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": "2019-10-26T09:28:45.593381",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006090/EBI-a-GCST006090_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-GCST006090/EBI-a-GCST006090.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006090/EBI-a-GCST006090_data.vcf.gz; Date=Sat Oct 26 09:43:35 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006090/ebi-a-GCST006090.vcf.gz; Date=Sun May 10 13:25:39 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-GCST006090/EBI-a-GCST006090.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-GCST006090/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 10:05:31 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006090/EBI-a-GCST006090.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 10:05:34 2019
Total time elapsed: 3.21sQC metrics
Metrics
Metrics
{
"af_correlation": 0.8473,
"inflation_factor": 1.016,
"mean_EFFECT": 0.0006,
"n": "-Inf",
"n_snps": 548674,
"n_clumped_hits": 2,
"n_p_sig": 74,
"n_mono": 0,
"n_ns": 3945,
"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": 5073,
"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 | 547180 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 54 | 0 | 312 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 35 | 0 | 240 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 547181 | 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 | 9.046100e+00 | 6.054004e+00 | 1.000e+00 | 4.000000e+00 | 8.000000e+00 | 1.400000e+01 | 2.300000e+01 | ▇▅▅▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.622532e+07 | 5.668312e+07 | 3.587e+03 | 2.961052e+07 | 6.469502e+07 | 1.127275e+08 | 2.492107e+08 | ▇▆▃▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.538000e-04 | 6.640940e-02 | -1.829e+00 | -3.979000e-02 | 3.264000e-04 | 4.054000e-02 | 2.582000e+00 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 6.229500e-02 | 2.023090e-02 | 4.602e-02 | 4.958000e-02 | 5.574000e-02 | 6.861000e-02 | 1.254000e+00 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.979036e-01 | 2.893213e-01 | 0.000e+00 | 2.465000e-01 | 4.966003e-01 | 7.488003e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.979036e-01 | 2.893215e-01 | 0.000e+00 | 2.465192e-01 | 4.965873e-01 | 7.488146e-01 | 9.999971e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.687336e-01 | 2.456285e-01 | 3.305e-04 | 1.583400e-01 | 3.087860e-01 | 5.484140e-01 | 9.950140e-01 | ▇▇▅▃▂ |
| numeric | AF_reference | 5073 | 0.9907288 | NA | NA | NA | NA | NA | NA | NA | 3.395460e-01 | 2.296710e-01 | 1.997e-04 | 1.509580e-01 | 2.933310e-01 | 5.015970e-01 | 9.982030e-01 | ▇▇▅▃▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 752566 | rs3094315 | G | A | -0.018810 | 0.06551 | 0.7740001 | 0.7740115 | 0.8448450 | 0.7182510 | NA |
| 1 | 990417 | rs2465136 | T | C | 0.038870 | 0.06451 | 0.5467994 | 0.5468133 | 0.1625320 | 0.3839860 | NA |
| 1 | 1018704 | rs9442372 | A | G | -0.033450 | 0.06014 | 0.5781000 | 0.5780726 | 0.8119550 | 0.6110220 | NA |
| 1 | 1036959 | rs11579015 | T | C | -0.070930 | 0.05780 | 0.2198002 | 0.2197615 | 0.2039570 | 0.1569490 | NA |
| 1 | 1046164 | rs6666280 | C | T | -0.070620 | 0.05795 | 0.2230001 | 0.2229821 | 0.2033310 | 0.2823480 | NA |
| 1 | 1062638 | rs9442373 | C | A | 0.016700 | 0.04763 | 0.7258001 | 0.7258739 | 0.5396500 | 0.5742810 | NA |
