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\">",
    "FORMAT.5": "<ID=NC,Number=A,Type=Float,Description=\"Number of cases used to estimate genetic effect\">",
    "FORMAT.6": "<ID=SE,Number=A,Type=Float,Description=\"Standard error of effect size estimate\">",
    "FORMAT.7": "<ID=SI,Number=A,Type=Float,Description=\"Accuracy score of summary data imputation\">",
    "FORMAT.8": "<ID=SS,Number=A,Type=Float,Description=\"Sample size used to estimate genetic effect\">",
    "INFO": "<ID=AF,Number=A,Type=Float,Description=\"Allele Frequency\">",
    "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.\">",
    "INFO.2": "<ID=SwappedAlleles,Number=0,Type=Flag,Description=\"The REF and the ALT alleles have been swapped in liftover due to changes in the reference. It is possible that not all INFO annotations reflect this swap, and in the genotypes, only the GT, PL, and AD fields have been modified. You should check the TAGS_TO_REVERSE parameter that was used during the LiftOver to be sure.\">",
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    "META.6": "<ID=VariantsNotHarmonised,Number=1,Type=Integer,Description=\"Total number of variants that could not be harmonised\">",
    "META.7": "<ID=VariantsNotRead,Number=1,Type=Integer,Description=\"Number of variants that could not be read\">",
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    "file_date": "2019-10-26T21:48:08.567714",
    "gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004575/EBI-a-GCST004575_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",
    "bcftools_annotateVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
    "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-GCST004575/EBI-a-GCST004575.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004575/EBI-a-GCST004575_data.vcf.gz; Date=Sat Oct 26 22:04:18 2019",
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    "bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST004575/ebi-a-GCST004575.vcf.gz; Date=Sun May 10 06:07:35 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-GCST004575/EBI-a-GCST004575.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-GCST004575/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 Sat Oct 26 22:28:03 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004575/EBI-a-GCST004575.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 Sat Oct 26 22:29:05 2019
Total time elapsed: 1.0m:1.95s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.962,
    "inflation_factor": 1.0207,
    "mean_EFFECT": 0.0002,
    "n": "-Inf",
    "n_snps": 9663718,
    "n_clumped_hits": 2,
    "n_p_sig": 110,
    "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": 0,
    "n_miss_AF_reference": 240193,
    "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 FALSE
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 59 0 9629260 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 9639750 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 8.991606e+00 6.105644e+00 1.0000 4.000000e+00 8.000000e+00 1.300000e+01 2.300000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.871350e+07 5.612785e+07 828.0000 3.242785e+07 6.962385e+07 1.146663e+08 2.492223e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.894000e-04 8.138790e-02 -1.2053 -2.810000e-02 -2.000000e-04 2.800000e-02 1.501000e+00 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 6.157220e-02 5.302670e-02 0.0119 2.540000e-02 3.760000e-02 7.740000e-02 4.941000e-01 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.967826e-01 2.885959e-01 0.0000 2.462998e-01 4.955997e-01 7.466000e-01 9.998000e-01 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.967820e-01 2.885960e-01 0.0000 2.463372e-01 4.956083e-01 7.465959e-01 9.997537e-01 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.399527e-01 2.536238e-01 0.0030 3.500000e-02 1.380000e-01 3.740000e-01 9.960000e-01 ▇▂▂▁▁
