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": "2019-10-26T21:43:21.340639",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006346/EBI-a-GCST006346_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-GCST006346/EBI-a-GCST006346.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006346/EBI-a-GCST006346_data.vcf.gz; Date=Sat Oct 26 21:56:24 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006346/ebi-a-GCST006346.vcf.gz; Date=Sun May 10 06:20:21 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-GCST006346/EBI-a-GCST006346.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-GCST006346/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 22:19:14 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006346/EBI-a-GCST006346.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 22:19:49 2019
Total time elapsed: 34.97sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9156,
"inflation_factor": 1.0217,
"mean_EFFECT": 0.0001,
"n": "-Inf",
"n_snps": 5278042,
"n_clumped_hits": 0,
"n_p_sig": 0,
"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": 35252,
"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 | 5265316 | 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 | 5265346 | 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 | 8.638495e+00 | 5.738675e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.879344e+07 | 5.645854e+07 | 828.0000000 | 3.228537e+07 | 6.932693e+07 | 1.146312e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.440000e-05 | 2.080560e-02 | -0.1432830 | -1.290960e-02 | 1.453000e-04 | 1.317170e-02 | 1.366360e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.006350e-02 | 5.346100e-03 | 0.0136000 | 1.566090e-02 | 1.807840e-02 | 2.325440e-02 | 4.167930e-02 | ▇▃▂▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.975700e-01 | 2.888591e-01 | 0.0000003 | 2.470632e-01 | 4.953920e-01 | 7.483332e-01 | 9.999980e-01 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.972892e-01 | 2.890269e-01 | 0.0000002 | 2.465775e-01 | 4.951142e-01 | 7.482153e-01 | 9.999984e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.367740e-01 | 2.457301e-01 | 0.0337955 | 1.265160e-01 | 2.651650e-01 | 5.043330e-01 | 9.653380e-01 | ▇▅▃▂▂ |
| numeric | AF_reference | 35252 | 0.9933049 | NA | NA | NA | NA | NA | NA | NA | 3.319970e-01 | 2.396594e-01 | 0.0001997 | 1.343850e-01 | 2.693690e-01 | 4.936100e-01 | 9.998000e-01 | ▇▆▃▂▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 729679 | rs4951859 | C | G | -0.0268411 | 0.0216945 | 0.2165110 | 0.2160015 | 0.863085 | 0.639976 | NA |
| 1 | 731718 | rs142557973 | T | C | 0.0191464 | 0.0242502 | 0.4301283 | 0.4297989 | 0.103120 | 0.154353 | NA |
| 1 | 734349 | rs141242758 | T | C | 0.0191464 | 0.0242502 | 0.4301283 | 0.4297989 | 0.103120 | 0.152556 | NA |
| 1 | 736289 | rs79010578 | T | A | 0.0367653 | 0.0236794 | 0.1210659 | 0.1205120 | 0.113518 | 0.139577 | NA |
| 1 | 752566 | rs3094315 | G | A | -0.0243431 | 0.0219920 | 0.2688023 | 0.2683341 | 0.867418 | 0.718251 | NA |
| 1 | 752721 | rs3131972 | A | G | -0.0243431 | 0.0219920 | 0.2688023 | 0.2683341 | 0.867418 | 0.653355 | NA |
| 1 | 753405 | rs3115860 | C | A | -0.0209530 | 0.0235213 | 0.3734066 | 0.3730313 | 0.886482 | 0.751797 | NA |
| 1 | 753541 | rs2073813 | G | A | 0.0231361 | 0.0238879 | 0.3331900 | 0.3327807 | 0.110919 | 0.301917 | NA |
