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": "2019-10-26T21:41:43.985834",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006360/EBI-a-GCST006360_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-GCST006360/EBI-a-GCST006360.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006360/EBI-a-GCST006360_data.vcf.gz; Date=Sat Oct 26 21:53:47 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006360/ebi-a-GCST006360.vcf.gz; Date=Sat May 9 22:24:03 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-GCST006360/EBI-a-GCST006360.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-GCST006360/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 22:18:23 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006360/EBI-a-GCST006360.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 22:18:58 2019
Total time elapsed: 35.41sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9164,
"inflation_factor": 0.9901,
"mean_EFFECT": -0,
"n": "-Inf",
"n_snps": 5278042,
"n_clumped_hits": 1,
"n_p_sig": 1,
"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 | -3.460000e-05 | 1.068450e-02 | -0.0859577 | -6.608000e-03 | 2.230000e-05 | 6.576100e-03 | 6.694220e-02 | ▁▁▇▃▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.030370e-02 | 2.720000e-03 | 0.0071121 | 8.041900e-03 | 9.288000e-03 | 1.195290e-02 | 1.862740e-02 | ▇▃▂▂▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.007595e-01 | 2.890129e-01 | 0.0000000 | 2.507203e-01 | 5.021310e-01 | 7.504159e-01 | 9.999990e-01 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.005988e-01 | 2.891094e-01 | 0.0000000 | 2.504417e-01 | 5.019739e-01 | 7.503475e-01 | 9.999991e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.367567e-01 | 2.455678e-01 | 0.0500527 | 1.262580e-01 | 2.655940e-01 | 5.045270e-01 | 9.499470e-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 | -0.0084470 | 0.0109105 | 0.4389894 | 0.4388049 | 0.852616 | 0.639976 | NA |
| 1 | 731718 | rs142557973 | T | C | 0.0067714 | 0.0122718 | 0.5812206 | 0.5810960 | 0.105634 | 0.154353 | NA |
| 1 | 734349 | rs141242758 | T | C | 0.0087388 | 0.0124936 | 0.4844277 | 0.4842628 | 0.103119 | 0.152556 | NA |
| 1 | 736289 | rs79010578 | T | A | 0.0122368 | 0.0118577 | 0.3023389 | 0.3020858 | 0.121227 | 0.139577 | NA |
| 1 | 752566 | rs3094315 | G | A | -0.0101749 | 0.0110390 | 0.3569028 | 0.3566731 | 0.860161 | 0.718251 | NA |
| 1 | 752721 | rs3131972 | A | G | -0.0101749 | 0.0110390 | 0.3569028 | 0.3566731 | 0.860161 | 0.653355 | NA |
| 1 | 753405 | rs3115860 | C | A | -0.0082392 | 0.0118941 | 0.4886490 | 0.4884869 | 0.886318 | 0.751797 | NA |
| 1 | 753541 | rs2073813 | G | A | 0.0056134 | 0.0121110 | 0.6431111 | 0.6430089 | 0.110161 | 0.301917 | NA |
| 1 | 754182 | rs3131969 | A | G | -0.0081121 | 0.0118798 | 0.4948630 | 0.4947038 | 0.885815 | 0.678514 | NA |
| 1 | 754192 | rs3131968 | A | G | -0.0081121 | 0.0118798 | 0.4948630 | 0.4947038 | 0.885815 | 0.678514 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51217954 | rs9616974 | G | A | 0.0031263 | 0.0149521 | 0.8344250 | 0.8343819 | 0.0729376 | 0.0621006 | NA |
| 22 | 51218224 | rs9616975 | C | A | 0.0031263 | 0.0149521 | 0.8344250 | 0.8343819 | 0.0729376 | 0.0619010 | NA |
