig FALSE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio TRUE
ldsc_intercept_beta TRUE
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 logical.mean logical.count numeric.mean numeric.sd numeric.p0 numeric.p25 numeric.p50 numeric.p75 numeric.p100 numeric.hist
character ID 0 1.0000000 3 42 0 2415637 0 NA NA 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 NA NA
character ALT 0 1.0000000 1 1 0 4 0 NA NA NA NA NA NA NA NA NA NA
logical N 2415639 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
numeric CHROM 0 1.0000000 NA NA NA NA NA NA NA 8.584695e+00 5.654126e+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 NA NA 7.886645e+07 5.565556e+07 1.1523e+04 3.271277e+07 7.033533e+07 1.143398e+08 2.492190e+08 ▇▇▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 2.754000e-04 3.820860e-02 -5.9000e-01 -2.000000e-02 1.400000e-04 2.000000e-02 6.300000e-01 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 3.360860e-02 1.774940e-02 2.1000e-02 2.300000e-02 2.700000e-02 3.700000e-02 3.000000e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.985382e-01 2.896027e-01 9.0000e-07 2.474201e-01 4.977451e-01 7.492867e-01 9.999890e-01 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.986011e-01 2.896492e-01 1.5000e-06 2.475789e-01 4.965045e-01 7.496136e-01 9.999871e-01 ▇▇▇▇▇
numeric AF 1887 0.9992188 NA NA NA NA NA NA NA 5.021701e-01 3.067951e-01 4.0000e-03 2.170000e-01 5.000000e-01 7.860000e-01 9.960000e-01 ▇▆▆▆▇
numeric AF_reference 18768 0.9922306 NA NA NA NA NA NA NA 3.629796e-01 2.542659e-01 1.9970e-04 1.493610e-01 3.019170e-01 5.465260e-01 1.000000e+00 ▇▆▅▃▂

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 721290 rs12565286 G C -0.120 0.071 0.1025600 0.0910010 0.968 0.0371406 NA
1 723819 rs11804171 T A -0.120 0.070 0.0966029 0.0864763 0.963 0.1345850 NA
1 723891 rs2977670 G C 0.072 0.081 0.3763128 0.3740628 0.071 0.7799520 NA
1 752566 rs3094315 G A 0.042 0.028 0.1288971 0.1336144 0.835 0.7182510 NA
1 754192 rs3131968 A G 0.038 0.046 0.4088773 0.4087548 0.875 0.6785140 NA
1 775659 rs2905035 A G 0.036 0.033 0.2677898 0.2753129 0.125 0.7450080 NA
1 777122 rs2980319 A T 0.037 0.033 0.2590001 0.2621976 0.134 0.7472040 NA
1 779322 rs4040617 A G -0.037 0.033 0.2657303 0.2621976 0.133 0.2264380 NA
1 780785 rs2977612 T A 0.037 0.033 0.2648518 0.2621976 0.866 0.6693290 NA
1 785050 rs2905062 G A 0.037 0.033 0.2621012 0.2621976 0.856 0.6269970 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51171693 rs756638 G A -0.0044 0.037 0.9051370 0.9053396 0.739 0.3049120 NA
22 51173542 rs4824147 T C 0.1400 0.130 0.2682730 0.2815146 0.958 0.9812300 NA
22 51175626 rs3810648 A G 0.1000 0.043 0.0175332 0.0200409 0.066 0.1084270 NA
22 51178090 rs2285395 G A 0.0980 0.044 0.0276261 0.0259291 0.934 0.0666933 NA
22 51196164 rs8136603 A T 0.1100 0.054 0.0458691 0.0416463 0.075 0.1427720 NA
22 51212875 rs2238837 A C -0.0680 0.034 0.0487001 0.0455003 0.385 0.3724040 NA
