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\">",
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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.\">",
    "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.4": "<ID=TotalControls,Number=1,Type=Integer,Description=\"Total number of controls in the association study\">",
    "META.5": "<ID=TotalVariants,Number=1,Type=Integer,Description=\"Total number of variants in input\">",
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    "file_date": "2019-10-26T21:45:48.535965",
    "gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005904/EBI-a-GCST005904_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-GCST005904/EBI-a-GCST005904.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005904/EBI-a-GCST005904_data.vcf.gz; Date=Sat Oct 26 22:03:46 2019",
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    "bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST005904/ebi-a-GCST005904.vcf.gz; Date=Sun May 10 07:19:12 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-GCST005904/EBI-a-GCST005904.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-GCST005904/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 22:27:32 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005904/EBI-a-GCST005904.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 22:28:25 2019
Total time elapsed: 53.5s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9407,
    "inflation_factor": 1.0687,
    "mean_EFFECT": 9.1511e-07,
    "n": "-Inf",
    "n_snps": 7649378,
    "n_clumped_hits": 2,
    "n_p_sig": 20,
    "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": 68160,
    "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 58 0 7628827 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 7633415 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 8.648714e+00 5.757280e+00 1.0000000 4.000000e+00 8.000000e+00 1.300000e+01 2.200000e+01 ▇▅▅▂▂
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.879374e+07 5.641785e+07 828.0000000 3.230680e+07 6.934630e+07 1.146515e+08 2.492235e+08 ▇▆▅▂▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 9.000000e-07 3.045400e-03 -0.0333570 -1.478400e-03 -4.200000e-06 1.471200e-03 3.315000e-02 ▁▁▇▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.594000e-03 1.476900e-03 0.0012801 1.428300e-03 1.949400e-03 3.377400e-03 1.997400e-02 ▇▁▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.895483e-01 2.919983e-01 0.0000000 2.333673e-01 4.856350e-01 7.430534e-01 1.000000e+00 ▇▇▇▇▇
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.895474e-01 2.919989e-01 0.0000000 2.333639e-01 4.856327e-01 7.430462e-01 1.000000e+00 ▇▇▇▇▇
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 2.524247e-01 2.608517e-01 0.0100000 4.040210e-02 1.462630e-01 3.989650e-01 9.900000e-01 ▇▂▂▁▁
numeric AF_reference 68160 0.9910708 NA NA NA NA NA NA NA 2.517120e-01 2.524793e-01 0.0000000 4.432910e-02 1.615420e-01 3.939700e-01 1.000000e+00 ▇▃▂▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 15850 rs575961614 G A -0.0062481 0.0063696 0.3266330 0.3266297 0.0212635 0.0005990 NA
1 82103 rs2020400 T C -0.0050177 0.0031622 0.1125667 0.1125636 0.9243520 NA NA
1 174747 rs1399732465 C T -0.0033059 0.0064109 0.6060801 0.6060859 0.0255757 NA NA
1 234313 rs8179466 C T -0.0056621 0.0043997 0.1981208 0.1981192 0.0748172 NA NA
1 546697 rs12025928 A G -0.0019745 0.0031699 0.5333595 0.5333566 0.9131950 NA NA
1 568800 rs375217967 G A -0.0147800 0.0087324 0.0905316 0.0905417 0.0168753 0.0778754 NA
1 693731 rs12238997 A G -0.0006094 0.0021357 0.7753897 0.7753875 0.1163100 0.1417730 NA
