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": "2019-10-26T21:57:29.889629",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST003724/EBI-a-GCST003724_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-GCST003724/EBI-a-GCST003724.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST003724/EBI-a-GCST003724_data.vcf.gz; Date=Sat Oct 26 22:17:38 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST003724/ebi-a-GCST003724.vcf.gz; Date=Sun May 10 09:52:24 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-GCST003724/EBI-a-GCST003724.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-GCST003724/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 22:42:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST003724/EBI-a-GCST003724.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 22:43:15 2019
Total time elapsed: 1.0m:1.98sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9463,
"inflation_factor": 1.0891,
"mean_EFFECT": 0.0006,
"n": "-Inf",
"n_snps": 9483147,
"n_clumped_hits": 7,
"n_p_sig": 140,
"n_mono": 0,
"n_ns": 600218,
"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": 81741,
"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 | 83 | 0 | 9463631 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 96 | 0 | 29635 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 103 | 0 | 28164 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 9463834 | 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 | 8.663661e+00 | 5.768059e+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 | 7.851200e+07 | 5.653060e+07 | 828.0000000 | 3.202347e+07 | 6.886660e+07 | 1.143369e+08 | 2.492393e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.826000e-04 | 9.981460e-02 | -112.1150000 | -2.650000e-02 | 1.000000e-03 | 2.880000e-02 | 5.914500e+00 | ▁▁▁▁▇ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.848030e-02 | 1.101835e-01 | 0.0204000 | 2.510000e-02 | 3.510000e-02 | 6.570000e-02 | 2.570350e+02 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.854569e-01 | 2.928479e-01 | 0.0000000 | 2.273998e-01 | 4.814997e-01 | 7.389993e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.856200e-01 | 2.928385e-01 | 0.0000000 | 2.274201e-01 | 4.813290e-01 | 7.397444e-01 | 9.998696e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.488821e-01 | 2.623765e-01 | 0.0001000 | 3.530000e-02 | 1.403000e-01 | 3.967000e-01 | 9.905000e-01 | ▇▂▂▁▁ |
| numeric | AF_reference | 81741 | 0.9913628 | NA | NA | NA | NA | NA | NA | NA | 2.485562e-01 | 2.535619e-01 | 0.0001997 | 3.973640e-02 | 1.555510e-01 | 3.919730e-01 | 1.000000e+00 | ▇▃▂▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 10177 | rs367896724 | A | AC | -0.0182 | 0.1385 | 0.8949999 | 0.8954526 | 0.3895 | 0.4253190 | NA |
| 1 | 10352 | rs555500075 | T | TA | -0.1287 | 0.1342 | 0.3378999 | 0.3375505 | 0.4117 | 0.4375000 | NA |
| 1 | 11012 | rs544419019 | C | G | 0.0511 | 0.1943 | 0.7925999 | 0.7925541 | 0.0924 | 0.0880591 | NA |
| 1 | 13110 | rs540538026 | G | A | -0.3031 | 0.2945 | 0.3034003 | 0.3033847 | 0.0649 | 0.0267572 | NA |
| 1 | 13116 | rs62635286 | T | G | 0.0117 | 0.1835 | 0.9491999 | 0.9491612 | 0.1678 | 0.0970447 | NA |
| 1 | 13118 | rs200579949 | A | G | 0.0117 | 0.1835 | 0.9491999 | 0.9491612 | 0.1678 | 0.0970447 | NA |
