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": "2019-10-26T09:32:07.241386",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006096/EBI-a-GCST006096_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-GCST006096/EBI-a-GCST006096.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006096/EBI-a-GCST006096_data.vcf.gz; Date=Sat Oct 26 09:45:14 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006096/ebi-a-GCST006096.vcf.gz; Date=Sun May 10 04:27:47 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-GCST006096/EBI-a-GCST006096.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-GCST006096/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 10:07:03 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006096/EBI-a-GCST006096.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 10:07:07 2019
Total time elapsed: 3.48sQC metrics
Metrics
Metrics
{
"af_correlation": 0.8501,
"inflation_factor": 1.008,
"mean_EFFECT": -0.0002,
"n": "-Inf",
"n_snps": 559836,
"n_clumped_hits": 2,
"n_p_sig": 28,
"n_mono": 0,
"n_ns": 5213,
"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": 5114,
"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 | 4 | 38 | 0 | 558286 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 47 | 0 | 511 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 42 | 0 | 339 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 558287 | 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 | 9.031507e+00 | 5.918279e+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 | 7.993162e+07 | 5.705368e+07 | 3587.0000000 | 3.139466e+07 | 7.124516e+07 | 1.195183e+08 | 2.492107e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.714000e-04 | 4.101470e-02 | -0.4976170 | -2.464300e-02 | 3.620000e-05 | 2.455830e-02 | 6.643570e-01 | ▁▂▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.843320e-02 | 1.290280e-02 | 0.0283610 | 3.041060e-02 | 3.423500e-02 | 4.220360e-02 | 6.266840e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.989802e-01 | 2.890091e-01 | 0.0000000 | 2.487454e-01 | 4.982875e-01 | 7.496516e-01 | 9.999999e-01 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.989802e-01 | 2.890091e-01 | 0.0000000 | 2.487449e-01 | 4.982876e-01 | 7.496510e-01 | 9.999999e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.667755e-01 | 2.455087e-01 | 0.0005333 | 1.569160e-01 | 3.072760e-01 | 5.450495e-01 | 9.944330e-01 | ▇▆▅▃▂ |
| numeric | AF_reference | 5114 | 0.9908398 | NA | NA | NA | NA | NA | NA | NA | 3.376788e-01 | 2.302457e-01 | 0.0001997 | 1.483630e-01 | 2.909350e-01 | 5.002000e-01 | 9.986020e-01 | ▇▇▅▃▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 752566 | rs3094315 | G | A | -0.0006896 | 0.0402213 | 0.9863215 | 0.9863216 | 0.8448450 | 0.7182510 | NA |
| 1 | 990417 | rs2465136 | T | C | -0.0256414 | 0.0395121 | 0.5163700 | 0.5163703 | 0.1625320 | 0.3839860 | NA |
| 1 | 1018704 | rs9442372 | A | G | 0.0534235 | 0.0369785 | 0.1485368 | 0.1485371 | 0.8119550 | 0.6110220 | NA |
| 1 | 1036959 | rs11579015 | T | C | -0.0070446 | 0.0360528 | 0.8450835 | 0.8450832 | 0.2039570 | 0.1569490 | NA |
| 1 | 1046164 | rs6666280 | C | T | -0.0122639 | 0.0361512 | 0.7344293 | 0.7344296 | 0.2033310 | 0.2823480 | NA |
| 1 | 1062638 | rs9442373 | C | A | -0.0477614 | 0.0292240 | 0.1021911 | 0.1021914 | 0.5396500 | 0.5742810 | NA |
| 1 | 1216195 | rs55834051 | C | A | -0.0036720 | 0.0303794 | 0.9037926 | 0.9037927 | 0.6441210 | 0.3182910 | NA |
