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": "2019-10-26T21:54:59.974081",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006367/EBI-a-GCST006367_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-GCST006367/EBI-a-GCST006367.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006367/EBI-a-GCST006367_data.vcf.gz; Date=Sat Oct 26 22:08:29 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006367/ebi-a-GCST006367.vcf.gz; Date=Sun May 10 12:40:15 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-GCST006367/EBI-a-GCST006367.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-GCST006367/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 22:31:41 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006367/EBI-a-GCST006367.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 22:32:22 2019
Total time elapsed: 41.63sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9431,
"inflation_factor": 1.0345,
"mean_EFFECT": -0.0027,
"n": "-Inf",
"n_snps": 6377725,
"n_clumped_hits": 15,
"n_p_sig": 237,
"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": 91914,
"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 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 | 6364650 | 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 | 6364653 | 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 | 8.575533e+00 | 5.710937e+00 | 1.0000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.913399e+07 | 5.626689e+07 | 828.0000 | 3.266566e+07 | 6.984954e+07 | 1.148250e+08 | 2.492165e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -2.712200e-03 | 1.132078e+00 | -22.2544 | -5.377000e-01 | -6.000000e-04 | 5.333000e-01 | 1.963600e+01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 9.406358e-01 | 6.191833e-01 | 0.5053 | 5.787000e-01 | 7.054000e-01 | 1.026400e+00 | 7.377900e+00 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.945975e-01 | 2.895922e-01 | 0.0000 | 2.426001e-01 | 4.927005e-01 | 7.449000e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.945975e-01 | 2.895921e-01 | 0.0000 | 2.425623e-01 | 4.927446e-01 | 7.449423e-01 | 9.999741e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.119126e-01 | 2.471682e-01 | 0.0101 | 1.051000e-01 | 2.416000e-01 | 4.758000e-01 | 9.897000e-01 | ▇▅▃▂▁ |
| numeric | AF_reference | 91914 | 0.9855587 | NA | NA | NA | NA | NA | NA | NA | 2.960135e-01 | 2.436918e-01 | 0.0000 | 9.604630e-02 | 2.262380e-01 | 4.536740e-01 | 1.000000e+00 | ▇▅▂▂▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 751756 | rs143225517 | T | C | 0.8556 | 0.8916 | 0.3372003 | 0.3372449 | 0.1390 | 0.242212 | NA |
| 1 | 752566 | rs3094315 | G | A | -0.7512 | 0.7645 | 0.3257999 | 0.3258029 | 0.8413 | 0.718251 | NA |
| 1 | 752894 | rs3131971 | T | C | -0.8819 | 0.9030 | 0.3287002 | 0.3287507 | 0.8308 | 0.753195 | NA |
| 1 | 753405 | rs3115860 | C | A | -0.8398 | 0.8600 | 0.3288001 | 0.3288110 | 0.8422 | 0.751797 | NA |
| 1 | 754503 | rs3115859 | G | A | -1.5520 | 1.1846 | 0.1900999 | 0.1901462 | 0.7306 | 0.663938 | NA |
| 1 | 755775 | rs3131965 | A | G | -1.0044 | 0.9226 | 0.2763001 | 0.2763028 | 0.7998 | NA | NA |