1 705882 rs72631875 G A 0.0008698 0.0031256 0.7808004 0.7808077 0.0673328 0.0315495 NA
1 717587 rs144155419 G A 0.0004068 0.0057453 0.9435502 0.9435496 0.0157432 0.0045926 NA
1 722670 rs116030099 T C -0.0025024 0.0026008 0.3359619 0.3359665 0.1017330 0.0413339 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51218377 rs2519461 G C -0.0068481 0.0024781 0.0057201 0.0057194 0.0732067 0.0826677 NA
22 51219006 rs28729663 G A -0.0040250 0.0019131 0.0353834 0.0353859 0.1375390 0.2052720 NA
22 51219387 rs9616832 T C -0.0069456 0.0024820 0.0051369 0.0051358 0.0734182 0.0654952 NA
22 51219704 rs147475742 G A -0.0097840 0.0033290 0.0032931 0.0032925 0.0417469 0.0473243 NA
22 51220517 rs9616980 C G -0.0037584 0.0074400 0.6134512 0.6134456 0.0101449 0.0027955 NA
22 51221190 rs369304721 G A -0.0068475 0.0033278 0.0396278 0.0396222 0.0494155 NA NA
22 51221731 rs115055839 T C -0.0068520 0.0024831 0.0057916 0.0057898 0.0729359 0.0625000 NA
22 51222100 rs114553188 G T -0.0001939 0.0029200 0.9470524 0.9470506 0.0544675 0.0880591 NA
22 51229805 rs9616985 T C -0.0067267 0.0024921 0.0069502 0.0069504 0.0727534 0.0730831 NA
22 51232488 rs376461333 A G 0.0012746 0.0058371 0.8271438 0.8271472 0.0201327 NA NA

bcf preview

1   15850   rs575961614 G   A   .   PASS    AF=0.0212635    ES:SE:LP:AF:ID  -0.0062481:0.0063696:0.48594:0.0212635:rs575961614
1   82103   rs2020400   T   C   .   PASS    AF=0.924352 ES:SE:LP:AF:ID  -0.0050177:0.0031622:0.94859:0.924352:rs2020400
1   174747  rs1399732465    C   T   .   PASS    AF=0.0255757    ES:SE:LP:AF:ID  -0.0033059:0.0064109:0.21747:0.0255757:rs1399732465
1   234313  rs8179466   C   T   .   PASS    AF=0.0748172    ES:SE:LP:AF:ID  -0.0056621:0.0043997:0.70307:0.0748172:rs8179466
1   546697  rs12025928  A   G   .   PASS    AF=0.913195 ES:SE:LP:AF:ID  -0.0019745:0.0031699:0.27298:0.913195:rs12025928
1   568800  rs375217967 G   A   .   PASS    AF=0.0168753    ES:SE:LP:AF:ID  -0.01478:0.0087324:1.0432:0.0168753:rs375217967
1   693731  rs12238997  A   G   .   PASS    AF=0.11631  ES:SE:LP:AF:ID  -0.00060939:0.0021357:0.11048:0.11631:rs12238997
1   705882  rs72631875  G   A   .   PASS    AF=0.0673328    ES:SE:LP:AF:ID  0.00086975:0.0031256:0.10746:0.0673328:rs72631875
1   717587  rs144155419 G   A   .   PASS    AF=0.0157432    ES:SE:LP:AF:ID  0.00040682:0.0057453:0.025235:0.0157432:rs144155419
1   722670  rs116030099 T   C   .   PASS    AF=0.101733 ES:SE:LP:AF:ID  -0.0025024:0.0026008:0.47371:0.101733:rs116030099
1   724849  rs12126395  C   A   .   PASS    AF=0.0320405    ES:SE:LP:AF:ID  0.0035114:0.0061548:0.2454:0.0320405:rs12126395
1   730087  rs148120343 T   C   .   PASS    AF=0.0566662    ES:SE:LP:AF:ID  0.001263:0.0029763:0.17308:0.0566662:rs148120343
1   731453  rs186002080 G   A   .   PASS    AF=0.0159918    ES:SE:LP:AF:ID  0.0068723:0.0066993:0.51574:0.0159918:rs186002080
1   732989  rs369030935 C   T   .   PASS    AF=0.0262021    ES:SE:LP:AF:ID  -0.00048472:0.0049331:0.035398:0.0262021:rs369030935
1   734349  rs141242758 T   C   .   PASS    AF=0.121417 ES:SE:LP:AF:ID  6.9774e-05:0.0020284:0.012084:0.121417:rs141242758
1   736689  rs181876450 T   C   .   PASS    AF=0.0110269    ES:SE:LP:AF:ID  -0.013773:0.0072993:1.2279:0.0110269:rs181876450
1   753405  rs3115860   C   A   .   PASS    AF=0.870485 ES:SE:LP:AF:ID  -3.7542e-05:0.001925:0.0068106:0.870485:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.129018 ES:SE:LP:AF:ID  0.00027689:0.0019293:0.052624:0.129018:rs2073813
1   754182  rs3131969   A   G   .   PASS    AF=0.870063 ES:SE:LP:AF:ID  -5.1111e-05:0.0019216:0.0093147:0.870063:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.870172 ES:SE:LP:AF:ID  -5.7342e-05:0.0019224:0.010459:0.870172:rs3131968