| 1 | 1217011 | rs1262894 | A | C | -0.0298079 | 0.0448063 | 0.5058829 | 0.5058833 | 0.1219990 | 0.2096650 | NA |
| 1 | 1217058 | rs3753340 | G | A | 0.0608623 | 0.1251020 | 0.6266110 | 0.6266117 | 0.0144225 | 0.0547125 | NA |
| 1 | 1218086 | rs6603788 | C | T | -0.0083572 | 0.0301833 | 0.7818690 | 0.7818698 | 0.6326950 | 0.4694490 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 155075318 | rs28673993 | A | G | -0.0262924 | 0.0292535 | 0.3687712 | 0.3687710 | 0.550435 | 0.494010 | NA |
| 23 | 155093036 | rs5940611 | A | G | 0.0361065 | 0.0294970 | 0.2209241 | 0.2209245 | 0.455459 | 0.518171 | NA |
| 23 | 155096106 | rs7056030 | C | T | 0.0423569 | 0.0299122 | 0.1567632 | 0.1567635 | 0.383539 | 0.509385 | NA |
| 23 | 155101861 | rs5940431 | T | C | -0.0128639 | 0.0292594 | 0.6601901 | 0.6601905 | 0.530342 | 0.646765 | NA |
| 23 | 155104608 | rs5940618 | G | A | -0.0202543 | 0.0304168 | 0.5054812 | 0.5054802 | 0.349194 | 0.339457 | NA |
| 23 | 155123237 | rs4893101 | C | T | -0.0316481 | 0.0306185 | 0.3013096 | 0.3013107 | 0.644919 | 0.592851 | NA |
| 23 | 155158490 | rs5983829 | A | G | -0.0118394 | 0.0308176 | 0.7008483 | 0.7008476 | 0.664322 | 0.637780 | NA |
| 23 | 155184866 | rs2889416 | T | C | 0.0195618 | 0.0337427 | 0.5620954 | 0.5620938 | 0.248887 | 0.370407 | NA |
| 23 | 155223705 | rs7051412 | T | G | -0.0280748 | 0.0335102 | 0.4021444 | 0.4021438 | 0.743987 | 0.552117 | NA |
| 23 | 155227607 | rs3093457 | T | G | -0.0484266 | 0.0329777 | 0.1419780 | 0.1419779 | 0.729838 | 0.512580 | NA |
bcf preview
1 752566 rs3094315 G A . PASS AF=0.844845 ES:SE:LP:AF:ID -0.000689563:0.0402213:0.00598148:0.844845:rs3094315
1 990417 rs2465136 T C . PASS AF=0.162532 ES:SE:LP:AF:ID -0.0256414:0.0395121:0.287039:0.162532:rs2465136
1 1018704 rs9442372 A G . PASS AF=0.811955 ES:SE:LP:AF:ID 0.0534235:0.0369785:0.828166:0.811955:rs9442372
1 1036959 rs11579015 T C . PASS AF=0.203957 ES:SE:LP:AF:ID -0.00704456:0.0360528:0.0731004:0.203957:rs11579015
1 1046164 rs6666280 C T . PASS AF=0.203331 ES:SE:LP:AF:ID -0.0122639:0.0361512:0.13405:0.203331:rs6666280
1 1062638 rs9442373 C A . PASS AF=0.53965 ES:SE:LP:AF:ID -0.0477614:0.029224:0.990587:0.53965:rs9442373
1 1216195 rs55834051 C A . PASS AF=0.644121 ES:SE:LP:AF:ID -0.00367201:0.0303794:0.0439312:0.644121:rs55834051
1 1217011 rs1262894 A C . PASS AF=0.121999 ES:SE:LP:AF:ID -0.0298079:0.0448063:0.29595:0.121999:rs1262894
1 1217058 rs3753340 G A . PASS AF=0.0144225 ES:SE:LP:AF:ID 0.0608623:0.125102:0.203002:0.0144225:rs3753340
1 1218086 rs6603788 C T . PASS AF=0.632695 ES:SE:LP:AF:ID -0.00835725:0.0301833:0.106866:0.632695:rs6603788
1 1220136 rs2144440 A G . PASS AF=0.652452 ES:SE:LP:AF:ID -0.00519206:0.0305614:0.0629352:0.652452:rs2144440
1 1220954 rs12751100 G A . PASS AF=0.63732 ES:SE:LP:AF:ID -0.00370006:0.030218:0.0445306:0.63732:rs12751100
1 1221138 rs11260578 G A . PASS AF=0.622697 ES:SE:LP:AF:ID -0.00822714:0.0301351:0.105215:0.622697:rs11260578
1 1222958 rs111819661 C T . PASS AF=0.0144934 ES:SE:LP:AF:ID 0.065756:0.126138:0.22029:0.0144934:rs111819661
1 1223529 rs78481580 G C . PASS AF=0.182145 ES:SE:LP:AF:ID 0.0215374:0.0380819:0.242835:0.182145:rs78481580
1 1225959 rs1570867 C G . PASS AF=0.922551 ES:SE:LP:AF:ID 0.086239:0.0546857:0.940069:0.922551:rs1570867
1 1227244 rs2239609 G A . PASS AF=0.274785 ES:SE:LP:AF:ID 0.0716344:0.0329676:1.52593:0.274785:rs2239609
1 1278237 rs307361 T C . PASS AF=0.86929 ES:SE:LP:AF:ID 0.0946273:0.0431286:1.54929:0.86929:rs307361