numeric AF_reference 240193 0.9750831 NA NA NA NA NA NA NA 2.349565e-01 2.529357e-01 0.0000 3.294730e-02 1.337860e-01 3.664140e-01 1.000000e+00 ▇▂▂▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 79033 rs2462495 A G -0.1628 0.1339 0.2242999 0.2240487 0.972 NA NA
1 79050 rs2949413 G T -0.1698 0.1350 0.2086998 0.2084721 0.972 NA NA
1 83084 rs181193408 T A -0.1911 0.1357 0.1590999 0.1590560 0.971 0.9201280 NA
1 84139 rs183605470 A T 0.3116 0.1219 0.0106001 0.0105824 0.033 0.0159744 NA
1 662622 rs61769339 G A 0.0440 0.0856 0.6068998 0.6072389 0.083 0.1475640 NA
1 668374 rs138476838 G A -0.0282 0.1460 0.8471000 0.8468410 0.024 0.0860623 NA
1 693731 rs12238997 A G 0.0021 0.0733 0.9770001 0.9771442 0.094 0.1417730 NA
1 706368 rs55727773 A G -0.0554 0.0548 0.3115997 0.3120409 0.356 0.2751600 NA
1 714019 rs114983708 A G 0.0447 0.1350 0.7408000 0.7405606 0.025 0.1383790 NA
1 721290 rs12565286 G C 0.0591 0.0762 0.4380997 0.4379908 0.036 0.0371406 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
23 154927185 rs185685661 T C -0.0930 0.0658 0.1572002 0.1575458 0.151 0.179603 NA
23 154927199 rs645904 C T -0.0259 0.0251 0.3036002 0.3021318 0.293 0.367417 NA
23 154927581 rs644138 G A -0.0212 0.0250 0.3962999 0.3964380 0.325 0.463576 NA
23 154929412 rs557132 C T -0.0289 0.0257 0.2610003 0.2607952 0.297 0.356821 NA
23 154930230 rs781880 A G -0.0266 0.0311 0.3927001 0.3923821 0.331 0.361854 NA
23 154972517 rs3899157 C T -0.0582 0.0606 0.3372997 0.3368559 0.219 0.222843 NA
23 154977448 rs306897 G A 0.0168 0.0863 0.8455000 0.8456515 0.098 0.116214 NA
23 154983133 rs306894 C T -0.0201 0.0370 0.5865000 0.5869623 0.508 0.393970 NA
23 155075814 rs5940597 G A 0.0531 0.0426 0.2125999 0.2125886 0.713 0.725439 NA
23 155195900 rs4518813 A G 0.0412 0.0386 0.2852003 0.2858104 0.358 0.461661 NA

bcf preview

1   79033   rs2462495   A   G   .   PASS    AF=0.972    ES:SE:LP:AF:ID  -0.1628:0.1339:0.649171:0.972:rs2462495
1   79050   rs2949413   G   T   .   PASS    AF=0.972    ES:SE:LP:AF:ID  -0.1698:0.135:0.680478:0.972:rs2949413
1   83084   rs4030326   T   A   .   PASS    AF=0.971    ES:SE:LP:AF:ID  -0.1911:0.1357:0.79833:0.971:rs4030326
1   84139   rs183605470 A   T   .   PASS    AF=0.033    ES:SE:LP:AF:ID  0.3116:0.1219:1.97469:0.033:rs183605470
1   662622  rs61769339  G   A   .   PASS    AF=0.083    ES:SE:LP:AF:ID  0.044:0.0856:0.216883:0.083:rs61769339
1   668374  rs138476838 G   A   .   PASS    AF=0.024    ES:SE:LP:AF:ID  -0.0282:0.146:0.0720653:0.024:rs138476838
1   693731  rs12238997  A   G   .   PASS    AF=0.094    ES:SE:LP:AF:ID  0.0021:0.0733:0.0101054:0.094:rs12238997
1   706368  rs12029736  A   G   .   PASS    AF=0.356    ES:SE:LP:AF:ID  -0.0554:0.0548:0.506403:0.356:rs12029736
1   714019  rs114983708 A   G   .   PASS    AF=0.025    ES:SE:LP:AF:ID  0.0447:0.135:0.130299:0.025:rs114983708
1   721290  rs12565286  G   C   .   PASS    AF=0.036    ES:SE:LP:AF:ID  0.0591:0.0762:0.358427:0.036:rs12565286
1   721757  rs189147642 T   A   .   PASS    AF=0.033    ES:SE:LP:AF:ID  0.0235:0.0915:0.0982693:0.033:rs189147642
1   723819  rs11804171  T   A   .   PASS    AF=0.039    ES:SE:LP:AF:ID  0.0481:0.1008:0.198185:0.039:rs11804171
1   726794  rs28454925  C   G   .   PASS    AF=0.032    ES:SE:LP:AF:ID  0.0514:0.0983:0.221198:0.032:rs28454925
1   727142  rs28641938  T   C   .   PASS    AF=0.032    ES:SE:LP:AF:ID  0.0488:0.0968:0.21169:0.032:rs28641938
1   727841  rs116587930 G   A   .   PASS    AF=0.022    ES:SE:LP:AF:ID  -0.1663:0.1674:0.494172:0.022:rs116587930
1   729679  rs4951859   C   G   .   PASS    AF=0.734    ES:SE:LP:AF:ID  -0.0122:0.0435:0.108351:0.734:rs4951859