| 1 | 755890 | rs3115858 | A | T | -0.9069 | 0.9030 | 0.3151998 | 0.3152249 | 0.8549 | 0.751398 | NA |
| 1 | 756604 | rs3131962 | A | G | -1.3622 | 1.1043 | 0.2174002 | 0.2173738 | 0.8694 | 0.748003 | NA |
| 1 | 757734 | rs4951929 | C | T | -0.9298 | 0.9117 | 0.3078003 | 0.3077982 | 0.8636 | 0.748203 | NA |
| 1 | 757936 | rs4951862 | C | A | -0.9318 | 0.9109 | 0.3063000 | 0.3063342 | 0.8633 | 0.748802 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51165390 | rs76268556 | C | T | -1.2274 | 0.9408 | 0.1919999 | 0.1920174 | 0.1308 | 0.0515176 | NA |
| 22 | 51165664 | rs8137951 | G | A | 0.3772 | 0.5473 | 0.4906999 | 0.4906965 | 0.4745 | 0.4063500 | NA |
| 22 | 51169045 | rs8140772 | C | T | -1.1411 | 0.8211 | 0.1647002 | 0.1646136 | 0.1484 | 0.0632987 | NA |
| 22 | 51171497 | rs2301584 | G | A | 0.7068 | 0.8542 | 0.4079998 | 0.4079872 | 0.2340 | 0.2533950 | NA |
| 22 | 51171667 | rs41281537 | G | A | -1.1119 | 0.8004 | 0.1647999 | 0.1647779 | 0.1504 | 0.0577077 | NA |
| 22 | 51171693 | rs756638 | G | A | -0.9562 | 0.6094 | 0.1166001 | 0.1166283 | 0.2466 | 0.3049120 | NA |
| 22 | 51172460 | rs5770824 | T | C | -1.2962 | 0.8079 | 0.1086000 | 0.1086245 | 0.1587 | 0.0684904 | NA |
| 22 | 51175626 | rs3810648 | A | G | 0.3058 | 1.0487 | 0.7706000 | 0.7705931 | 0.0720 | 0.1084270 | NA |
| 22 | 51178090 | rs2285395 | G | A | -0.2583 | 1.0563 | 0.8068000 | 0.8068182 | 0.0718 | 0.0666933 | NA |
| 22 | 51178607 | rs6010067 | G | C | -1.9723 | 1.0673 | 0.0646100 | 0.0646119 | 0.1882 | 0.0814696 | NA |
bcf preview
1 751756 rs28527770 T C . PASS AF=0.139 ES:SE:LP:AF:ID 0.8556:0.8916:0.472112:0.139:rs28527770
1 752566 rs3094315 G A . PASS AF=0.8413 ES:SE:LP:AF:ID -0.7512:0.7645:0.487049:0.8413:rs3094315
1 752894 rs3131971 T C . PASS AF=0.8308 ES:SE:LP:AF:ID -0.8819:0.903:0.4832:0.8308:rs3131971
1 753405 rs3115860 C A . PASS AF=0.8422 ES:SE:LP:AF:ID -0.8398:0.86:0.483068:0.8422:rs3115860
1 754503 rs3115859 G A . PASS AF=0.7306 ES:SE:LP:AF:ID -1.552:1.1846:0.721018:0.7306:rs3115859
1 755775 rs3131965 A G . PASS AF=0.7998 ES:SE:LP:AF:ID -1.0044:0.9226:0.558619:0.7998:rs3131965
1 755890 rs3115858 A T . PASS AF=0.8549 ES:SE:LP:AF:ID -0.9069:0.903:0.501414:0.8549:rs3115858
1 756604 rs3131962 A G . PASS AF=0.8694 ES:SE:LP:AF:ID -1.3622:1.1043:0.66274:0.8694:rs3131962
1 757734 rs4951929 C T . PASS AF=0.8636 ES:SE:LP:AF:ID -0.9298:0.9117:0.511731:0.8636:rs4951929
1 757936 rs4951862 C A . PASS AF=0.8633 ES:SE:LP:AF:ID -0.9318:0.9109:0.513853:0.8633:rs4951862
1 758144 rs3131956 A G . PASS AF=0.8573 ES:SE:LP:AF:ID -0.9049:0.8815:0.51627:0.8573:rs3131956
1 758626 rs3131954 C T . PASS AF=0.8626 ES:SE:LP:AF:ID -0.9459:0.9224:0.515415:0.8626:rs3131954
1 759700 rs3115852 T C . PASS AF=0.8489 ES:SE:LP:AF:ID -1.5435:1.1664:0.731188:0.8489:rs3115852
1 759837 rs3115851 T A . PASS AF=0.8977 ES:SE:LP:AF:ID -1.4021:1.1096:0.68529:0.8977:rs3115851
1 760912 rs1048488 C T . PASS AF=0.8812 ES:SE:LP:AF:ID -1.4615:1.1036:0.73189:0.8812:rs1048488
1 761147 rs3115850 T C . PASS AF=0.9056 ES:SE:LP:AF:ID -1.6496:1.1478:0.822175:0.9056:rs3115850
1 761752 rs1057213 C T . PASS AF=0.8795 ES:SE:LP:AF:ID -1.6165:1.209:0.741842:0.8795:rs1057213