22 51216564 rs9616970 T C 0.0510 0.048 0.2827522 0.2880088 0.850 0.1563500 NA
22 51217134 rs117417021 A G -0.0420 0.035 0.2351820 0.2301393 0.442 0.2671730 NA
22 51223637 rs375798137 G A 0.1200 0.054 0.0296551 0.0262683 0.933 0.0788738 NA
23 118495837 rs12882977 G A 0.0160 0.022 0.4628508 0.4670589 0.491 0.2307280 NA

bcf preview

1   721290  rs12565286  G   C   .   PASS    AF=0.968    ES:SE:LP:AF:ID  -0.12:0.071:0.989022:0.968:rs12565286
1   723819  rs11804171  T   A   .   PASS    AF=0.963    ES:SE:LP:AF:ID  -0.12:0.07:1.01501:0.963:rs11804171
1   723891  rs2977670   G   C   .   PASS    AF=0.071    ES:SE:LP:AF:ID  0.072:0.081:0.424451:0.071:rs2977670
1   752566  rs3094315   G   A   .   PASS    AF=0.835    ES:SE:LP:AF:ID  0.042:0.028:0.889757:0.835:rs3094315
1   754192  rs3131968   A   G   .   PASS    AF=0.875    ES:SE:LP:AF:ID  0.038:0.046:0.388407:0.875:rs3131968
1   775659  rs2905035   A   G   .   PASS    AF=0.125    ES:SE:LP:AF:ID  0.036:0.033:0.572206:0.125:rs2905035
1   777122  rs2980319   A   T   .   PASS    AF=0.134    ES:SE:LP:AF:ID  0.037:0.033:0.5867:0.134:rs2980319
1   779322  rs4040617   A   G   .   PASS    AF=0.133    ES:SE:LP:AF:ID  -0.037:0.033:0.575559:0.133:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.866    ES:SE:LP:AF:ID  0.037:0.033:0.576997:0.866:rs2977612
1   785050  rs2905062   G   A   .   PASS    AF=0.856    ES:SE:LP:AF:ID  0.037:0.033:0.581531:0.856:rs2905062
1   785989  rs2980300   T   C   .   PASS    AF=0.868    ES:SE:LP:AF:ID  0.035:0.033:0.543563:0.868:rs2980300
1   798026  rs4951864   C   T   .   PASS    AF=0.1  ES:SE:LP:AF:ID  0.13:0.062:1.43261:0.1:rs4951864
1   798801  rs12132517  G   A   .   PASS    AF=0.892    ES:SE:LP:AF:ID  -0.12:0.063:1.33003:0.892:rs12132517
1   798959  rs11240777  G   A   .   PASS    AF=0.781    ES:SE:LP:AF:ID  -0.073:0.037:1.29081:0.781:rs11240777
1   990380  rs3121561   C   T   .   PASS    AF=0.267    ES:SE:LP:AF:ID  -0.043:0.045:0.471688:0.267:rs3121561
1   998501  rs3813193   G   C   .   PASS    AF=0.85 ES:SE:LP:AF:ID  -0.021:0.038:0.231959:0.85:rs3813193
1   1003629 rs4075116   C   T   .   PASS    AF=0.266    ES:SE:LP:AF:ID  0.016:0.024:0.2934:0.266:rs4075116
1   1005806 rs3934834   C   T   .   PASS    AF=0.124    ES:SE:LP:AF:ID  -0.022:0.037:0.255005:0.124:rs3934834
1   1017170 rs3766193   C   G   .   PASS    AF=0.431    ES:SE:LP:AF:ID  0.02:0.027:0.329182:0.431:rs3766193
1   1017197 rs3766192   C   T   .   PASS    AF=0.429    ES:SE:LP:AF:ID  0.027:0.025:0.555373:0.429:rs3766192
1   1017587 rs3766191   C   T   .   PASS    AF=0.124    ES:SE:LP:AF:ID  -0.019:0.038:0.203086:0.124:rs3766191
1   1018562 rs9442371   C   T   .   PASS    AF=0.408    ES:SE:LP:AF:ID  0.026:0.024:0.542127:0.408:rs9442371
1   1018704 rs9442372   A   G   .   PASS    AF=0.412    ES:SE:LP:AF:ID  0.026:0.024:0.547128:0.412:rs9442372