| 1 | 1216195 | rs55834051 | C | A | -0.005924 | 0.04890 | 0.9036000 | 0.9035760 | 0.6441210 | 0.3182910 | NA |
| 1 | 1217011 | rs1262894 | A | C | -0.028410 | 0.07245 | 0.6950003 | 0.6949603 | 0.1219990 | 0.2096650 | NA |
| 1 | 1217058 | rs3753340 | G | A | 0.267000 | 0.21280 | 0.2095999 | 0.2095880 | 0.0144225 | 0.0547125 | NA |
| 1 | 1218086 | rs6603788 | C | T | 0.027900 | 0.04837 | 0.5640999 | 0.5640720 | 0.6326950 | 0.4694490 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 155075318 | rs28673993 | A | G | 0.050830 | 0.04774 | 0.2870001 | 0.2870001 | 0.550435 | 0.494010 | NA |
| 23 | 155093036 | rs5940611 | A | G | -0.054520 | 0.04820 | 0.2581000 | 0.2580044 | 0.455459 | 0.518171 | NA |
| 23 | 155096106 | rs7056030 | C | T | -0.005369 | 0.04873 | 0.9123001 | 0.9122678 | 0.383539 | 0.509385 | NA |
| 23 | 155101861 | rs5940431 | T | C | 0.038220 | 0.04802 | 0.4261005 | 0.4260795 | 0.530342 | 0.646765 | NA |
| 23 | 155104608 | rs5940618 | G | A | -0.046040 | 0.04936 | 0.3508997 | 0.3509547 | 0.349194 | 0.339457 | NA |
| 23 | 155123237 | rs4893101 | C | T | 0.020290 | 0.04984 | 0.6839998 | 0.6839325 | 0.644919 | 0.592851 | NA |
| 23 | 155158490 | rs5983829 | A | G | 0.011030 | 0.05025 | 0.8262000 | 0.8262586 | 0.664322 | 0.637780 | NA |
| 23 | 155184866 | rs2889416 | T | C | 0.049250 | 0.05537 | 0.3737997 | 0.3737501 | 0.248887 | 0.370407 | NA |
| 23 | 155223705 | rs7051412 | T | G | 0.039450 | 0.05475 | 0.4711997 | 0.4711877 | 0.743987 | 0.552117 | NA |
| 23 | 155227607 | rs3093457 | T | G | 0.048730 | 0.05365 | 0.3636997 | 0.3637226 | 0.729838 | 0.512580 | NA |
bcf preview
1 752566 rs3094315 G A . PASS AF=0.844845 ES:SE:LP:AF:ID -0.01881:0.06551:0.111259:0.844845:rs3094315
1 990417 rs2465136 T C . PASS AF=0.162532 ES:SE:LP:AF:ID 0.03887:0.06451:0.262172:0.162532:rs2465136
1 1018704 rs9442372 A G . PASS AF=0.811955 ES:SE:LP:AF:ID -0.03345:0.06014:0.237997:0.811955:rs9442372
1 1036959 rs11579015 T C . PASS AF=0.203957 ES:SE:LP:AF:ID -0.07093:0.0578:0.657972:0.203957:rs11579015
1 1046164 rs6666280 C T . PASS AF=0.203331 ES:SE:LP:AF:ID -0.07062:0.05795:0.651695:0.203331:rs6666280
1 1062638 rs9442373 C A . PASS AF=0.53965 ES:SE:LP:AF:ID 0.0167:0.04763:0.139183:0.53965:rs9442373
1 1216195 rs55834051 C A . PASS AF=0.644121 ES:SE:LP:AF:ID -0.005924:0.0489:0.0440238:0.644121:rs55834051
1 1217011 rs1262894 A C . PASS AF=0.121999 ES:SE:LP:AF:ID -0.02841:0.07245:0.158015:0.121999:rs1262894
1 1217058 rs3753340 G A . PASS AF=0.0144225 ES:SE:LP:AF:ID 0.267:0.2128:0.678609:0.0144225:rs3753340
1 1218086 rs6603788 C T . PASS AF=0.632695 ES:SE:LP:AF:ID 0.0279:0.04837:0.248644:0.632695:rs6603788
1 1220136 rs2144440 A G . PASS AF=0.652452 ES:SE:LP:AF:ID 0.009262:0.04885:0.0707855:0.652452:rs2144440
1 1220954 rs12751100 G A . PASS AF=0.63732 ES:SE:LP:AF:ID 0.02959:0.04854:0.265921:0.63732:rs12751100
1 1221138 rs11260578 G A . PASS AF=0.622697 ES:SE:LP:AF:ID 0.02001:0.04853:0.167427:0.622697:rs11260578
1 1222958 rs111819661 C T . PASS AF=0.0144934 ES:SE:LP:AF:ID 0.1352:0.213:0.279427:0.0144934:rs111819661
1 1223529 rs78481580 G C . PASS AF=0.182145 ES:SE:LP:AF:ID -0.09008:0.06103:0.853872:0.182145:rs78481580
1 1225959 rs1570867 C G . PASS AF=0.922551 ES:SE:LP:AF:ID 0.02925:0.08891:0.129538:0.922551:rs1570867
1 1227244 rs2239609 G A . PASS AF=0.274785 ES:SE:LP:AF:ID 0.01477:0.05259:0.108574:0.274785:rs2239609
