Summary

Summary {data-width=650}

Manhattan plot

manhattan_plot

QQ plot

qq_plot

AF plot

af_plot

P-Z plot

pz_plot

beta_std plot

beta_std_plot

Metadata

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    "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\">",
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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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    "file_date": "2019-10-26T21:56:20.534265",
    "gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006944/EBI-a-GCST006944_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-GCST006944/EBI-a-GCST006944.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006944/EBI-a-GCST006944_data.vcf.gz; Date=Sat Oct 26 22:17:38 2019",
    "bcftools_viewVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
    "bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006944/ebi-a-GCST006944.vcf.gz; Date=Thu May  7 22:29:09 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-GCST006944/EBI-a-GCST006944.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-GCST006944/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 22:42:12 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006944/EBI-a-GCST006944.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 22:43:25 2019
Total time elapsed: 1.0m:13.38s

QC metrics

Metrics

Metrics

{
    "af_correlation": 0.9589,
    "inflation_factor": 1.2302,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 10824841,
    "n_clumped_hits": 40,
    "n_p_sig": 4001,
    "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": 0,
    "n_miss_AF_reference": 429023,
    "n_est": "NA",
    "ratio_se_n": "NA",
    "mean_diff": "NaN",
    "ratio_diff": "NaN",
    "sd_y_est1": "NA",
    "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 TRUE
n TRUE
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 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 47 0 10809171 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 10809172 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 8.526216e+00 5.701019e+00 1.0000000 4.000000e+00 7.000000e+00 1.200000e+01 2.200000e+01 <U+2587><U+2585><U+2583><U+2582><U+2582>
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 7.942131e+07 5.593410e+07 828.0000000 3.358260e+07 7.035950e+07 1.147901e+08 2.492251e+08 <U+2587><U+2587><U+2585><U+2582><U+2581>
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 8.740000e-05 2.006050e-02 -0.4260820 -4.406700e-03 3.740000e-05 4.451900e-03 3.959430e-01 <U+2581><U+2581><U+2587><U+2581><U+2581>
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 1.244200e-02 1.555510e-02 0.0023146 2.891600e-03 5.662500e-03 1.601030e-02 1.223970e-01 <U+2587><U+2581><U+2581><U+2581><U+2581>
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.659098e-01 2.983834e-01 0.0000000 1.989001e-01 4.543997e-01 7.246996e-01 9.996000e-01 <U+2587><U+2586><U+2586><U+2586><U+2586>
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.659097e-01 2.983834e-01 0.0000000 1.987930e-01 4.544599e-01 7.248380e-01 9.992021e-01 <U+2587><U+2586><U+2586><U+2586><U+2586>
numeric AF 0 1.0000000 NA NA NA NA NA NA NA 1.801831e-01 2.533991e-01 0.0000894 5.471400e-03 4.879270e-02 2.651640e-01 9.998900e-01 <U+2587><U+2582><U+2581><U+2581><U+2581>
numeric AF_reference 429023 0.9603094 NA NA NA NA NA NA NA 1.908452e-01 2.453537e-01 0.0000000 1.337860e-02 7.488020e-02 2.825480e-01 1.000000e+00 <U+2587><U+2582><U+2581><U+2581><U+2581>

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 715265 rs12184267 C T 0.0086160 0.0062031 0.1650000 0.1648328 0.0366377 0.0275559 NA
1 715367 rs12184277 A G 0.0069319 0.0061892 0.2627000 0.2627133 0.0367695 0.0281550 NA
1 717485 rs12184279 C A 0.0093084 0.0062139 0.1342001 0.1341331 0.0364631 NA NA
1 720381 rs116801199 G T 0.0064816 0.0061553 0.2923001 0.2923412 0.0371104 0.0359425 NA
1 721290 rs12565286 G C 0.0074772 0.0061490 0.2240000 0.2239848 0.0372080 0.0371406 NA
1 723891 rs2977670 G C -0.0041547 0.0053678 0.4389004 0.4389306 0.9503520 0.7799520 NA
1 726794 rs28454925 C G 0.0069244 0.0061936 0.2638001 0.2635666 0.0366130 0.0279553 NA
1 729632 rs116720794 C T 0.0075004 0.0061681 0.2241001 0.2239850 0.0368931 0.0099840 NA
1 729679 rs4951859 C G 0.0017278 0.0031529 0.5840002 0.5836905 0.8316140 0.6399760 NA
1 752478 rs146277091 G A 0.0063380 0.0061654 0.3040997 0.3039500 0.0367696 0.0277556 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
22 51219387 rs9616832 T C -0.0010677 0.0044303 0.8094000 0.8095546 0.0737920 0.0654952 NA
22 51219704 rs147475742 G A 0.0043589 0.0057887 0.4514005 0.4514500 0.0427541 0.0473243 NA
22 51219766 rs182321900 C T -0.0129181 0.0202796 0.5244004 0.5241250 0.0032748 NA NA
22 51220025 rs148808236 G A -0.0101090 0.0277720 0.7158005 0.7158582 0.0017399 0.0215655 NA
22 51221731 rs115055839 T C -0.0010311 0.0044444 0.8162000 0.8165383 0.0732027 0.0625000 NA
22 51222100 rs114553188 G T 0.0035549 0.0050424 0.4807995 0.4808101 0.0568181 0.0880591 NA
22 51223637 rs375798137 G A 0.0035840 0.0050837 0.4809002 0.4808096 0.0558736 0.0788738 NA
22 51224208 rs116656403 G A -0.0299873 0.0276891 0.2789003 0.2788083 0.0017501 0.0209665 NA
22 51224267 rs138354270 G A -0.0112004 0.0277926 0.6871998 0.6869487 0.0017376 0.0209665 NA
22 51229805 rs9616985 T C -0.0001598 0.0044384 0.9709000 0.9712824 0.0735865 0.0730831 NA

