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": "2019-10-26T21:49:17.901400",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006979/EBI-a-GCST006979_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-GCST006979/EBI-a-GCST006979.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006979/EBI-a-GCST006979_data.vcf.gz; Date=Sat Oct 26 22:12:11 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006979/ebi-a-GCST006979.vcf.gz; Date=Sun May 10 02:45:10 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-GCST006979/EBI-a-GCST006979.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-GCST006979/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 22:31:40 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006979/EBI-a-GCST006979.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 22:33:12 2019
Total time elapsed: 1.0m:32.04sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9571,
"inflation_factor": 1.4295,
"mean_EFFECT": 0,
"n": "-Inf",
"n_snps": 13705641,
"n_clumped_hits": 512,
"n_p_sig": 102921,
"n_mono": 0,
"n_ns": 46,
"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": 1323353,
"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 | 64 | 0 | 13673531 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 5 | 0 | 15 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 4 | 0 | 19 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 13691137 | 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 | 8.636530e+00 | 5.774686e+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 | 7.906057e+07 | 5.615464e+07 | 173.0000000 | 3.293083e+07 | 6.989370e+07 | 1.146830e+08 | 2.492330e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.350000e-05 | 2.146130e-02 | -0.5642760 | -5.834800e-03 | -3.300000e-06 | 5.843700e-03 | 4.527340e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.412520e-02 | 1.396780e-02 | 0.0018163 | 2.630200e-03 | 7.675000e-03 | 2.316680e-02 | 7.579040e-02 | ▇▂▂▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.376667e-01 | 3.066161e-01 | 0.0000000 | 1.600000e-01 | 4.199997e-01 | 6.999999e-01 | 1.000000e+00 | ▇▅▅▅▅ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.291482e-01 | 3.083848e-01 | 0.0000000 | 1.431064e-01 | 4.037189e-01 | 6.961422e-01 | 9.999996e-01 | ▇▅▅▅▅ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.412673e-01 | 2.344749e-01 | 0.0005010 | 1.907000e-03 | 1.595900e-02 | 1.764910e-01 | 9.995000e-01 | ▇▁▁▁▁ |
| numeric | AF_reference | 1323353 | 0.9033424 | NA | NA | NA | NA | NA | NA | NA | 1.571871e-01 | 2.334485e-01 | 0.0000000 | 1.797100e-03 | 3.694090e-02 | 2.208470e-01 | 1.000000e+00 | ▇▁▁▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 13169 | rs1436530583 | A | G | -0.0145119 | 0.0248848 | 0.5900000 | 0.5597834 | 0.997287 | NA | NA |
| 1 | 13178 | rs1181355646 | G | A | 0.0025553 | 0.0608671 | 0.8700001 | 0.9665132 | 0.000626 | NA | NA |
| 1 | 17661 | rs1199908028 | G | A | 0.0215497 | 0.0598973 | 0.9800000 | 0.7190135 | 0.000566 | NA | NA |
| 1 | 55326 | rs3107975 | T | C | 0.0324378 | 0.0181701 | 0.2500000 | 0.0742241 | 0.008350 | 0.0459265 | NA |
| 1 | 55351 | rs531766459 | T | A | -0.0646877 | 0.0517019 | 0.3400001 | 0.2108736 | 0.000508 | 0.0007987 | NA |
| 1 | 55389 | rs1190986229 | T | C | -0.0119578 | 0.0180115 | 0.9199999 | 0.5067556 | 0.004180 | NA | NA |
| 1 | 59036 | rs1481837182 | A | G | -0.0008116 | 0.0557375 | 0.9400001 | 0.9883818 | 0.000649 | NA | NA |