1   730087  rs148120343 T   C   .   PASS    AF=0.022    ES:SE:LP:AF:ID  -0.1727:0.1642:0.533429:0.022:rs148120343
1   731718  rs58276399  T   C   .   PASS    AF=0.173    ES:SE:LP:AF:ID  0.0061:0.0525:0.042297:0.173:rs58276399
1   732164  rs138208096 T   G   .   PASS    AF=0.146    ES:SE:LP:AF:ID  0.0677:0.0886:0.352324:0.146:rs138208096
1   732809  rs12131618  T   C   .   PASS    AF=0.032    ES:SE:LP:AF:ID  0.002:0.1078:0.00638744:0.032:rs12131618
1   733013  rs4951860   T   C   .   PASS    AF=0.035    ES:SE:LP:AF:ID  0.03:0.0974:0.120503:0.035:rs4951860
1   734349  rs141242758 T   C   .   PASS    AF=0.165    ES:SE:LP:AF:ID  0.0143:0.0541:0.10122:0.165:rs141242758
1   736289  rs79010578  T   A   .   PASS    AF=0.163    ES:SE:LP:AF:ID  -0.0049:0.0539:0.0326393:0.163:rs79010578
1   748878  rs2519043   G   T   .   PASS    AF=0.669    ES:SE:LP:AF:ID  -0.0084:0.042:0.0751007:0.669:rs2519043
1   751456  rs141709959 T   C   .   PASS    AF=0.035    ES:SE:LP:AF:ID  0.1207:0.0948:0.69229:0.035:rs141709959
1   751756  rs28527770  T   C   .   PASS    AF=0.155    ES:SE:LP:AF:ID  -0.0042:0.0357:0.0425364:0.155:rs28527770
1   752242  rs12090487  T   A   .   PASS    AF=0.059    ES:SE:LP:AF:ID  0.0193:0.0675:0.110586:0.059:rs12090487
1   752478  rs146277091 G   A   .   PASS    AF=0.039    ES:SE:LP:AF:ID  0.0947:0.0861:0.56639:0.039:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.799    ES:SE:LP:AF:ID  -0.0019:0.0273:0.024844:0.799:rs3094315
1   752617  rs149886465 C   A   .   PASS    AF=0.04 ES:SE:LP:AF:ID  0.0924:0.0856:0.552377:0.04:rs149886465
1   752721  rs3131972   A   G   .   PASS    AF=0.745    ES:SE:LP:AF:ID  -0.005:0.0265:0.0703767:0.745:rs3131972
1   752796  rs148649543 C   T   .   PASS    AF=0.043    ES:SE:LP:AF:ID  0.1222:0.0832:0.847712:0.043:rs148649543
1   752894  rs3131971   T   C   .   PASS    AF=0.802    ES:SE:LP:AF:ID  0.0011:0.0304:0.012155:0.802:rs3131971
1   753405  rs3115860   C   A   .   PASS    AF=0.824    ES:SE:LP:AF:ID  -0.003:0.031:0.034375:0.824:rs3115860
1   753474  rs2073814   C   G   .   PASS    AF=0.748    ES:SE:LP:AF:ID  -0.0139:0.0282:0.206769:0.748:rs2073814
1   753541  rs2073813   G   A   .   PASS    AF=0.235    ES:SE:LP:AF:ID  0.0128:0.0286:0.183759:0.235:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.036    ES:SE:LP:AF:ID  0.0516:0.0882:0.252977:0.036:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.032    ES:SE:LP:AF:ID  0.0435:0.0953:0.188224:0.032:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.759    ES:SE:LP:AF:ID  -0.0037:0.0283:0.0473044:0.759:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.761    ES:SE:LP:AF:ID  -0.0032:0.0282:0.0415317:0.761:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.034    ES:SE:LP:AF:ID  0.0271:0.0925:0.113904:0.034:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.746    ES:SE:LP:AF:ID  -0.0021:0.0285:0.0263642:0.746:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.764    ES:SE:LP:AF:ID  -0.0015:0.0282:0.0194513:0.764:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.034    ES:SE:LP:AF:ID  0.0269:0.0927:0.112439:0.034:rs10454459
1   754954  rs10454454  G   A   .   PASS    AF=0.032    ES:SE:LP:AF:ID  0.0288:0.0988:0.113058:0.032:rs10454454
1   754964  rs3131966   C   T   .   PASS    AF=0.731    ES:SE:LP:AF:ID  -0.004:0.0273:0.053204:0.731:rs3131966
1   755274  rs78408995  C   T   .   PASS    AF=0.057    ES:SE:LP:AF:ID  0.0341:0.0691:0.20621:0.057:rs78408995
1   755364  rs150361407 G   C   .   PASS    AF=0.034    ES:SE:LP:AF:ID  0.0395:0.0974:0.164119:0.034:rs150361407
1   755609  rs188739018 T   C   .   PASS    AF=0.034    ES:SE:LP:AF:ID  0.0249:0.0952:0.100508:0.034:rs188739018
1   755775  rs3131965   A   G   .   PASS    AF=0.773    ES:SE:LP:AF:ID  0.0179:0.0347:0.217241:0.773:rs3131965