bcf preview

1   715265  rs12184267  C   T   .   PASS    AF=0.0366377    ES:SE:LP:AF:ID  0.00861605:0.00620306:0.782516:0.0366377:rs12184267
1   715367  rs12184277  A   G   .   PASS    AF=0.0367695    ES:SE:LP:AF:ID  0.0069319:0.00618919:0.58054:0.0367695:rs12184277
1   717485  rs12184279  C   A   .   PASS    AF=0.0364631    ES:SE:LP:AF:ID  0.00930841:0.00621389:0.872247:0.0364631:rs12184279
1   720381  rs116801199 G   T   .   PASS    AF=0.0371104    ES:SE:LP:AF:ID  0.00648157:0.00615534:0.534171:0.0371104:rs116801199
1   721290  rs12565286  G   C   .   PASS    AF=0.037208 ES:SE:LP:AF:ID  0.00747721:0.00614902:0.649752:0.037208:rs12565286
1   723891  rs2977670   G   C   .   PASS    AF=0.950352 ES:SE:LP:AF:ID  -0.00415471:0.00536784:0.357634:0.950352:rs2977670
1   726794  rs28454925  C   G   .   PASS    AF=0.036613 ES:SE:LP:AF:ID  0.00692444:0.00619359:0.578725:0.036613:rs28454925
1   729632  rs116720794 C   T   .   PASS    AF=0.0368931    ES:SE:LP:AF:ID  0.00750036:0.00616806:0.649558:0.0368931:rs116720794
1   729679  rs4951859   C   G   .   PASS    AF=0.831614 ES:SE:LP:AF:ID  0.00172779:0.00315289:0.233587:0.831614:rs4951859
1   752478  rs146277091 G   A   .   PASS    AF=0.0367696    ES:SE:LP:AF:ID  0.00633805:0.00616542:0.516984:0.0367696:rs146277091
1   752566  rs3094315   G   A   .   PASS    AF=0.829189 ES:SE:LP:AF:ID  -0.000415707:0.00307931:0.0495378:0.829189:rs3094315
1   752721  rs3131972   A   G   .   PASS    AF=0.826243 ES:SE:LP:AF:ID  -9.16332e-05:0.00305444:0.0106392:0.826243:rs3131972
1   753405  rs3115860   C   A   .   PASS    AF=0.860653 ES:SE:LP:AF:ID  0.00109974:0.00335286:0.128894:0.860653:rs3115860
1   753541  rs2073813   G   A   .   PASS    AF=0.140455 ES:SE:LP:AF:ID  -0.00183938:0.00334432:0.235002:0.140455:rs2073813
1   754063  rs12184312  G   T   .   PASS    AF=0.0371833    ES:SE:LP:AF:ID  0.00483473:0.00611992:0.366936:0.0371833:rs12184312
1   754105  rs12184325  C   T   .   PASS    AF=0.0374306    ES:SE:LP:AF:ID  0.00574351:0.00609715:0.460673:0.0374306:rs12184325
1   754182  rs3131969   A   G   .   PASS    AF=0.857265 ES:SE:LP:AF:ID  0.00147427:0.00332043:0.182567:0.857265:rs3131969
1   754192  rs3131968   A   G   .   PASS    AF=0.857357 ES:SE:LP:AF:ID  0.00159431:0.00332148:0.199764:0.857357:rs3131968
1   754211  rs12184313  G   A   .   PASS    AF=0.0374202    ES:SE:LP:AF:ID  0.00609806:0.00610417:0.497983:0.0374202:rs12184313
1   754334  rs3131967   T   C   .   PASS    AF=0.857369 ES:SE:LP:AF:ID  0.00149139:0.00332157:0.184954:0.857369:rs3131967
1   754503  rs3115859   G   A   .   PASS    AF=0.826634 ES:SE:LP:AF:ID  -0.00046625:0.00306743:0.0558629:0.826634:rs3115859
1   754629  rs10454459  A   G   .   PASS    AF=0.0374193    ES:SE:LP:AF:ID  0.00685756:0.00610647:0.582694:0.0374193:rs10454459
1   754964  rs3131966   C   T   .   PASS    AF=0.827271 ES:SE:LP:AF:ID  -0.000439706:0.00307487:0.0522723:0.827271:rs3131966
1   755775  rs3131965   A   G   .   PASS    AF=0.831031 ES:SE:LP:AF:ID  -0.000460809:0.00315623:0.0535969:0.831031:rs3131965
1   755890  rs3115858   A   T   .   PASS    AF=0.860232 ES:SE:LP:AF:ID  0.000988883:0.00334082:0.114978:0.860232:rs3115858