| 1 | 13550 | rs554008981 | G | A | 0.4345 | 0.4780 | 0.3632997 | 0.3633523 | 0.0130 | 0.0033946 | NA |
| 1 | 14464 | rs546169444 | A | T | -0.1405 | 0.1902 | 0.4598996 | 0.4600915 | 0.1849 | 0.0958466 | NA |
| 1 | 14599 | rs531646671 | T | A | -0.4091 | 0.1868 | 0.0286003 | 0.0285211 | 0.1916 | 0.1475640 | NA |
| 1 | 14604 | rs541940975 | A | G | -0.4091 | 0.1868 | 0.0286003 | 0.0285211 | 0.1916 | 0.1475640 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51233347 | rs62240044 | T | C | 0.0251 | 0.0296 | 0.3735003 | 0.3964530 | 0.2575 | 0.2134580 | NA |
| 22 | 51233666 | rs11091014 | C | T | 0.0659 | 0.1396 | 0.9303000 | 0.6368818 | 0.0221 | 0.0970447 | NA |
| 22 | 51234343 | rs374867791 | G | T | 0.0649 | 0.1396 | 0.9349001 | 0.6420033 | 0.0221 | 0.1002400 | NA |
| 22 | 51234799 | rs191117135 | G | A | 0.0906 | 0.1060 | 0.4600998 | 0.3927078 | 0.0150 | 0.0059904 | NA |
| 22 | 51235959 | rs200189535 | T | C | -0.0097 | 0.0358 | 0.7103003 | 0.7864297 | 0.1993 | 0.1996810 | NA |
| 22 | 51236013 | rs200507571 | A | AT | -0.0121 | 0.0307 | 0.6937005 | 0.6934800 | 0.2527 | 0.1487620 | NA |
| 22 | 51237063 | rs3896457 | T | C | 0.0326 | 0.0286 | 0.2355000 | 0.2543446 | 0.2737 | 0.2050720 | NA |
| 22 | 51237712 | rs370652263 | G | A | -0.0989 | 0.0531 | 0.0534601 | 0.0625293 | 0.0540 | 0.0690895 | NA |
| 22 | 51240820 | rs202228854 | C | T | -0.8860 | 0.5579 | 0.1123001 | 0.1122641 | 0.0273 | 0.1267970 | NA |
| 22 | 51244237 | rs575160859 | C | T | 0.2061 | 0.2304 | 0.3692003 | 0.3710377 | 0.0122 | 0.0037939 | NA |
bcf preview
1 10177 rs367896724 A AC . PASS AF=0.3895 ES:SE:LP:AF:ID -0.0182:0.1385:0.048177:0.3895:rs367896724
1 10352 rs555500075 T TA . PASS AF=0.4117 ES:SE:LP:AF:ID -0.1287:0.1342:0.471212:0.4117:rs555500075
1 11012 rs544419019 C G . PASS AF=0.0924 ES:SE:LP:AF:ID 0.0511:0.1943:0.100946:0.0924:rs544419019
1 13110 rs540538026 G A . PASS AF=0.0649 ES:SE:LP:AF:ID -0.3031:0.2945:0.517984:0.0649:rs540538026
1 13116 rs62635286 T G . PASS AF=0.1678 ES:SE:LP:AF:ID 0.0117:0.1835:0.0226423:0.1678:rs62635286
1 13118 rs62028691 A G . PASS AF=0.1678 ES:SE:LP:AF:ID 0.0117:0.1835:0.0226423:0.1678:rs62028691
1 13550 rs554008981 G A . PASS AF=0.013 ES:SE:LP:AF:ID 0.4345:0.478:0.439735:0.013:rs554008981
1 14464 rs546169444 A T . PASS AF=0.1849 ES:SE:LP:AF:ID -0.1405:0.1902:0.337337:0.1849:rs546169444
1 14599 rs707680 T A . PASS AF=0.1916 ES:SE:LP:AF:ID -0.4091:0.1868:1.54363:0.1916:rs707680
1 14604 rs541940975 A G . PASS AF=0.1916 ES:SE:LP:AF:ID -0.4091:0.1868:1.54363:0.1916:rs541940975
1 14930 rs6682385 A G . PASS AF=0.5076 ES:SE:LP:AF:ID 0.1525:0.134:0.592949:0.5076:rs6682385
1 15211 rs3982632 T G . PASS AF=0.7036 ES:SE:LP:AF:ID -0.1024:0.1455:0.317314:0.7036:rs3982632
1 15274 rs2758118 A G . PASS AF=0.2716 ES:SE:LP:AF:ID 0.0241:0.14:0.0638383:0.2716:rs2758118
1 15903 rs557514207 G GC . PASS AF=0.4311 ES:SE:LP:AF:ID -0.0737:0.138:0.226872:0.4311:rs557514207
1 18849 rs533090414 C G . PASS AF=0.9837 ES:SE:LP:AF:ID -0.3945:0.383:0.518557:0.9837:rs533090414
1 47159 rs540662756 T C . PASS AF=0.0637 ES:SE:LP:AF:ID 0.1015:0.282:0.143332:0.0637:rs540662756
1 51762 rs559190862 A G . PASS AF=0.0137 ES:SE:LP:AF:ID 0.3332:0.4707:0.319755:0.0137:rs559190862
