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": "2019-10-26T21:41:44.193552",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006867/EBI-a-GCST006867_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-GCST006867/EBI-a-GCST006867.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006867/EBI-a-GCST006867_data.vcf.gz; Date=Sat Oct 26 21:54:26 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006867/ebi-a-GCST006867.vcf.gz; Date=Sun May 10 10:12:34 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-GCST006867/EBI-a-GCST006867.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-GCST006867/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 22:18:11 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006867/EBI-a-GCST006867.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 22:18:44 2019
Total time elapsed: 33.21sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9274,
"inflation_factor": 1.416,
"mean_EFFECT": 0.0003,
"n": "-Inf",
"n_snps": 5030727,
"n_clumped_hits": 118,
"n_p_sig": 5967,
"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": 24749,
"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 | 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 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 | 1.000000 | 3 | 35 | 0 | 5021057 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 5021057 | 0.000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 8.410593e+00 | 5.606336e+00 | 1.0000e+00 | 4.000000e+00 | 7.000000e+00 | 1.200000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 7.964176e+07 | 5.551137e+07 | 1.1336e+04 | 3.391265e+07 | 7.087940e+07 | 1.145370e+08 | 2.491746e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 2.629000e-04 | 1.589620e-02 | -1.5690e-01 | -8.700000e-03 | 2.000000e-04 | 9.000000e-03 | 3.059000e-01 | ▁▇▁▁▁ |
| numeric | SE | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 1.221080e-02 | 5.470800e-03 | 3.6000e-03 | 8.300000e-03 | 1.000000e-02 | 1.400000e-02 | 4.170000e-02 | ▇▃▁▁▁ |
| numeric | PVAL | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 4.422006e-01 | 3.021671e-01 | 0.0000e+00 | 1.661001e-01 | 4.221998e-01 | 7.032002e-01 | 9.988000e-01 | ▇▆▅▅▅ |
| numeric | PVAL_ztest | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 4.421961e-01 | 3.021625e-01 | 0.0000e+00 | 1.661701e-01 | 4.223244e-01 | 7.032386e-01 | 9.979003e-01 | ▇▆▅▅▅ |
| numeric | AF | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 3.112576e-01 | 2.593001e-01 | 1.0039e-02 | 9.290940e-02 | 2.303260e-01 | 4.820870e-01 | 9.899500e-01 | ▇▃▂▂▁ |
| numeric | AF_reference | 24749 | 0.995071 | NA | NA | NA | NA | NA | NA | NA | 3.121136e-01 | 2.466831e-01 | 5.9900e-04 | 1.092250e-01 | 2.398160e-01 | 4.718450e-01 | 9.988020e-01 | ▇▅▃▂▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 785050 | rs2905062 | G | A | -0.0082 | 0.0116 | 0.4790998 | 0.4796308 | 0.8680250 | 0.626997 | NA |
| 1 | 1087683 | rs9442380 | T | C | -0.0016 | 0.0161 | 0.9213001 | 0.9208374 | 0.9351570 | 0.839058 | NA |
| 1 | 1090010 | rs9442361 | C | A | -0.0061 | 0.0157 | 0.6950003 | 0.6976201 | 0.9329430 | 0.824281 | NA |
| 1 | 1092599 | rs56863140 | G | C | -0.0046 | 0.0156 | 0.7664997 | 0.7680918 | 0.9328520 | 0.831270 | NA |
| 1 | 1096908 | rs1539636 | T | C | -0.0069 | 0.0155 | 0.6549995 | 0.6562032 | 0.9317060 | 0.816294 | NA |