1   1021346 rs10907177  A   G   .   PASS    AF=0.137    ES:SE:LP:AF:ID  -0.018:0.04:0.18422:0.137:rs10907177
1   1021415 rs3737728   A   G   .   PASS    AF=0.265    ES:SE:LP:AF:ID  0.016:0.028:0.259266:0.265:rs3737728
1   1021583 rs10907178  A   C   .   PASS    AF=0.113    ES:SE:LP:AF:ID  -0.018:0.041:0.184423:0.113:rs10907178
1   1021695 rs9442398   A   G   .   PASS    AF=0.274    ES:SE:LP:AF:ID  0.016:0.028:0.255348:0.274:rs9442398
1   1022037 rs6701114   C   T   .   PASS    AF=0.433    ES:SE:LP:AF:ID  0.025:0.03:0.402549:0.433:rs6701114
1   1026707 rs4074137   C   A   .   PASS    AF=0.6  ES:SE:LP:AF:ID  0.046:0.039:0.640929:0.6:rs4074137
1   1030565 rs6687776   C   T   .   PASS    AF=0.133    ES:SE:LP:AF:ID  -0.095:0.045:1.45435:0.133:rs6687776
1   1031540 rs9651273   A   G   .   PASS    AF=0.283    ES:SE:LP:AF:ID  -0.012:0.036:0.135207:0.283:rs9651273
1   1036959 rs11579015  T   C   .   PASS    AF=0.95 ES:SE:LP:AF:ID  -0.1:0.068:0.855441:0.95:rs11579015
1   1040026 rs6671356   T   C   .   PASS    AF=0.885    ES:SE:LP:AF:ID  -0.034:0.06:0.243677:0.885:rs6671356
1   1046164 rs6666280   C   T   .   PASS    AF=0.067    ES:SE:LP:AF:ID  -0.034:0.059:0.249265:0.067:rs6666280
1   1048955 rs4970405   A   G   .   PASS    AF=0.088    ES:SE:LP:AF:ID  -0.092:0.067:0.767276:0.088:rs4970405
1   1049950 rs12726255  A   G   .   PASS    AF=0.115    ES:SE:LP:AF:ID  -0.018:0.055:0.12682:0.115:rs12726255
1   1053452 rs4970409   G   A   .   PASS    AF=0.907    ES:SE:LP:AF:ID  -0.072:0.064:0.592015:0.907:rs4970409
1   1060235 rs7540009   G   A   .   PASS    AF=0.983    ES:SE:LP:AF:ID  0.022:0.089:0.0934926:0.983:rs7540009
1   1060608 rs17160824  G   A   .   PASS    AF=0.903    ES:SE:LP:AF:ID  -0.075:0.064:0.618468:0.903:rs17160824
1   1061115 rs17160826  T   C   .   PASS    AF=0.945    ES:SE:LP:AF:ID  -0.075:0.064:0.62105:0.945:rs17160826
1   1061152 rs12748370  T   C   .   PASS    AF=0.95 ES:SE:LP:AF:ID  -0.076:0.065:0.617612:0.95:rs12748370
1   1061166 rs11807848  T   C   .   PASS    AF=0.611    ES:SE:LP:AF:ID  0.025:0.035:0.318298:0.611:rs11807848
1   1062015 rs9659914   C   T   .   PASS    AF=0.017    ES:SE:LP:AF:ID  0.021:0.091:0.0861623:0.017:rs9659914
1   1062638 rs9442373   C   A   .   PASS    AF=0.575    ES:SE:LP:AF:ID  0.042:0.035:0.653567:0.575:rs9442373
1   1064979 rs2298217   C   T   .   PASS    AF=0.115    ES:SE:LP:AF:ID  -0.11:0.05:1.54476:0.115:rs2298217
1   1066403 rs10907182  T   C   .   PASS    AF=0.675    ES:SE:LP:AF:ID  0.087:0.04:1.51018:0.675:rs10907182
1   1071118 rs10907183  G   C   .   PASS    AF=0.683    ES:SE:LP:AF:ID  0.086:0.041:1.41838:0.683:rs10907183
1   1077064 rs4970357   C   A   .   PASS    AF=0.916    ES:SE:LP:AF:ID  0.073:0.047:0.911194:0.916:rs4970357
1   1087683 rs9442380   T   C   .   PASS    AF=0.934    ES:SE:LP:AF:ID  0.032:0.043:0.349706:0.934:rs9442380
1   1089262 rs4970358   A   G   .   PASS    AF=0.034    ES:SE:LP:AF:ID  0.081:0.053:0.901554:0.034:rs4970358