1 51765 rs575564077 C G . PASS AF=0.0137 ES:SE:LP:AF:ID 0.3332:0.4707:0.319755:0.0137:rs575564077
1 60249 rs547227933 C T . PASS AF=0.0176 ES:SE:LP:AF:ID 0.1657:0.5377:0.120331:0.0176:rs547227933
1 62777 rs3844233 A T . PASS AF=0.4021 ES:SE:LP:AF:ID -0.0613:0.1427:0.175484:0.4021:rs3844233
1 63735 rs61158452 CCTA C . PASS AF=0.347 ES:SE:LP:AF:ID 0.0077:0.1445:0.0189519:0.347:rs201888535
1 66219 rs181028663 A T . PASS AF=0.0139 ES:SE:LP:AF:ID 0.0261:0.5655:0.0163286:0.0139:rs181028663
1 68082 rs367789441 T C . PASS AF=0.0698 ES:SE:LP:AF:ID -0.1724:0.2929:0.254691:0.0698:rs367789441
1 69428 rs140739101 T G . PASS AF=0.0433 ES:SE:LP:AF:ID -0.0046:0.3634:0.00436481:0.0433:rs140739101
1 69761 rs200505207 A T . PASS AF=0.0742 ES:SE:LP:AF:ID -0.13:0.2765:0.194975:0.0742:rs200505207
1 73490 rs558384541 T C . PASS AF=0.0173 ES:SE:LP:AF:ID -0.372:0.5446:0.305746:0.0173:rs558384541
1 74790 rs13328700 C G . PASS AF=0.0377 ES:SE:LP:AF:ID -0.2971:0.3468:0.407046:0.0377:rs13328700
1 74792 rs13328684 G A . PASS AF=0.0377 ES:SE:LP:AF:ID -0.2971:0.3468:0.407046:0.0377:rs13328684
1 81260 rs571136476 C T . PASS AF=0.047 ES:SE:LP:AF:ID -0.3103:0.3692:0.397181:0.047:rs571136476
1 82133 rs550749506 CAA C . PASS AF=0.9882 ES:SE:LP:AF:ID -0.639:0.4348:0.84863:0.9882:rs550749506
1 86028 rs114608975 T C . PASS AF=0.0484 ES:SE:LP:AF:ID -0.8116:0.3792:1.49039:0.0484:rs114608975
1 86331 rs115209712 A G . PASS AF=0.1098 ES:SE:LP:AF:ID -0.3094:0.241:0.700711:0.1098:rs115209712
1 88169 rs940550 C T . PASS AF=0.1783 ES:SE:LP:AF:ID -0.2064:0.1852:0.576918:0.1783:rs940550
1 88172 rs940551 G A . PASS AF=0.0685 ES:SE:LP:AF:ID -0.2557:0.3051:0.39599:0.0685:rs940551
1 88177 rs143215837 G C . PASS AF=0.0682 ES:SE:LP:AF:ID -0.2763:0.3069:0.43427:0.0682:rs143215837
1 88316 rs113759966 G A . PASS AF=0.0687 ES:SE:LP:AF:ID -0.2486:0.3027:0.38563:0.0687:rs113759966
1 91421 rs28619159 T C . PASS AF=0.0117 ES:SE:LP:AF:ID 0.4157:0.4838:0.408713:0.0117:rs28619159
1 99687 rs139153227 C T . PASS AF=0.0641 ES:SE:LP:AF:ID -0.2634:0.3138:0.396639:0.0641:rs139153227
1 104186 rs4288537 T C . PASS AF=0.6664 ES:SE:LP:AF:ID -0.09:0.1378:0.289713:0.6664:rs4288537
1 108929 rs62642118 C G . PASS AF=0.0114 ES:SE:LP:AF:ID -1.5368:1.0129:0.888737:0.0114:rs62642118
1 115729 rs199999500 GCACA G . PASS AF=0.0195 ES:SE:LP:AF:ID -0.6247:0.5488:0.59346:0.0195:rs199999500
1 122872 rs62642125 T G . PASS AF=0.2351 ES:SE:LP:AF:ID -0.0252:0.1668:0.0555667:0.2351:rs62642125
1 125271 rs3871807 C T . PASS AF=0.9712 ES:SE:LP:AF:ID -0.4963:0.2912:1.05443:0.9712:rs3871807
1 129010 rs377161483 AATG A . PASS AF=0.5609 ES:SE:LP:AF:ID 0.0833:0.1378:0.263205:0.5609:rs377161483
1 135195 rs554762511 A G . PASS AF=0.0117 ES:SE:LP:AF:ID -1.6501:1.1485:0.821599:0.0117:rs554762511
1 138593 rs375595668 G T . PASS AF=0.1031 ES:SE:LP:AF:ID -0.2789:0.2422:0.602755:0.1031:rs375595668
1 234408 rs111659307 A G . PASS AF=0.021 ES:SE:LP:AF:ID -0.2431:0.5212:0.19321:0.021:rs111659307
1 249652 rs538729150 G C . PASS AF=0.0169 ES:SE:LP:AF:ID -0.0583:0.3062:0.0654511:0.0169:rs538729150
1 255633 rs375136935 A G . PASS AF=0.0552 ES:SE:LP:AF:ID 0.3383:0.2916:0.608888:0.0552:rs375136935
1 255923 rs199745078 G GTC . PASS AF=0.1136 ES:SE:LP:AF:ID 0.0358:0.2166:0.0611802:0.1136:rs199745078