| 1 | 1097100 | rs1539634 | C | T | -0.0078 | 0.0156 | 0.6186001 | 0.6170751 | 0.9328110 | 0.814097 | NA |
| 1 | 1097287 | rs9442384 | T | C | -0.0069 | 0.0156 | 0.6612002 | 0.6582666 | 0.9330790 | 0.818490 | NA |
| 1 | 1122539 | rs12063897 | A | G | 0.0303 | 0.0139 | 0.0290797 | 0.0292681 | 0.0915407 | 0.107029 | NA |
| 1 | 1122916 | rs28460227 | A | G | 0.0297 | 0.0139 | 0.0323601 | 0.0326232 | 0.0913276 | 0.103435 | NA |
| 1 | 1122937 | rs28648687 | G | A | 0.0297 | 0.0139 | 0.0322099 | 0.0326232 | 0.0914160 | 0.103435 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51140316 | rs739365 | C | T | 0.0067 | 0.0084 | 0.4208003 | 0.4250916 | 0.3055250 | 0.4363020 | NA |
| 22 | 51145136 | rs73174415 | C | T | 0.0169 | 0.0155 | 0.2765999 | 0.2755711 | 0.0703008 | 0.0425319 | NA |
| 22 | 51145746 | rs142356721 | C | T | 0.0163 | 0.0155 | 0.2942998 | 0.2929772 | 0.0701431 | 0.0425319 | NA |
| 22 | 51146439 | rs6010060 | A | G | 0.0174 | 0.0156 | 0.2664999 | 0.2646856 | 0.0706151 | 0.0551118 | NA |
| 22 | 51148995 | rs9616946 | G | A | 0.0166 | 0.0093 | 0.0731594 | 0.0742700 | 0.2301380 | 0.2408150 | NA |
| 22 | 51150473 | rs5770820 | G | A | 0.0156 | 0.0092 | 0.0882897 | 0.0899518 | 0.2307600 | 0.2462060 | NA |
| 22 | 51175626 | rs3810648 | A | G | 0.0108 | 0.0165 | 0.5116005 | 0.5127605 | 0.0608362 | 0.1084270 | NA |
| 22 | 51178090 | rs2285395 | G | A | -0.0038 | 0.0161 | 0.8129000 | 0.8134134 | 0.0527946 | 0.0666933 | NA |
| 22 | 51196164 | rs8136603 | A | T | -0.0095 | 0.0176 | 0.5892004 | 0.5893538 | 0.0519345 | 0.1427720 | NA |
| 22 | 51197602 | rs187225588 | T | A | -0.0063 | 0.0181 | 0.7265006 | 0.7277904 | 0.0504618 | 0.0175719 | NA |
bcf preview
1 785050 rs2905062 G A . PASS AF=0.868025 ES:SE:LP:AF:ID -0.0082:0.0116:0.319574:0.868025:rs2905062
1 1087683 rs9442380 T C . PASS AF=0.935157 ES:SE:LP:AF:ID -0.0016:0.0161:0.0355989:0.935157:rs9442380
1 1090010 rs9442361 C A . PASS AF=0.932943 ES:SE:LP:AF:ID -0.0061:0.0157:0.158015:0.932943:rs9442361
1 1092599 rs56863140 G C . PASS AF=0.932852 ES:SE:LP:AF:ID -0.0046:0.0156:0.115488:0.932852:rs56863140
1 1096908 rs1539636 T C . PASS AF=0.931706 ES:SE:LP:AF:ID -0.0069:0.0155:0.183759:0.931706:rs1539636
1 1097100 rs1539634 C T . PASS AF=0.932811 ES:SE:LP:AF:ID -0.0078:0.0156:0.20859:0.932811:rs1539634
1 1097287 rs9442384 T C . PASS AF=0.933079 ES:SE:LP:AF:ID -0.0069:0.0156:0.179667:0.933079:rs9442384
1 1122539 rs12063897 A G . PASS AF=0.0915407 ES:SE:LP:AF:ID 0.0303:0.0139:1.53641:0.0915407:rs12063897
1 1122916 rs28460227 A G . PASS AF=0.0913276 ES:SE:LP:AF:ID 0.0297:0.0139:1.48999:0.0913276:rs28460227
1 1122937 rs28648687 G A . PASS AF=0.091416 ES:SE:LP:AF:ID 0.0297:0.0139:1.49201:0.091416:rs28648687
1 1124819 rs6694487 C T . PASS AF=0.0916791 ES:SE:LP:AF:ID 0.0308:0.0139:1.58153:0.0916791:rs6694487
1 1125220 rs12065129 C T . PASS AF=0.0915307 ES:SE:LP:AF:ID 0.0314:0.0139:1.62949:0.0915307:rs12065129
1 1127101 rs9659458 C A . PASS AF=0.0915671 ES:SE:LP:AF:ID 0.0309:0.0139:1.58386:0.0915671:rs9659458
1 1127137 rs12062271 A C . PASS AF=0.0921988 ES:SE:LP:AF:ID 0.0312:0.0138:1.62142:0.0921988:rs12062271
1 1127330 rs12061357 C T . PASS AF=0.0943436 ES:SE:LP:AF:ID 0.0312:0.0137:1.64589:0.0943436:rs12061357
1 1129122 rs9659213 G C . PASS AF=0.0919861 ES:SE:LP:AF:ID 0.0325:0.0138:1.72886:0.0919861:rs9659213
1 1129789 rs12060374 G C . PASS AF=0.0919428 ES:SE:LP:AF:ID 0.0313:0.0138:1.62415:0.0919428:rs12060374