| 22 | 51218377 | rs2519461 | G | C | 0.0032244 | 0.0149125 | 0.8288619 | 0.8288179 | 0.0734406 | 0.0826677 | NA |
| 22 | 51219006 | rs28729663 | G | A | 0.0092754 | 0.0110487 | 0.4013876 | 0.4011859 | 0.1423540 | 0.2052720 | NA |
| 22 | 51219387 | rs9616832 | T | C | 0.0031263 | 0.0149521 | 0.8344250 | 0.8343819 | 0.0729376 | 0.0654952 | NA |
| 22 | 51221731 | rs115055839 | T | C | 0.0031263 | 0.0149521 | 0.8344250 | 0.8343819 | 0.0729376 | 0.0625000 | NA |
| 22 | 51222100 | rs114553188 | G | T | 0.0037754 | 0.0163224 | 0.8171301 | 0.8170818 | 0.0588531 | 0.0880591 | NA |
| 22 | 51223637 | rs375798137 | G | A | 0.0018851 | 0.0162665 | 0.9077649 | 0.9077414 | 0.0593561 | 0.0788738 | NA |
| 22 | 51229805 | rs9616985 | T | C | 0.0034040 | 0.0149937 | 0.8204500 | 0.8204035 | 0.0724346 | 0.0730831 | NA |
| 22 | 51237063 | rs3896457 | T | C | 0.0008793 | 0.0083306 | 0.9159621 | 0.9159407 | 0.2756540 | 0.2050720 | NA |
bcf preview
1 729679 rs4951859 C G . PASS AF=0.852616 ES:SE:LP:AF:ID -0.00844705:0.0109105:0.357546:0.852616:rs4951859
1 731718 rs58276399 T C . PASS AF=0.105634 ES:SE:LP:AF:ID 0.00677139:0.0122718:0.235659:0.105634:rs58276399
1 734349 rs141242758 T C . PASS AF=0.103119 ES:SE:LP:AF:ID 0.00873881:0.0124936:0.314771:0.103119:rs141242758
1 736289 rs79010578 T A . PASS AF=0.121227 ES:SE:LP:AF:ID 0.0122368:0.0118577:0.519506:0.121227:rs79010578
1 752566 rs3094315 G A . PASS AF=0.860161 ES:SE:LP:AF:ID -0.0101749:0.011039:0.44745:0.860161:rs3094315
1 752721 rs3131972 A G . PASS AF=0.860161 ES:SE:LP:AF:ID -0.0101749:0.011039:0.44745:0.860161:rs3131972
1 753405 rs3115860 C A . PASS AF=0.886318 ES:SE:LP:AF:ID -0.00823925:0.0118941:0.311003:0.886318:rs3115860
1 753541 rs2073813 G A . PASS AF=0.110161 ES:SE:LP:AF:ID 0.0056134:0.012111:0.191714:0.110161:rs2073813
1 754182 rs3131969 A G . PASS AF=0.885815 ES:SE:LP:AF:ID -0.00811208:0.0118798:0.305515:0.885815:rs3131969
1 754192 rs3131968 A G . PASS AF=0.885815 ES:SE:LP:AF:ID -0.00811208:0.0118798:0.305515:0.885815:rs3131968
1 754334 rs3131967 T C . PASS AF=0.886318 ES:SE:LP:AF:ID -0.00823925:0.0118941:0.311003:0.886318:rs3131967
1 754503 rs3115859 G A . PASS AF=0.86167 ES:SE:LP:AF:ID -0.0111803:0.0111017:0.502873:0.86167:rs3115859
1 754964 rs3131966 C T . PASS AF=0.86167 ES:SE:LP:AF:ID -0.0111803:0.0111017:0.502873:0.86167:rs3131966
1 755775 rs3131965 A G . PASS AF=0.864185 ES:SE:LP:AF:ID -0.0125594:0.0111464:0.584831:0.864185:rs3131965
1 755890 rs3115858 A T . PASS AF=0.886318 ES:SE:LP:AF:ID -0.00823925:0.0118941:0.311003:0.886318:rs3115858
1 756604 rs3131962 A G . PASS AF=0.886318 ES:SE:LP:AF:ID -0.00823925:0.0118941:0.311003:0.886318:rs3131962
1 757640 rs3115853 G A . PASS AF=0.884306 ES:SE:LP:AF:ID -0.0065839:0.0117476:0.240105:0.884306:rs3115853
1 757734 rs4951929 C T . PASS AF=0.886318 ES:SE:LP:AF:ID -0.00823925:0.0118941:0.311003:0.886318:rs4951929
1 757936 rs4951862 C A . PASS AF=0.886318 ES:SE:LP:AF:ID -0.00823925:0.0118941:0.311003:0.886318:rs4951862
1 758144 rs3131956 A G . PASS AF=0.886318 ES:SE:LP:AF:ID -0.00823925:0.0118941:0.311003:0.886318:rs3131956
1 758626 rs3131954 C T . PASS AF=0.886318 ES:SE:LP:AF:ID -0.00823925:0.0118941:0.311003:0.886318:rs3131954
