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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"file_date": "2019-10-26T21:45:56.959482",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005902/EBI-a-GCST005902_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-GCST005902/EBI-a-GCST005902.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005902/EBI-a-GCST005902_data.vcf.gz; Date=Sat Oct 26 22:01:08 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST005902/ebi-a-GCST005902.vcf.gz; Date=Sun May 10 14:28:21 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-GCST005902/EBI-a-GCST005902.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-GCST005902/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 22:20:31 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST005902/EBI-a-GCST005902.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 22:21:21 2019
Total time elapsed: 50.05sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9407,
"inflation_factor": 1.2789,
"mean_EFFECT": 0,
"n": "-Inf",
"n_snps": 7624934,
"n_clumped_hits": 14,
"n_p_sig": 1102,
"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": 67246,
"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 | TRUE |
| 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 | 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 betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.n: Maximum value of reported sample size across all SNPs, \(n\).n_clumped_hits: Number of clumped hits.n_snps: Number of SNPsn_p_sig: Number of SNPs with pvalue below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations 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 expectratio_se_nto 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 ofdiffand the mean ofdiff2(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<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).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: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_mean_chisq< 0.7.n_p_sig:n_p_sig> 1000.miss_<*>:n_miss_<*>/n_snps> 0.01.ldsc_ratio:ldsc_ratio> 0.5ldsc_intercept_beta:ldsc_intercept_beta> 1.5n_clumped_hits:n_clumped_hits> 1000r2_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 | 7604708 | 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 | 7609162 | 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 | 8.646800e+00 | 5.756787e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.882954e+07 | 5.641675e+07 | 828.0000000 | 3.234969e+07 | 6.940890e+07 | 1.146924e+08 | 2.492235e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.790000e-05 | 2.952600e-03 | -0.0509320 | -1.481300e-03 | 1.510000e-05 | 1.507200e-03 | 3.897900e-02 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.368700e-03 | 1.348900e-03 | 0.0011425 | 1.304300e-03 | 1.780200e-03 | 3.083200e-03 | 1.811000e-02 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.604592e-01 | 2.995683e-01 | 0.0000000 | 1.908633e-01 | 4.456049e-01 | 7.201782e-01 | 9.999999e-01 | ▇▆▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.604586e-01 | 2.995686e-01 | 0.0000000 | 1.908646e-01 | 4.456076e-01 | 7.201749e-01 | 9.999999e-01 | ▇▆▆▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.524501e-01 | 2.608710e-01 | 0.0100000 | 4.043760e-02 | 1.462990e-01 | 3.990630e-01 | 9.900000e-01 | ▇▂▂▁▁ |
| numeric | AF_reference | 67246 | 0.9911625 | NA | NA | NA | NA | NA | NA | NA | 2.517593e-01 | 2.524473e-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 | -0.0075208 | 0.0057967 | 0.1944867 | 0.1944840 | 0.0213148 | 0.0005990 | NA |
| 1 | 82103 | rs2020400 | T | C | -0.0031045 | 0.0028941 | 0.2834132 | 0.2834059 | 0.9246800 | NA | NA |
| 1 | 174747 | rs1399732465 | C | T | -0.0057466 | 0.0058218 | 0.3236011 | 0.3236019 | 0.0257319 | NA | NA |