1   756604  rs3131962   A   G   .   PASS    AF=0.85979  ES:SE:LP:AF:ID  0.00057999:0.00333327:0.0646439:0.85979:rs3131962
1   757640  rs3115853   G   A   .   PASS    AF=0.854521 ES:SE:LP:AF:ID  0.00111709:0.00328556:0.134481:0.854521:rs3115853
1   757734  rs4951929   C   T   .   PASS    AF=0.859889 ES:SE:LP:AF:ID  0.000703756:0.00333534:0.079355:0.859889:rs4951929
1   757936  rs4951862   C   A   .   PASS    AF=0.859935 ES:SE:LP:AF:ID  0.000717206:0.00333584:0.0810789:0.859935:rs4951862
1   758144  rs3131956   A   G   .   PASS    AF=0.859942 ES:SE:LP:AF:ID  0.000720559:0.00333592:0.0813931:0.859942:rs3131956
1   758626  rs3131954   C   T   .   PASS    AF=0.860464 ES:SE:LP:AF:ID  7.02276e-05:0.00334417:0.00735813:0.860464:rs3131954
1   759036  rs114525117 G   A   .   PASS    AF=0.0374737    ES:SE:LP:AF:ID  0.00576471:0.00609378:0.463315:0.0374737:rs114525117
1   760912  rs1048488   C   T   .   PASS    AF=0.82959  ES:SE:LP:AF:ID  -0.00102907:0.0030903:0.131238:0.82959:rs1048488
1   760998  rs148828841 C   A   .   PASS    AF=0.0369479    ES:SE:LP:AF:ID  0.00615392:0.00614777:0.499215:0.0369479:rs148828841
1   761147  rs3115850   T   C   .   PASS    AF=0.829712 ES:SE:LP:AF:ID  -0.0010759:0.00309168:0.138167:0.829712:rs3115850
1   761606  rs377377186 G   A   .   PASS    AF=0.0358125    ES:SE:LP:AF:ID  0.00473773:0.00626684:0.346981:0.0358125:rs377377186
1   761732  rs2286139   C   T   .   PASS    AF=0.848492 ES:SE:LP:AF:ID  0.00168438:0.0033027:0.214457:0.848492:rs2286139
1   761881  rs374493323 A   C   .   PASS    AF=0.0342849    ES:SE:LP:AF:ID  0.00556527:0.00641899:0.41375:0.0342849:rs374493323
1   766007  rs61768174  A   C   .   PASS    AF=0.105478 ES:SE:LP:AF:ID  -0.00168683:0.00381636:0.181576:0.105478:rs61768174
1   767096  rs115991721 A   G   .   PASS    AF=0.00259125   ES:SE:LP:AF:ID  0.0192591:0.0227649:0.400335:0.00259125:rs115991721
1   768253  rs2977608   A   C   .   PASS    AF=0.744125 ES:SE:LP:AF:ID  -0.000903947:0.00265867:0.134481:0.744125:rs2977608
1   768448  rs12562034  G   A   .   PASS    AF=0.111263 ES:SE:LP:AF:ID  0.00248059:0.00368039:0.300856:0.111263:rs12562034
1   768680  rs140605359 C   T   .   PASS    AF=0.00057169   ES:SE:LP:AF:ID  -0.0125423:0.0484258:0.0992506:0.00057169:rs140605359
1   768819  rs12562811  C   T   .   PASS    AF=0.0121867    ES:SE:LP:AF:ID  0.0046694:0.0105882:0.180917:0.0121867:rs12562811
1   769223  rs60320384  C   G   .   PASS    AF=0.135131 ES:SE:LP:AF:ID  -0.00107143:0.0033906:0.123898:0.135131:rs60320384
1   770504  rs150664068 C   G   .   PASS    AF=0.000562164  ES:SE:LP:AF:ID  -0.017141:0.0488348:0.139363:0.000562164:rs150664068
1   771823  rs2977605   T   C   .   PASS    AF=0.859693 ES:SE:LP:AF:ID  0.000580625:0.00333692:0.064392:0.859693:rs2977605
1   771967  rs59066358  G   A   .   PASS    AF=0.136281 ES:SE:LP:AF:ID  -0.000949354:0.00337849:0.10863:0.136281:rs59066358
1   772755  rs2905039   A   C   .   PASS    AF=0.859685 ES:SE:LP:AF:ID  0.000523892:0.00333689:0.0578431:0.859685:rs2905039
1   776556  rs151160018 C   T   .   PASS    AF=0.00833475   ES:SE:LP:AF:ID  0.00791478:0.0127452:0.272134:0.00833475:rs151160018