1   754334  rs3131967   T   C   .   PASS    AF=0.870058 ES:SE:LP:AF:ID  -6.5533e-05:0.0019216:0.011979:0.870058:rs3131967
1   755240  rs181660517 T   G   .   PASS    AF=0.0137126    ES:SE:LP:AF:ID  0.0015674:0.0062643:0.095597:0.0137126:rs181660517
1   755890  rs3115858   A   T   .   PASS    AF=0.870147 ES:SE:LP:AF:ID  1.0978e-05:0.0019196:0.0019862:0.870147:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.869725 ES:SE:LP:AF:ID  -1.1176e-05:0.0019152:0.0020268:0.869725:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.868945 ES:SE:LP:AF:ID  0.00022039:0.0019109:0.041827:0.868945:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.869864 ES:SE:LP:AF:ID  -2.0624e-05:0.0019165:0.003745:0.869864:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.86987  ES:SE:LP:AF:ID  -1.9071e-05:0.0019167:0.0034616:0.86987:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.869881 ES:SE:LP:AF:ID  -2.2975e-05:0.0019167:0.0041734:0.869881:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.870315 ES:SE:LP:AF:ID  -8.6496e-05:0.0019217:0.015878:0.870315:rs3131954
1   761732  rs2286139   C   T   .   PASS    AF=0.863534 ES:SE:LP:AF:ID  -0.00011361:0.0019101:0.021104:0.863534:rs2286139
1   766007  rs61768174  A   C   .   PASS    AF=0.105759 ES:SE:LP:AF:ID  0.00034015:0.0021311:0.058892:0.105759:rs61768174
1   768253  rs2977608   A   C   .   PASS    AF=0.763614 ES:SE:LP:AF:ID  0.0009061:0.0015167:0.25945:0.763614:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.105221 ES:SE:LP:AF:ID  -0.0018401:0.002096:0.42021:0.105221:rs12562034
1   769223  rs60320384  C   G   .   PASS    AF=0.128982 ES:SE:LP:AF:ID  0.00027363:0.0019284:0.051996:0.128982:rs60320384
1   769885  rs200025137 G   A   .   PASS    AF=0.0142904    ES:SE:LP:AF:ID  -0.0042267:0.0096979:0.17851:0.0142904:rs200025137
1   770085  rs150344285 G   C   .   PASS    AF=0.0106168    ES:SE:LP:AF:ID  -0.0072297:0.0090155:0.37407:0.0106168:rs150344285
1   771823  rs2977605   T   C   .   PASS    AF=0.869727 ES:SE:LP:AF:ID  -0.00019515:0.0019184:0.036696:0.869727:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.129065 ES:SE:LP:AF:ID  0.00038885:0.0019271:0.075673:0.129065:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.869739 ES:SE:LP:AF:ID  -0.00023653:0.0019184:0.044853:0.869739:rs2905039
1   772927  rs116390263 C   T   .   PASS    AF=0.0166672    ES:SE:LP:AF:ID  0.0093454:0.0085764:0.55931:0.0166672:rs116390263
1   773124  rs142049927 T   C   .   PASS    AF=0.0128246    ES:SE:LP:AF:ID  0.011763:0.009723:0.64518:0.0128246:rs142049927
1   773136  rs146709693 G   T   .   PASS    AF=0.0130045    ES:SE:LP:AF:ID  0.010843:0.009653:0.58281:0.0130045:rs146709693
1   774760  rs187867912 C   T   .   PASS    AF=0.013254 ES:SE:LP:AF:ID  -0.0095422:0.0070167:0.75981:0.013254:rs187867912
1   775125  rs147281566 C   T   .   PASS    AF=0.0125772    ES:SE:LP:AF:ID  0.0013184:0.0094194:0.051251:0.0125772:rs147281566
1   777122  rs2980319   A   T   .   PASS    AF=0.870771 ES:SE:LP:AF:ID  -0.00029735:0.0019219:0.05698:0.870771:rs2980319
1   777232  rs112618790 C   T   .   PASS    AF=0.0950482    ES:SE:LP:AF:ID  -0.0013513:0.0022223:0.26507:0.0950482:rs112618790
1   778745  rs1055606   A   G   .   PASS    AF=0.12803  ES:SE:LP:AF:ID  0.00045821:0.0019296:0.090283:0.12803:rs1055606
1   779322  rs4040617   A   G   .   PASS    AF=0.12825  ES:SE:LP:AF:ID  0.0005648:0.0019266:0.11385:0.12825:rs4040617
1   780785  rs2977612   T   A   .   PASS    AF=0.86978  ES:SE:LP:AF:ID  -0.0003291:0.0019176:0.063619:0.86978:rs2977612
1   781845  rs61768199  A   G   .   PASS    AF=0.102639 ES:SE:LP:AF:ID  2.0738e-05:0.002161:0.0033381:0.102639:rs61768199