| 1 | 234313 | rs8179466 | C | T | -0.0018425 | 0.0040062 | 0.6455799 | 0.6455793 | 0.0747481 | NA | NA |
| 1 | 546697 | rs12025928 | A | G | -0.0008898 | 0.0028943 | 0.7585077 | 0.7585015 | 0.9133130 | NA | NA |
| 1 | 568800 | rs375217967 | G | A | -0.0157520 | 0.0079866 | 0.0485736 | 0.0485750 | 0.0168505 | 0.0778754 | NA |
| 1 | 705882 | rs72631875 | G | A | -0.0002131 | 0.0028592 | 0.9405784 | 0.9405793 | 0.0671098 | 0.0315495 | NA |
| 1 | 717587 | rs144155419 | G | A | 0.0003299 | 0.0052367 | 0.9497668 | 0.9497683 | 0.0157119 | 0.0045926 | NA |
| 1 | 722670 | rs116030099 | T | C | -0.0003961 | 0.0023816 | 0.8679126 | 0.8679110 | 0.1012960 | 0.0413339 | NA |
| 1 | 724849 | rs12126395 | C | A | 0.0054620 | 0.0056507 | 0.3337490 | 0.3337411 | 0.0318573 | NA | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51219006 | rs28729663 | G | A | 0.0001007 | 0.0017447 | 0.9539574 | 0.9539553 | 0.1374580 | 0.2052720 | NA |
| 22 | 51219387 | rs9616832 | T | C | -0.0002276 | 0.0022681 | 0.9200703 | 0.9200713 | 0.0733499 | 0.0654952 | NA |
| 22 | 51219704 | rs147475742 | G | A | -0.0006726 | 0.0030439 | 0.8251274 | 0.8251262 | 0.0416676 | 0.0473243 | NA |
| 22 | 51220517 | rs9616980 | C | G | -0.0006970 | 0.0068355 | 0.9187810 | 0.9187823 | 0.0100368 | 0.0027955 | NA |
| 22 | 51221190 | rs369304721 | G | A | 0.0012004 | 0.0030454 | 0.6934577 | 0.6934568 | 0.0492587 | NA | NA |
| 22 | 51221731 | rs115055839 | T | C | -0.0001324 | 0.0022692 | 0.9534677 | 0.9534691 | 0.0728602 | 0.0625000 | NA |
| 22 | 51222100 | rs114553188 | G | T | 0.0005269 | 0.0026648 | 0.8432571 | 0.8432595 | 0.0544739 | 0.0880591 | NA |
| 22 | 51229805 | rs9616985 | T | C | -0.0001541 | 0.0022775 | 0.9460607 | 0.9460618 | 0.0726718 | 0.0730831 | NA |
| 22 | 51232488 | rs376461333 | A | G | 0.0048720 | 0.0053405 | 0.3616346 | 0.3616244 | 0.0200378 | NA | NA |
| 23 | 65456737 | rs77978087 | G | C | -0.0025986 | 0.0014191 | 0.0670811 | 0.0670766 | 0.5079520 | NA | NA |
bcf preview
1 15850 rs575961614 G A . PASS AF=0.0213148 ES:SE:LP:AF:ID -0.0075208:0.0057967:0.71111:0.0213148:rs575961614
1 82103 rs2020400 T C . PASS AF=0.92468 ES:SE:LP:AF:ID -0.0031045:0.0028941:0.54758:0.92468:rs2020400
1 174747 rs1399732465 C T . PASS AF=0.0257319 ES:SE:LP:AF:ID -0.0057466:0.0058218:0.48999:0.0257319:rs1399732465
1 234313 rs8179466 C T . PASS AF=0.0747481 ES:SE:LP:AF:ID -0.0018425:0.0040062:0.19005:0.0747481:rs8179466
1 546697 rs12025928 A G . PASS AF=0.913313 ES:SE:LP:AF:ID -0.00088985:0.0028943:0.12004:0.913313:rs12025928
1 568800 rs375217967 G A . PASS AF=0.0168505 ES:SE:LP:AF:ID -0.015752:0.0079866:1.3136:0.0168505:rs375217967
1 705882 rs72631875 G A . PASS AF=0.0671098 ES:SE:LP:AF:ID -0.00021313:0.0028592:0.026605:0.0671098:rs72631875
1 717587 rs144155419 G A . PASS AF=0.0157119 ES:SE:LP:AF:ID 0.0003299:0.0052367:0.022383:0.0157119:rs144155419
1 722670 rs116030099 T C . PASS AF=0.101296 ES:SE:LP:AF:ID -0.00039609:0.0023816:0.061524:0.101296:rs116030099
1 724849 rs12126395 C A . PASS AF=0.0318573 ES:SE:LP:AF:ID 0.005462:0.0056507:0.47658:0.0318573:rs12126395
1 730087 rs148120343 T C . PASS AF=0.0565248 ES:SE:LP:AF:ID 0.0001046:0.0027177:0.013542:0.0565248:rs148120343
1 731453 rs186002080 G A . PASS AF=0.0157551 ES:SE:LP:AF:ID 0.010941:0.0061742:1.117:0.0157551:rs186002080
1 732989 rs369030935 C T . PASS AF=0.0261446 ES:SE:LP:AF:ID -0.0020532:0.0045067:0.18796:0.0261446:rs369030935
1 734349 rs141242758 T C . PASS AF=0.120977 ES:SE:LP:AF:ID -0.00032292:0.0018533:0.064656:0.120977:rs141242758
1 736689 rs181876450 T C . PASS AF=0.0110064 ES:SE:LP:AF:ID 0.00090166:0.0066623:0.049468:0.0110064:rs181876450
1 753405 rs3115860 C A . PASS AF=0.870952 ES:SE:LP:AF:ID 4.3408e-05:0.0017598:0.0086318:0.870952:rs3115860