| 1 | 754182 | rs3131969 | A | G | -0.0209530 | 0.0235213 | 0.3734066 | 0.3730313 | 0.886482 | 0.678514 | NA |
| 1 | 754192 | rs3131968 | A | G | -0.0209530 | 0.0235213 | 0.3734066 | 0.3730313 | 0.886482 | 0.678514 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51217954 | rs9616974 | G | A | -0.0150330 | 0.0295027 | 0.6105665 | 0.6103692 | 0.0675910 | 0.0621006 | NA |
| 22 | 51218224 | rs9616975 | C | A | -0.0150330 | 0.0295027 | 0.6105665 | 0.6103692 | 0.0675910 | 0.0619010 | NA |
| 22 | 51218377 | rs2519461 | G | C | -0.0150330 | 0.0295027 | 0.6105665 | 0.6103692 | 0.0675910 | 0.0826677 | NA |
| 22 | 51219006 | rs28729663 | G | A | -0.0039719 | 0.0217171 | 0.8549480 | 0.8548825 | 0.1343150 | 0.2052720 | NA |
| 22 | 51219387 | rs9616832 | T | C | -0.0150330 | 0.0295027 | 0.6105665 | 0.6103692 | 0.0675910 | 0.0654952 | NA |
| 22 | 51221731 | rs115055839 | T | C | -0.0150330 | 0.0295027 | 0.6105665 | 0.6103692 | 0.0675910 | 0.0625000 | NA |
| 22 | 51222100 | rs114553188 | G | T | 0.0055562 | 0.0317174 | 0.8610021 | 0.8609400 | 0.0580589 | 0.0880591 | NA |
| 22 | 51223637 | rs375798137 | G | A | 0.0082752 | 0.0315201 | 0.7930015 | 0.7929073 | 0.0589255 | 0.0788738 | NA |
| 22 | 51229805 | rs9616985 | T | C | -0.0150330 | 0.0295027 | 0.6105665 | 0.6103692 | 0.0675910 | 0.0730831 | NA |
| 22 | 51237063 | rs3896457 | T | C | 0.0297852 | 0.0160416 | 0.0638631 | 0.0633471 | 0.2712310 | 0.2050720 | NA |
bcf preview
1 729679 rs4951859 C G . PASS AF=0.863085 ES:SE:LP:AF:ID -0.0268411:0.0216945:0.66452:0.863085:rs4951859
1 731718 rs58276399 T C . PASS AF=0.10312 ES:SE:LP:AF:ID 0.0191464:0.0242502:0.366402:0.10312:rs58276399
1 734349 rs141242758 T C . PASS AF=0.10312 ES:SE:LP:AF:ID 0.0191464:0.0242502:0.366402:0.10312:rs141242758
1 736289 rs79010578 T A . PASS AF=0.113518 ES:SE:LP:AF:ID 0.0367653:0.0236794:0.916978:0.113518:rs79010578
1 752566 rs3094315 G A . PASS AF=0.867418 ES:SE:LP:AF:ID -0.0243431:0.021992:0.570567:0.867418:rs3094315
1 752721 rs3131972 A G . PASS AF=0.867418 ES:SE:LP:AF:ID -0.0243431:0.021992:0.570567:0.867418:rs3131972
1 753405 rs3115860 C A . PASS AF=0.886482 ES:SE:LP:AF:ID -0.020953:0.0235213:0.427818:0.886482:rs3115860
1 753541 rs2073813 G A . PASS AF=0.110919 ES:SE:LP:AF:ID 0.0231361:0.0238879:0.477308:0.110919:rs2073813
1 754182 rs3131969 A G . PASS AF=0.886482 ES:SE:LP:AF:ID -0.020953:0.0235213:0.427818:0.886482:rs3131969
1 754192 rs3131968 A G . PASS AF=0.886482 ES:SE:LP:AF:ID -0.020953:0.0235213:0.427818:0.886482:rs3131968
1 754334 rs3131967 T C . PASS AF=0.886482 ES:SE:LP:AF:ID -0.020953:0.0235213:0.427818:0.886482:rs3131967
1 754503 rs3115859 G A . PASS AF=0.868284 ES:SE:LP:AF:ID -0.0253833:0.0221587:0.597783:0.868284:rs3115859
1 754964 rs3131966 C T . PASS AF=0.868284 ES:SE:LP:AF:ID -0.0253833:0.0221587:0.597783:0.868284:rs3131966
1 755775 rs3131965 A G . PASS AF=0.87175 ES:SE:LP:AF:ID -0.0329715:0.0222844:0.855304:0.87175:rs3131965
1 755890 rs3115858 A T . PASS AF=0.886482 ES:SE:LP:AF:ID -0.020953:0.0235213:0.427818:0.886482:rs3115858
1 756604 rs3131962 A G . PASS AF=0.886482 ES:SE:LP:AF:ID -0.020953:0.0235213:0.427818:0.886482:rs3131962
1 757640 rs3115853 G A . PASS AF=0.885615 ES:SE:LP:AF:ID -0.0198684:0.023327:0.403712:0.885615:rs3115853
1 757734 rs4951929 C T . PASS AF=0.886482 ES:SE:LP:AF:ID -0.020953:0.0235213:0.427818:0.886482:rs4951929