1 760912 rs1048488 C T . PASS AF=0.863682 ES:SE:LP:AF:ID -0.0131399:0.0111805:0.619467:0.863682:rs1048488
1 761147 rs3115850 T C . PASS AF=0.863682 ES:SE:LP:AF:ID -0.0131399:0.0111805:0.619467:0.863682:rs3115850
1 761732 rs2286139 C T . PASS AF=0.881791 ES:SE:LP:AF:ID -0.00302079:0.0117215:0.0987155:0.881791:rs2286139
1 766007 rs61768174 A C . PASS AF=0.0885312 ES:SE:LP:AF:ID 0.0114766:0.0131159:0.418187:0.0885312:rs61768174
1 768253 rs2977608 A C . PASS AF=0.776157 ES:SE:LP:AF:ID 0.0116504:0.00928319:0.678242:0.776157:rs2977608
1 769223 rs60320384 C G . PASS AF=0.107646 ES:SE:LP:AF:ID 0.00297777:0.0121815:0.0931625:0.107646:rs60320384
1 771823 rs2977605 T C . PASS AF=0.887324 ES:SE:LP:AF:ID -0.00625926:0.0119083:0.222378:0.887324:rs2977605
1 771967 rs59066358 G A . PASS AF=0.108652 ES:SE:LP:AF:ID 0.00377232:0.0121474:0.121356:0.108652:rs59066358
1 772755 rs2905039 A C . PASS AF=0.887324 ES:SE:LP:AF:ID -0.00625926:0.0119083:0.222378:0.887324:rs2905039
1 777122 rs2980319 A T . PASS AF=0.889336 ES:SE:LP:AF:ID -0.00819261:0.0119737:0.306275:0.889336:rs2980319
1 778745 rs1055606 A G . PASS AF=0.10664 ES:SE:LP:AF:ID 0.00575541:0.0122171:0.1954:0.10664:rs1055606
1 779322 rs4040617 A G . PASS AF=0.107143 ES:SE:LP:AF:ID 0.0059795:0.0121989:0.204729:0.107143:rs4040617
1 780785 rs2977612 T A . PASS AF=0.885815 ES:SE:LP:AF:ID 0.000536884:0.0117071:0.0161794:0.885815:rs2977612
1 781845 rs61768199 A G . PASS AF=0.0850101 ES:SE:LP:AF:ID 0.00946683:0.0134597:0.316948:0.0850101:rs61768199
1 785050 rs2905062 G A . PASS AF=0.885312 ES:SE:LP:AF:ID 0.00356399:0.0117331:0.1184:0.885312:rs2905062
1 785989 rs2980300 T C . PASS AF=0.885312 ES:SE:LP:AF:ID 0.00356399:0.0117331:0.1184:0.885312:rs2980300
1 787606 rs3863622 G T . PASS AF=0.10664 ES:SE:LP:AF:ID 0.00559029:0.0122159:0.188879:0.10664:rs3863622
1 787685 rs2905054 G T . PASS AF=0.881791 ES:SE:LP:AF:ID 5.17001e-05:0.0115776:0.00154972:0.881791:rs2905054
1 787844 rs2905053 C T . PASS AF=0.887324 ES:SE:LP:AF:ID -0.00299655:0.0118433:0.0967423:0.887324:rs2905053
1 790465 rs61768207 G A . PASS AF=0.084507 ES:SE:LP:AF:ID 0.00713048:0.013568:0.222334:0.084507:rs61768207
1 791191 rs111818025 G A . PASS AF=0.10664 ES:SE:LP:AF:ID 0.004699:0.0122161:0.154545:0.10664:rs111818025
1 791853 rs6684487 G A . PASS AF=0.0940644 ES:SE:LP:AF:ID -0.00906835:0.0134135:0.301759:0.0940644:rs6684487
1 794332 rs12127425 G A . PASS AF=0.0870221 ES:SE:LP:AF:ID -0.00694856:0.0138175:0.211012:0.0870221:rs12127425
1 795222 rs12131377 C G . PASS AF=0.0855131 ES:SE:LP:AF:ID -0.00703765:0.0139087:0.212555:0.0855131:rs12131377
1 796100 rs12132398 C T . PASS AF=0.0865191 ES:SE:LP:AF:ID -0.00683918:0.0138538:0.206455:0.0865191:rs12132398
1 796375 rs12083781 T C . PASS AF=0.109155 ES:SE:LP:AF:ID 0.00281529:0.011976:0.08927:0.109155:rs12083781
1 797281 rs76631953 G C . PASS AF=0.0860161 ES:SE:LP:AF:ID -0.00717293:0.0138795:0.217949:0.0860161:rs76631953
1 797325 rs111739932 T C . PASS AF=0.0860161 ES:SE:LP:AF:ID -0.00717293:0.0138795:0.217949:0.0860161:rs111739932
1 797440 rs58013264 T C . PASS AF=0.108652 ES:SE:LP:AF:ID 0.00215969:0.0119909:0.066967:0.108652:rs58013264