1 753541 rs2073813 G A . PASS AF=0.128582 ES:SE:LP:AF:ID -0.00020103:0.0017634:0.041323:0.128582:rs2073813
1 754182 rs3131969 A G . PASS AF=0.87054 ES:SE:LP:AF:ID -3.8133e-05:0.0017567:0.0075873:0.87054:rs3131969
1 754192 rs3131968 A G . PASS AF=0.870647 ES:SE:LP:AF:ID -1.8716e-05:0.0017574:0.003706:0.870647:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870541 ES:SE:LP:AF:ID -3.0834e-05:0.0017567:0.0061248:0.870541:rs3131967
1 755240 rs181660517 T G . PASS AF=0.0140726 ES:SE:LP:AF:ID 0.0030039:0.0056346:0.22624:0.0140726:rs181660517
1 755890 rs3115858 A T . PASS AF=0.87061 ES:SE:LP:AF:ID 1.1018e-05:0.0017547:0.0021812:0.87061:rs3115858
1 756604 rs3131962 A G . PASS AF=0.870187 ES:SE:LP:AF:ID -7.0538e-05:0.0017506:0.014188:0.870187:rs3131962
1 757640 rs3115853 G A . PASS AF=0.86944 ES:SE:LP:AF:ID -3.3453e-05:0.0017469:0.0066864:0.86944:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870327 ES:SE:LP:AF:ID -5.6697e-05:0.0017519:0.011359:0.870327:rs4951929
1 757936 rs4951862 C A . PASS AF=0.870332 ES:SE:LP:AF:ID -5.8058e-05:0.0017521:0.011635:0.870332:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870342 ES:SE:LP:AF:ID -5.7349e-05:0.0017521:0.01149:0.870342:rs3131956
1 758626 rs3131954 C T . PASS AF=0.870792 ES:SE:LP:AF:ID -5.6844e-05:0.0017567:0.011358:0.870792:rs3131954
1 761732 rs2286139 C T . PASS AF=0.864048 ES:SE:LP:AF:ID -6.8675e-05:0.0017459:0.013845:0.864048:rs2286139
1 766007 rs61768174 A C . PASS AF=0.105407 ES:SE:LP:AF:ID -0.00027822:0.001948:0.052354:0.105407:rs61768174
1 768253 rs2977608 A C . PASS AF=0.76398 ES:SE:LP:AF:ID -0.00017444:0.0013854:0.045853:0.76398:rs2977608
1 768448 rs12562034 G A . PASS AF=0.10534 ES:SE:LP:AF:ID -6.3836e-05:0.0019147:0.011707:0.10534:rs12562034
1 769223 rs60320384 C G . PASS AF=0.128585 ES:SE:LP:AF:ID -0.00023597:0.0017624:0.048912:0.128585:rs60320384
1 769885 rs200025137 G A . PASS AF=0.0143431 ES:SE:LP:AF:ID 0.002339:0.0087854:0.10234:0.0143431:rs200025137
1 770085 rs150344285 G C . PASS AF=0.0106191 ES:SE:LP:AF:ID -0.011648:0.0082457:0.80194:0.0106191:rs150344285
1 771823 rs2977605 T C . PASS AF=0.870164 ES:SE:LP:AF:ID -0.00010899:0.0017535:0.022075:0.870164:rs2977605
1 771967 rs59066358 G A . PASS AF=0.128645 ES:SE:LP:AF:ID -0.00016456:0.0017613:0.033594:0.128645:rs59066358
1 772755 rs2905039 A C . PASS AF=0.870174 ES:SE:LP:AF:ID -0.00012503:0.0017536:0.025415:0.870174:rs2905039
1 772927 rs116390263 C T . PASS AF=0.0165659 ES:SE:LP:AF:ID 0.021848:0.0078717:2.2588:0.0165659:rs116390263
1 773124 rs142049927 T C . PASS AF=0.0127515 ES:SE:LP:AF:ID 0.021783:0.0089302:1.8322:0.0127515:rs142049927
1 773136 rs146709693 G T . PASS AF=0.0129392 ES:SE:LP:AF:ID 0.023:0.0088581:2.026:0.0129392:rs146709693
1 774760 rs187867912 C T . PASS AF=0.0133135 ES:SE:LP:AF:ID -0.0063757:0.006392:0.49683:0.0133135:rs187867912
1 775125 rs147281566 C T . PASS AF=0.0125009 ES:SE:LP:AF:ID 0.019231:0.0086377:1.5852:0.0125009:rs147281566
1 777122 rs2980319 A T . PASS AF=0.871197 ES:SE:LP:AF:ID 0.00020071:0.0017566:0.041421:0.871197:rs2980319
1 777232 rs112618790 C T . PASS AF=0.0951252 ES:SE:LP:AF:ID -0.00045795:0.0020291:0.085423:0.0951252:rs112618790
1 778745 rs1055606 A G . PASS AF=0.127631 ES:SE:LP:AF:ID -0.00048398:0.0017632:0.10584:0.127631:rs1055606
1 779322 rs4040617 A G . PASS AF=0.127863 ES:SE:LP:AF:ID -0.00053749:0.0017604:0.11912:0.127863:rs4040617
1 780785 rs2977612 T A . PASS AF=0.870245 ES:SE:LP:AF:ID -1.3635e-05:0.0017525:0.0027044:0.870245:rs2977612
1 781845 rs61768199 A G . PASS AF=0.102359 ES:SE:LP:AF:ID -0.00052102:0.0019737:0.10139:0.102359:rs61768199
1 782721 rs185280546 G A . PASS AF=0.0146613 ES:SE:LP:AF:ID 0.00025716:0.0053439:0.016997:0.0146613:rs185280546