1 757936 rs4951862 C A . PASS AF=0.886482 ES:SE:LP:AF:ID -0.020953:0.0235213:0.427818:0.886482:rs4951862
1 758144 rs3131956 A G . PASS AF=0.886482 ES:SE:LP:AF:ID -0.020953:0.0235213:0.427818:0.886482:rs3131956
1 758626 rs3131954 C T . PASS AF=0.886482 ES:SE:LP:AF:ID -0.020953:0.0235213:0.427818:0.886482:rs3131954
1 760912 rs1048488 C T . PASS AF=0.870017 ES:SE:LP:AF:ID -0.026601:0.0222211:0.634954:0.870017:rs1048488
1 761147 rs3115850 T C . PASS AF=0.870017 ES:SE:LP:AF:ID -0.026601:0.0222211:0.634954:0.870017:rs3115850
1 761732 rs2286139 C T . PASS AF=0.882149 ES:SE:LP:AF:ID -0.0208874:0.0230941:0.436353:0.882149:rs2286139
1 766007 rs61768174 A C . PASS AF=0.0883882 ES:SE:LP:AF:ID 0.0297838:0.0257313:0.606325:0.0883882:rs61768174
1 768253 rs2977608 A C . PASS AF=0.777296 ES:SE:LP:AF:ID -0.0223742:0.0183162:0.652904:0.777296:rs2977608
1 769223 rs60320384 C G . PASS AF=0.109185 ES:SE:LP:AF:ID 0.0230472:0.0239836:0.472395:0.109185:rs60320384
1 771823 rs2977605 T C . PASS AF=0.887348 ES:SE:LP:AF:ID -0.0207508:0.0235501:0.421801:0.887348:rs2977605
1 771967 rs59066358 G A . PASS AF=0.110052 ES:SE:LP:AF:ID 0.0229469:0.0239253:0.471196:0.110052:rs59066358
1 772755 rs2905039 A C . PASS AF=0.887348 ES:SE:LP:AF:ID -0.0207508:0.0235501:0.421801:0.887348:rs2905039
1 777122 rs2980319 A T . PASS AF=0.891681 ES:SE:LP:AF:ID -0.0190012:0.0238302:0.371024:0.891681:rs2980319
1 778745 rs1055606 A G . PASS AF=0.105719 ES:SE:LP:AF:ID 0.0212007:0.0242239:0.418127:0.105719:rs1055606
1 779322 rs4040617 A G . PASS AF=0.105719 ES:SE:LP:AF:ID 0.0212007:0.0242239:0.418127:0.105719:rs4040617
1 780785 rs2977612 T A . PASS AF=0.887348 ES:SE:LP:AF:ID -0.021377:0.0229779:0.452725:0.887348:rs2977612
1 781845 rs61768199 A G . PASS AF=0.0823224 ES:SE:LP:AF:ID 0.0289441:0.0266334:0.556576:0.0823224:rs61768199
1 785050 rs2905062 G A . PASS AF=0.886482 ES:SE:LP:AF:ID -0.0193594:0.0230833:0.395772:0.886482:rs2905062
1 785989 rs2980300 T C . PASS AF=0.886482 ES:SE:LP:AF:ID -0.0193594:0.0230833:0.395772:0.886482:rs2980300
1 787606 rs3863622 G T . PASS AF=0.104853 ES:SE:LP:AF:ID 0.021892:0.0242834:0.434516:0.104853:rs3863622
1 787685 rs2905054 G T . PASS AF=0.883016 ES:SE:LP:AF:ID -0.0115697:0.0228993:0.212127:0.883016:rs2905054
1 787844 rs2905053 C T . PASS AF=0.889081 ES:SE:LP:AF:ID -0.0181491:0.0233961:0.358297:0.889081:rs2905053
1 790465 rs61768207 G A . PASS AF=0.0823224 ES:SE:LP:AF:ID 0.0212713:0.026706:0.370515:0.0823224:rs61768207
1 791191 rs111818025 G A . PASS AF=0.104853 ES:SE:LP:AF:ID 0.0239314:0.0242746:0.488626:0.104853:rs111818025
1 791853 rs6684487 G A . PASS AF=0.0918544 ES:SE:LP:AF:ID 0.0179257:0.0266914:0.299195:0.0918544:rs6684487
1 794332 rs12127425 G A . PASS AF=0.0831889 ES:SE:LP:AF:ID 0.030439:0.0277391:0.563903:0.0831889:rs12127425
1 795222 rs12131377 C G . PASS AF=0.0823224 ES:SE:LP:AF:ID 0.0297646:0.0278322:0.544656:0.0823224:rs12131377
1 796100 rs12132398 C T . PASS AF=0.0831889 ES:SE:LP:AF:ID 0.030439:0.0277391:0.563903:0.0831889:rs12132398
1 796375 rs12083781 T C . PASS AF=0.107452 ES:SE:LP:AF:ID 0.0234293:0.0237689:0.488528:0.107452:rs12083781
1 797281 rs76631953 G C . PASS AF=0.0831889 ES:SE:LP:AF:ID 0.030439:0.0277391:0.563903:0.0831889:rs76631953
1 797325 rs111739932 T C . PASS AF=0.0831889 ES:SE:LP:AF:ID 0.030439:0.0277391:0.563903:0.0831889:rs111739932
1 797440 rs58013264 T C . PASS AF=0.107452 ES:SE:LP:AF:ID 0.0234293:0.0237689:0.488528:0.107452:rs58013264