1 1129920 rs12060422 G A . PASS AF=0.0920677 ES:SE:LP:AF:ID 0.0316:0.0138:1.65092:0.0920677:rs12060422
1 1130727 rs10907175 A C . PASS AF=0.0912872 ES:SE:LP:AF:ID 0.0325:0.0138:1.73779:0.0912872:rs10907175
1 1130855 rs10907176 T C . PASS AF=0.083123 ES:SE:LP:AF:ID 0.025:0.0145:1.07397:0.083123:rs10907176
1 1131052 rs12066103 C T . PASS AF=0.0918153 ES:SE:LP:AF:ID 0.0312:0.0138:1.61279:0.0918153:rs12066103
1 1131236 rs12062042 G T . PASS AF=0.0914339 ES:SE:LP:AF:ID 0.0311:0.0139:1.59843:0.0914339:rs12062042
1 1472873 rs4259576 T A . PASS AF=0.303646 ES:SE:LP:AF:ID 0.0063:0.0086:0.335076:0.303646:rs4259576
1 1474167 rs1571149 A G . PASS AF=0.318991 ES:SE:LP:AF:ID 0.0077:0.0084:0.440333:0.318991:rs1571149
1 1474304 rs1571150 C A . PASS AF=0.298446 ES:SE:LP:AF:ID 0.0066:0.0086:0.353106:0.298446:rs1571150
1 1474871 rs9439465 G C . PASS AF=0.30418 ES:SE:LP:AF:ID 0.0069:0.0084:0.381743:0.30418:rs9439465
1 1477244 rs7290 T C . PASS AF=0.289866 ES:SE:LP:AF:ID 0.0078:0.0086:0.435926:0.289866:rs7290
1 1478153 rs3766180 T C . PASS AF=0.286858 ES:SE:LP:AF:ID 0.0073:0.0085:0.407934:0.286858:rs3766180
1 1478173 rs3766179 C G . PASS AF=0.287991 ES:SE:LP:AF:ID 0.0077:0.0087:0.42539:0.287991:rs3766179
1 1478180 rs3766178 T C . PASS AF=0.286942 ES:SE:LP:AF:ID 0.0075:0.0086:0.414765:0.286942:rs3766178
1 1478880 rs6665973 T G . PASS AF=0.289795 ES:SE:LP:AF:ID 0.0079:0.0086:0.446481:0.289795:rs6665973
1 1479333 rs7533 A G . PASS AF=0.289445 ES:SE:LP:AF:ID 0.0077:0.0087:0.429457:0.289445:rs7533
1 1481175 rs9329413 C A . PASS AF=0.289375 ES:SE:LP:AF:ID 0.0076:0.0086:0.422623:0.289375:rs9329413
1 1483010 rs7517401 G A . PASS AF=0.316601 ES:SE:LP:AF:ID 0.0075:0.0085:0.423313:0.316601:rs7517401
1 1484970 rs7515814 C G . PASS AF=0.319279 ES:SE:LP:AF:ID 0.0063:0.0085:0.335076:0.319279:rs7515814
1 1489072 rs3930748 A G . PASS AF=0.319526 ES:SE:LP:AF:ID 0.0055:0.0083:0.291919:0.319526:rs3930748
1 1489670 rs7531530 C T . PASS AF=0.273102 ES:SE:LP:AF:ID 0.009:0.0088:0.513428:0.273102:rs7531530
1 1489928 rs7366884 T C . PASS AF=0.272689 ES:SE:LP:AF:ID 0.0083:0.0088:0.460422:0.272689:rs7366884
1 1490074 rs7366635 A G . PASS AF=0.321041 ES:SE:LP:AF:ID 0.0061:0.0082:0.334419:0.321041:rs7366635
1 1490161 rs3753332 A G . PASS AF=0.321099 ES:SE:LP:AF:ID 0.0065:0.0084:0.357239:0.321099:rs3753332
1 1490232 rs3753331 T C . PASS AF=0.320995 ES:SE:LP:AF:ID 0.006:0.0085:0.321027:0.320995:rs3753331
1 1490559 rs3820075 A G . PASS AF=0.272986 ES:SE:LP:AF:ID 0.0077:0.0088:0.414539:0.272986:rs3820075
1 1490627 rs3753330 T A . PASS AF=0.321085 ES:SE:LP:AF:ID 0.0059:0.0083:0.319846:0.321085:rs3753330
1 1491251 rs12048706 T C . PASS AF=0.273645 ES:SE:LP:AF:ID 0.0065:0.0088:0.339135:0.273645:rs12048706
1 1495083 rs6667347 G C . PASS AF=0.305127 ES:SE:LP:AF:ID 0.0055:0.0086:0.280834:0.305127:rs6667347
1 1496145 rs12410854 T C . PASS AF=0.274505 ES:SE:LP:AF:ID 0.0064:0.0088:0.328179:0.274505:rs12410854
1 1497008 rs3766170 T C . PASS AF=0.320269 ES:SE:LP:AF:ID 0.0064:0.0085:0.343614:0.320269:rs3766170
1 1497201 rs3766169 A C . PASS AF=0.289532 ES:SE:LP:AF:ID 0.007:0.0087:0.373352:0.289532:rs3766169
1 1499298 rs9439468 A G . PASS AF=0.31909 ES:SE:LP:AF:ID 0.0062:0.0085:0.328272:0.31909:rs9439468
1 1500941 rs6603791 A G . PASS AF=0.318872 ES:SE:LP:AF:ID 0.0061:0.0084:0.329383:0.318872:rs6603791