1 1287040 rs182532 T C . PASS AF=0.869056 ES:SE:LP:AF:ID 0.0921869:0.0431715:1.48504:0.869056:rs182532
1 1295323 rs34389364 G A . PASS AF=0.808131 ES:SE:LP:AF:ID 0.0699167:0.0371208:1.22451:0.808131:rs34389364
1 1314015 rs2649588 C T . PASS AF=0.826185 ES:SE:LP:AF:ID 0.0684623:0.0385756:1.11954:0.826185:rs2649588
1 1335218 rs2291889 G A . PASS AF=0.121077 ES:SE:LP:AF:ID -0.0854067:0.0445856:1.25633:0.121077:rs2291889
1 1487059 rs1887284 G A . PASS AF=0.262417 ES:SE:LP:AF:ID -0.000355669:0.0330961:0.00373985:0.262417:rs1887284
1 1489928 rs7366884 T C . PASS AF=0.716754 ES:SE:LP:AF:ID 0.00843119:0.0326234:0.0990502:0.716754:rs7366884
1 1500941 rs6603791 A G . PASS AF=0.824429 ES:SE:LP:AF:ID 0.0606748:0.0384807:0.939865:0.824429:rs6603791
1 1599161 rs6604981 A G . PASS AF=0.621014 ES:SE:LP:AF:ID -0.00187261:0.0300879:0.0221058:0.621014:rs6604981
1 1647686 rs909823 A C . PASS AF=0.869063 ES:SE:LP:AF:ID 0.0115335:0.0423285:0.104988:0.869063:rs909823
1 1687625 rs34306661 T C . PASS AF=0.332064 ES:SE:LP:AF:ID -0.0284443:0.0307782:0.449287:0.332064:rs34306661
1 1706160 rs7531583 A G . PASS AF=0.70011 ES:SE:LP:AF:ID 0.0450312:0.0317304:0.807302:0.70011:rs7531583
1 1721479 rs2272908 C T . PASS AF=0.502984 ES:SE:LP:AF:ID 0.00955486:0.0291325:0.129053:0.502984:rs2272908
1 1722585 rs3737626 C A . PASS AF=0.0381004 ES:SE:LP:AF:ID 0.0653316:0.0769481:0.402456:0.0381004:rs3737626
1 1722932 rs3737628 C T . PASS AF=0.502721 ES:SE:LP:AF:ID 0.011326:0.0291367:0.156466:0.502721:rs3737628
1 1723031 rs9660180 G A . PASS AF=0.504401 ES:SE:LP:AF:ID 0.00978962:0.029217:0.132194:0.504401:rs9660180
1 1725016 rs80220232 G A . PASS AF=0.066223 ES:SE:LP:AF:ID -0.0350898:0.0579607:0.263676:0.066223:rs80220232
1 1725626 rs9970652 C T . PASS AF=0.206243 ES:SE:LP:AF:ID -0.0669188:0.0358045:1.21026:0.206243:rs9970652
1 1733219 rs10907185 A G . PASS AF=0.710327 ES:SE:LP:AF:ID -0.0395916:0.032243:0.658606:0.710327:rs10907185
1 1734337 rs75622028 T C . PASS AF=0.103286 ES:SE:LP:AF:ID 0.0627455:0.0482079:0.714292:0.103286:rs75622028
1 1737900 rs17363334 C T . PASS AF=0.0685096 ES:SE:LP:AF:ID -0.0475736:0.057825:0.386508:0.0685096:rs17363334
1 1738984 rs76117314 C A . PASS AF=0.0598594 ES:SE:LP:AF:ID -0.0623075:0.061066:0.512055:0.0598594:rs76117314
1 1745726 rs16825336 G A . PASS AF=0.266627 ES:SE:LP:AF:ID 0.0232525:0.0329172:0.318809:0.266627:rs16825336
1 1746694 rs12742323 G T . PASS AF=0.207488 ES:SE:LP:AF:ID -0.0610985:0.0357211:1.05955:0.207488:rs12742323
1 1747318 rs59787372 T C . PASS AF=0.0356951 ES:SE:LP:AF:ID 0.00101163:0.0786174:0.00448183:0.0356951:rs59787372
1 1748734 rs2180311 T C . PASS AF=0.505353 ES:SE:LP:AF:ID 0.0137282:0.0291059:0.195746:0.505353:rs2180311
1 1752955 rs4648726 C T . PASS AF=0.843103 ES:SE:LP:AF:ID -0.0711071:0.0405009:1.1016:0.843103:rs4648726
1 1759026 rs9786963 T C . PASS AF=0.908969 ES:SE:LP:AF:ID -0.0256462:0.0513665:0.209305:0.908969:rs9786963
1 1759054 rs10907187 G A . PASS AF=0.128451 ES:SE:LP:AF:ID -0.023958:0.0440846:0.231498:0.128451:rs10907187
1 1759213 rs9786942 A G . PASS AF=0.505091 ES:SE:LP:AF:ID 0.0146243:0.0291442:0.21055:0.505091:rs9786942
1 1760937 rs77726987 G A . PASS AF=0.0353723 ES:SE:LP:AF:ID 0.025157:0.0801402:0.122866:0.0353723:rs77726987
1 1765583 rs6603797 T C . PASS AF=0.908316 ES:SE:LP:AF:ID -0.0232905:0.0511327:0.187918:0.908316:rs6603797
1 1766094 rs6663586 A C . PASS AF=0.195172 ES:SE:LP:AF:ID 0.0354001:0.0370718:0.469:0.195172:rs6663586