| 1 | 64904 | rs1452689085 | T | G | 0.1134560 | 0.0564493 | 0.0259998 | 0.0444445 | 0.000644 | NA | NA |
| 1 | 64908 | rs540391097 | A | G | -0.0385734 | 0.0482376 | 0.7899998 | 0.4239112 | 0.000638 | 0.0001997 | NA |
| 1 | 69618 | rs1220828488 | G | A | 0.0506224 | 0.0512339 | 0.6899999 | 0.3231210 | 0.000687 | NA | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154743324 | rs62618044 | T | C | -0.0008665 | 0.0018956 | 0.6475987 | 0.6475997 | 0.422638 | 0.1353640 | NA |
| 23 | 154788637 | rs73247699 | G | A | -0.0004690 | 0.0077948 | 0.9520229 | 0.9520230 | 0.014749 | 0.0031788 | NA |
| 23 | 154821956 | rs5940536 | G | A | -0.0019294 | 0.0049016 | 0.6938618 | 0.6938628 | 0.038389 | 0.0389404 | NA |
| 23 | 154846305 | rs5940404 | T | C | 0.0099740 | 0.0043470 | 0.0217646 | 0.0217641 | 0.049700 | 0.0286093 | NA |
| 23 | 154851523 | rs561841 | G | A | 0.0021380 | 0.0021695 | 0.3243852 | 0.3243858 | 0.751743 | 0.6376160 | NA |
| 23 | 154859910 | rs144293808 | A | C | -0.0004569 | 0.0036458 | 0.9002740 | 0.9002740 | 0.070978 | 0.0196026 | NA |
| 23 | 154865915 | rs601290 | G | A | 0.0023134 | 0.0021697 | 0.2863077 | 0.2863088 | 0.751927 | 0.6381460 | NA |
| 23 | 154899846 | rs473491 | A | G | 0.0023925 | 0.0020745 | 0.2487912 | 0.2487902 | 0.713484 | 0.5290070 | NA |
| 23 | 154900890 | rs150522543 | C | T | -0.0154038 | 0.0044631 | 0.0005579 | 0.0005578 | 0.046448 | 0.0105960 | NA |
| 23 | 154923374 | rs111332691 | T | A | 0.0003770 | 0.0045499 | 0.9339699 | 0.9339697 | 0.044516 | 0.0116556 | NA |
bcf preview
1 13169 rs1436530583 A G . PASS AF=0.997287 ES:SE:LP:AF:ID -0.0145119:0.0248848:0.229148:0.997287:rs1436530583
1 13178 rs1181355646 G A . PASS AF=0.000626 ES:SE:LP:AF:ID 0.00255531:0.0608671:0.0604807:0.000626:rs1181355646
1 17661 rs1199908028 G A . PASS AF=0.000566 ES:SE:LP:AF:ID 0.0215497:0.0598973:0.00877392:0.000566:rs1199908028
1 55326 rs3107975 T C . PASS AF=0.00835 ES:SE:LP:AF:ID 0.0324378:0.0181701:0.60206:0.00835:rs3107975
1 55351 rs531766459 T A . PASS AF=0.000508 ES:SE:LP:AF:ID -0.0646877:0.0517019:0.468521:0.000508:rs531766459
1 55389 rs1190986229 T C . PASS AF=0.00418 ES:SE:LP:AF:ID -0.0119578:0.0180115:0.0362122:0.00418:rs1190986229
1 59036 rs1481837182 A G . PASS AF=0.000649 ES:SE:LP:AF:ID -0.000811637:0.0557375:0.0268721:0.000649:rs1481837182
1 64904 rs1452689085 T G . PASS AF=0.000644 ES:SE:LP:AF:ID 0.113456:0.0564493:1.58503:0.000644:rs1452689085
1 64908 rs540391097 A G . PASS AF=0.000638 ES:SE:LP:AF:ID -0.0385734:0.0482376:0.102373:0.000638:rs540391097
1 69618 rs1220828488 G A . PASS AF=0.000687 ES:SE:LP:AF:ID 0.0506224:0.0512339:0.161151:0.000687:rs1220828488
1 70728 rs1259734071 C T . PASS AF=0.002156 ES:SE:LP:AF:ID 0.0382604:0.0325851:0.236572:0.002156:rs1259734071
1 74356 rs1374516807 T C . PASS AF=0.996708 ES:SE:LP:AF:ID 0.0444413:0.0245459:0.408935:0.996708:rs1374516807
1 76709 rs1376019375 T A . PASS AF=0.999254 ES:SE:LP:AF:ID -0.113533:0.0579697:0.958607:0.999254:rs1376019375
1 79033 rs2462495 A G . PASS AF=0.998739 ES:SE:LP:AF:ID -0.0408334:0.0417941:0.420216:0.998739:rs2462495
1 81120 rs1180184210 G C . PASS AF=0.998439 ES:SE:LP:AF:ID -0.0436694:0.0321019:0.744727:0.998439:rs1180184210
1 88166 rs1329210408 T C . PASS AF=0.997813 ES:SE:LP:AF:ID -0.0216597:0.0298656:0.366532:0.997813:rs1329210408
1 91311 rs1354585492 T C . PASS AF=0.997673 ES:SE:LP:AF:ID -0.0096961:0.0258393:0.455932:0.997673:rs1354585492
1 115967 rs1310910178 C T . PASS AF=0.002539 ES:SE:LP:AF:ID 0.0474087:0.0318486:1.05552:0.002539:rs1310910178