1 1278237 rs307361 T C . PASS AF=0.86929 ES:SE:LP:AF:ID 0.04447:0.07074:0.276052:0.86929:rs307361
1 1287040 rs182532 T C . PASS AF=0.869056 ES:SE:LP:AF:ID 0.04366:0.0708:0.269622:0.869056:rs182532
1 1295323 rs34389364 G A . PASS AF=0.808131 ES:SE:LP:AF:ID 0.007699:0.06078:0.0461437:0.808131:rs34389364
1 1314015 rs2649588 C T . PASS AF=0.826185 ES:SE:LP:AF:ID 0.07051:0.06349:0.573977:0.826185:rs2649588
1 1335218 rs2291889 G A . PASS AF=0.121077 ES:SE:LP:AF:ID -0.09533:0.07217:0.729321:0.121077:rs2291889
1 1487059 rs1887284 G A . PASS AF=0.262417 ES:SE:LP:AF:ID 0.03232:0.05509:0.253833:0.262417:rs1887284
1 1489928 rs7366884 T C . PASS AF=0.716754 ES:SE:LP:AF:ID -0.04568:0.0538:0.402524:0.716754:rs7366884
1 1500941 rs6603791 A G . PASS AF=0.824429 ES:SE:LP:AF:ID -0.06553:0.06463:0.507799:0.824429:rs6603791
1 1599161 rs6604981 A G . PASS AF=0.621014 ES:SE:LP:AF:ID -0.006346:0.04895:0.0473044:0.621014:rs6604981
1 1647686 rs909823 A C . PASS AF=0.869063 ES:SE:LP:AF:ID 0.06228:0.0669:0.453581:0.869063:rs909823
1 1687625 rs34306661 T C . PASS AF=0.332064 ES:SE:LP:AF:ID -0.006723:0.0502:0.0489054:0.332064:rs34306661
1 1706160 rs7531583 A G . PASS AF=0.70011 ES:SE:LP:AF:ID 0.02174:0.05188:0.170568:0.70011:rs7531583
1 1721479 rs2272908 C T . PASS AF=0.502984 ES:SE:LP:AF:ID 0.008136:0.04703:0.0641402:0.502984:rs2272908
1 1722585 rs3737626 C A . PASS AF=0.0381004 ES:SE:LP:AF:ID -0.03923:0.1226:0.125576:0.0381004:rs3737626
1 1722932 rs3737628 C T . PASS AF=0.502721 ES:SE:LP:AF:ID 0.01158:0.04707:0.0938266:0.502721:rs3737628
1 1723031 rs9660180 G A . PASS AF=0.504401 ES:SE:LP:AF:ID 0.01382:0.04711:0.113904:0.504401:rs9660180
1 1725016 rs80220232 G A . PASS AF=0.066223 ES:SE:LP:AF:ID -0.07153:0.09451:0.347657:0.066223:rs80220232
1 1725626 rs9970652 C T . PASS AF=0.206243 ES:SE:LP:AF:ID -0.05454:0.05923:0.44721:0.206243:rs9970652
1 1733219 rs10907185 A G . PASS AF=0.710327 ES:SE:LP:AF:ID -0.03936:0.05197:0.34785:0.710327:rs10907185
1 1734337 rs75622028 T C . PASS AF=0.103286 ES:SE:LP:AF:ID 0.05507:0.07719:0.322849:0.103286:rs75622028
1 1737900 rs17363334 C T . PASS AF=0.0685096 ES:SE:LP:AF:ID 0.02683:0.09439:0.110026:0.0685096:rs17363334
1 1738984 rs76117314 C A . PASS AF=0.0598594 ES:SE:LP:AF:ID -0.03881:0.09865:0.158641:0.0598594:rs76117314
1 1745726 rs16825336 G A . PASS AF=0.266627 ES:SE:LP:AF:ID 0.009818:0.05353:0.0682879:0.266627:rs16825336
1 1746694 rs12742323 G T . PASS AF=0.207488 ES:SE:LP:AF:ID -0.05774:0.05925:0.481881:0.207488:rs12742323
1 1747318 rs59787372 T C . PASS AF=0.0356951 ES:SE:LP:AF:ID -0.02873:0.1269:0.0857626:0.0356951:rs59787372
1 1748734 rs2180311 T C . PASS AF=0.505353 ES:SE:LP:AF:ID 0.0153:0.04699:0.128019:0.505353:rs2180311
1 1752955 rs4648726 C T . PASS AF=0.843103 ES:SE:LP:AF:ID -0.1326:0.0658:1.35684:0.843103:rs4648726
1 1759026 rs9786963 T C . PASS AF=0.908969 ES:SE:LP:AF:ID -0.03988:0.08069:0.206838:0.908969:rs9786963
1 1759054 rs10907187 G A . PASS AF=0.128451 ES:SE:LP:AF:ID -0.1139:0.06964:0.991826:0.128451:rs10907187
1 1759213 rs9786942 A G . PASS AF=0.505091 ES:SE:LP:AF:ID 0.006932:0.04705:0.0540885:0.505091:rs9786942
1 1760937 rs77726987 G A . PASS AF=0.0353723 ES:SE:LP:AF:ID -0.01711:0.131:0.0476435:0.0353723:rs77726987
1 1765583 rs6603797 T C . PASS AF=0.908316 ES:SE:LP:AF:ID -0.0501:0.08049:0.272784:0.908316:rs6603797
1 1766094 rs6663586 A C . PASS AF=0.195172 ES:SE:LP:AF:ID 0.01369:0.05973:0.0868752:0.195172:rs6663586