1 768448 rs12562034 G A . PASS AF=0.3383 ES:SE:LP:AF:ID 1.1069:0.8705:0.691222:0.3383:rs12562034
1 769963 rs7518545 G A . PASS AF=0.3185 ES:SE:LP:AF:ID 0.5778:0.8859:0.288783:0.3185:rs7518545
1 846078 rs28612348 C T . PASS AF=0.1429 ES:SE:LP:AF:ID 0.3331:1.141:0.11334:0.1429:rs28612348
1 846808 rs4475691 C T . PASS AF=0.1774 ES:SE:LP:AF:ID -0.4814:0.7251:0.295163:0.1774:rs4475691
1 846864 rs950122 G C . PASS AF=0.1686 ES:SE:LP:AF:ID -0.4442:0.8649:0.216382:0.1686:rs950122
1 847228 rs3905286 C T . PASS AF=0.1993 ES:SE:LP:AF:ID 0.3271:0.9882:0.130416:0.1993:rs3905286
1 847491 rs28407778 G A . PASS AF=0.2069 ES:SE:LP:AF:ID 0.3289:0.9807:0.132356:0.2069:rs28407778
1 888659 rs3748597 T C . PASS AF=0.9159 ES:SE:LP:AF:ID 1.6454:2.5164:0.289713:0.9159:rs3748597
1 900205 rs4970436 T C . PASS AF=0.2058 ES:SE:LP:AF:ID -0.2926:0.8553:0.135311:0.2058:rs4970436
1 900505 rs28705211 G C . PASS AF=0.203 ES:SE:LP:AF:ID -0.4637:0.7734:0.260586:0.203:rs28705211
1 913889 rs2340596 G A . PASS AF=0.6832 ES:SE:LP:AF:ID 0.4692:0.618:0.348916:0.6832:rs2340596
1 914333 rs13302979 C G . PASS AF=0.705 ES:SE:LP:AF:ID 0.568:0.6759:0.397181:0.705:rs13302979
1 914852 rs13303368 G C . PASS AF=0.6792 ES:SE:LP:AF:ID 0.4517:0.6119:0.336959:0.6792:rs13303368
1 914940 rs13303033 T C . PASS AF=0.6721 ES:SE:LP:AF:ID 0.4512:0.6069:0.339799:0.6721:rs13303033
1 916834 rs6694632 G A . PASS AF=0.7177 ES:SE:LP:AF:ID 0.5404:0.6455:0.395234:0.7177:rs6694632
1 918384 rs13303118 G T . PASS AF=0.682 ES:SE:LP:AF:ID 0.4309:0.5606:0.354479:0.682:rs13303118
1 918573 rs2341354 A G . PASS AF=0.7126 ES:SE:LP:AF:ID 0.3906:0.6533:0.259716:0.7126:rs2341354
1 920648 rs6677020 T C . PASS AF=0.9591 ES:SE:LP:AF:ID -0.9669:2.6804:0.143694:0.9591:rs6677020
1 920733 rs6677131 T C . PASS AF=0.9572 ES:SE:LP:AF:ID -0.9518:2.6545:0.142728:0.9572:rs6677131
1 921570 rs6662128 T C . PASS AF=0.9624 ES:SE:LP:AF:ID -0.1878:1.752:0.0387213:0.9624:rs6662128
1 923076 rs6605060 A G . PASS AF=0.9725 ES:SE:LP:AF:ID -0.9293:2.297:0.163803:0.9725:rs6605060
1 923459 rs9442609 A G . PASS AF=0.9652 ES:SE:LP:AF:ID -0.2242:1.7271:0.0473528:0.9652:rs9442609
1 923749 rs9442610 T C . PASS AF=0.9528 ES:SE:LP:AF:ID 0.4676:1.8936:0.0942041:0.9528:rs9442610
1 924368 rs35562283 C T . PASS AF=0.9775 ES:SE:LP:AF:ID -0.9593:2.3991:0.161655:0.9775:rs35562283
1 924629 rs28622096 A G . PASS AF=0.9659 ES:SE:LP:AF:ID -0.2355:1.7087:0.0504148:0.9659:rs28622096
1 924898 rs6665000 C A . PASS AF=0.9664 ES:SE:LP:AF:ID -0.9533:1.8083:0.223226:0.9664:rs6665000
1 925684 rs6605061 T C . PASS AF=0.9406 ES:SE:LP:AF:ID -1.1985:2.2501:0.225994:0.9406:rs6605061
1 926351 rs6671243 C T . PASS AF=0.9668 ES:SE:LP:AF:ID -0.2342:1.6953:0.0505612:0.9668:rs6671243
1 926431 rs4970403 A T . PASS AF=0.9674 ES:SE:LP:AF:ID -0.2033:1.718:0.0429677:0.9674:rs4970403
1 926621 rs4970351 A C . PASS AF=0.966 ES:SE:LP:AF:ID -0.1898:1.7204:0.0399575:0.966:rs4970351
1 927309 rs2341362 T C . PASS AF=0.968 ES:SE:LP:AF:ID -0.9242:1.8177:0.213817:0.968:rs2341362
1 928373 rs79271194 A G . PASS AF=0.9702 ES:SE:LP:AF:ID -0.1006:2.0057:0.0177288:0.9702:rs79271194
1 928578 rs28394749 G A . PASS AF=0.9682 ES:SE:LP:AF:ID -0.2233:1.6846:0.0483711:0.9682:rs28394749