1 121759 rs975013924 C A . PASS AF=0.007699 ES:SE:LP:AF:ID 0.00899462:0.0127507:0.346787:0.007699:rs975013924
1 123130 rs1235743598 T C . PASS AF=0.994572 ES:SE:LP:AF:ID -0.0115286:0.0195075:0.207608:0.994572:rs1235743598
1 125590 rs1323463760 G A . PASS AF=0.999213 ES:SE:LP:AF:ID -0.000482408:0.0585467:0.0222764:0.999213:rs1323463760
1 126133 rs531293975 G T . PASS AF=0.998568 ES:SE:LP:AF:ID -0.0372818:0.0379441:0.443698:0.998568:rs531293975
1 128927 rs1180010278 A G . PASS AF=0.999431 ES:SE:LP:AF:ID 0.0011724:0.0517848:0.142668:0.999431:rs1180010278
1 157899 rs1339985321 G C . PASS AF=0.001261 ES:SE:LP:AF:ID -0.0185585:0.0420713:0.200659:0.001261:rs1339985321
1 526736 rs28863004 C G . PASS AF=0.005795 ES:SE:LP:AF:ID 0.0341271:0.0219307:1.05552:0.005795:rs28863004
1 533198 rs78497331 C T . PASS AF=0.00096 ES:SE:LP:AF:ID 0.0570928:0.0523302:0.366532:0.00096:rs78497331
1 534583 rs6683466 C G . PASS AF=0.006663 ES:SE:LP:AF:ID -0.0391271:0.020562:1.14267:0.006663:rs6683466
1 544584 rs576404767 C T . PASS AF=0.001838 ES:SE:LP:AF:ID 0.0464233:0.0298123:0.420216:0.001838:rs576404767
1 564397 rs1040654131 T C . PASS AF=0.000736 ES:SE:LP:AF:ID -0.0640538:0.051681:1.27572:0.000736:rs1040654131
1 564862 rs1988726 T C . PASS AF=0.001322 ES:SE:LP:AF:ID -0.00914868:0.044188:0.0604807:0.001322:rs1988726
1 565111 rs573042692 T C . PASS AF=0.00159 ES:SE:LP:AF:ID -0.0147923:0.0350226:-0:0.00159:rs573042692
1 565130 rs371431021 G A . PASS AF=0.004552 ES:SE:LP:AF:ID -0.0128653:0.0224764:0.39794:0.004552:rs371431021
1 565196 rs538567606 T C . PASS AF=0.002313 ES:SE:LP:AF:ID 0.0518051:0.031104:0.142668:0.002313:rs538567606
1 565205 rs201203786 G A . PASS AF=0.000633 ES:SE:LP:AF:ID 0.0479327:0.0518635:0.251812:0.000633:rs201203786
1 565282 rs567227003 A G . PASS AF=0.00055 ES:SE:LP:AF:ID -0.11654:0.0632084:1.25181:0.00055:rs567227003
1 565469 rs554127336 C T . PASS AF=0.001427 ES:SE:LP:AF:ID 0.0328468:0.0428328:0.823909:0.001427:rs554127336
1 565470 rs544876160 G A . PASS AF=0.001029 ES:SE:LP:AF:ID 0.0171773:0.036241:0.468521:0.001029:rs544876160
1 565490 rs7349153 T C . PASS AF=0.00137 ES:SE:LP:AF:ID 0.0413744:0.044333:0.537602:0.00137:rs7349153
1 566024 rs6421779 G A . PASS AF=0.001306 ES:SE:LP:AF:ID -0.00767672:0.0442919:-0:0.001306:rs6421779
1 566776 rs542499209 C G . PASS AF=0.000538 ES:SE:LP:AF:ID 0.136876:0.0583431:1.02228:0.000538:rs542499209
1 566875 rs2185539 C T . PASS AF=0.00067 ES:SE:LP:AF:ID -0.0171112:0.051732:0.154902:0.00067:rs2185539
1 566933 rs113120793 A G . PASS AF=0.001315 ES:SE:LP:AF:ID 0.00707862:0.0452301:0.136677:0.001315:rs113120793
1 567006 rs565235853 G T . PASS AF=0.003042 ES:SE:LP:AF:ID 0.0403815:0.0201212:0.69897:0.003042:rs565235853
1 567726 rs560688216 T C . PASS AF=0.000529 ES:SE:LP:AF:ID 0.029017:0.0718887:0.0655015:0.000529:rs560688216
1 567867 rs2000096 A G . PASS AF=0.002893 ES:SE:LP:AF:ID 0.0416556:0.0308178:0.958607:0.002893:rs2000096
1 568072 rs2853820 A G . PASS AF=0.001538 ES:SE:LP:AF:ID 0.0252752:0.0405781:0.619789:0.001538:rs2853820
1 569604 rs9645429 G A . PASS AF=0.001682 ES:SE:LP:AF:ID -0.0556937:0.0362161:0.823909:0.001682:rs9645429
1 570161 rs572999760 G A . PASS AF=0.001195 ES:SE:LP:AF:ID 0.0301816:0.0477755:0.346787:0.001195:rs572999760
1 570247 rs879960388 T C . PASS AF=0.000841 ES:SE:LP:AF:ID -0.0856686:0.0569653:0.508638:0.000841:rs879960388
1 592007 rs771664146 G A . PASS AF=0.000524 ES:SE:LP:AF:ID -0.0828862:0.0629348:0.744727:0.000524:rs771664146