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": "2019-10-26T21:46:50.900132",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004988/EBI-a-GCST004988_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-GCST004988/EBI-a-GCST004988.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004988/EBI-a-GCST004988_data.vcf.gz; Date=Sat Oct 26 22:07:26 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST004988/ebi-a-GCST004988.vcf.gz; Date=Sat May 9 15:05:26 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-GCST004988/EBI-a-GCST004988.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-GCST004988/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 22:32:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004988/EBI-a-GCST004988.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 22:33:25 2019
Total time elapsed: 1.0m:11.75sQC metrics
Metrics
Metrics
{
"af_correlation": 0.952,
"inflation_factor": 1.2627,
"mean_EFFECT": -0.0011,
"n": "-Inf",
"n_snps": 11069664,
"n_clumped_hits": 154,
"n_p_sig": 19512,
"n_mono": 0,
"n_ns": 707965,
"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": 107392,
"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 | TRUE |
| 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 | TRUE |
| 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 | 11022315 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 96 | 0 | 35434 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 103 | 0 | 31588 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 11043349 | 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 | 9.107574e+00 | 6.202040e+00 | 1.0000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.853699e+07 | 5.621317e+07 | 828.0000 | 3.217570e+07 | 6.937220e+07 | 1.146036e+08 | 2.492393e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.050100e-03 | 2.340124e-01 | -754.9790 | -1.010000e-02 | -3.000000e-04 | 9.400000e-03 | 2.122000e+01 | ▁▁▁▁▇ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.113610e-02 | 1.655270e+01 | 0.0061 | 7.500000e-03 | 1.160000e-02 | 2.580000e-02 | 2.637100e+04 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.607251e-01 | 2.988315e-01 | 0.0000 | 1.928000e-01 | 4.484995e-01 | 7.198997e-01 | 9.998000e-01 | ▇▆▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.607211e-01 | 2.988283e-01 | 0.0000 | 1.928051e-01 | 4.485632e-01 | 7.199762e-01 | 9.998003e-01 | ▇▆▆▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.217881e-01 | 2.601975e-01 | 0.0051 | 2.010000e-02 | 1.015000e-01 | 3.515000e-01 | 9.949000e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 107392 | 0.9902754 | NA | NA | NA | NA | NA | NA | NA | 2.235894e-01 | 2.512875e-01 | 0.0000 | 2.156550e-02 | 1.206070e-01 | 3.514380e-01 | 1.000000e+00 | ▇▂▂▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 10616 | rs376342519 | CCGCCGTTGCAAAGGCGCGCCG | C | 0.0001 | 0.0578 | 0.9987000 | 0.9986196 | 0.9925 | 0.9930110 | NA |
| 1 | 10711 | rs1434325972 | A | G | -0.0303 | 0.0814 | 0.7094993 | 0.7097172 | 0.9924 | NA | NA |
| 1 | 11012 | rs544419019 | C | G | -0.0251 | 0.0158 | 0.1125999 | 0.1121490 | 0.0959 | 0.0880591 | NA |
| 1 | 13110 | rs540538026 | G | A | 0.0112 | 0.0297 | 0.7071003 | 0.7060960 | 0.0554 | 0.0267572 | NA |
| 1 | 13116 | rs62635286 | T | G | 0.0071 | 0.0141 | 0.6149998 | 0.6145804 | 0.1693 | 0.0970447 | NA |
| 1 | 13118 | rs200579949 | A | G | 0.0071 | 0.0141 | 0.6149998 | 0.6145804 | 0.1693 | 0.0970447 | NA |
| 1 | 13273 | rs531730856 | G | C | 0.0123 | 0.0154 | 0.4228000 | 0.4244636 | 0.1422 | 0.0950479 | NA |
| 1 | 13550 | rs554008981 | G | A | 0.1081 | 0.0927 | 0.2434002 | 0.2435630 | 0.0084 | 0.0033946 | NA |
| 1 | 13624 | rs1304990809 | C | G | -0.0270 | 0.0165 | 0.1015000 | 0.1017635 | 0.3062 | NA | NA |
| 1 | 14464 | rs546169444 | A | T | -0.0105 | 0.0147 | 0.4760001 | 0.4750505 | 0.1614 | 0.0958466 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154925905 | rs767460948 | T | C | 0.0373 | 0.0553 | 0.4995995 | 0.4999918 | 0.0083 | 0.0060927 | NA |
| 23 | 154927161 | rs764949235 | T | C | -0.0647 | 0.0346 | 0.0614299 | 0.0614918 | 0.0278 | 0.0521854 | NA |
| 23 | 154927183 | rs199695571 | C | T | -0.0165 | 0.0198 | 0.4035004 | 0.4046568 | 0.0801 | NA | NA |
| 23 | 154927183 | rs750002413 | C | CACACATATAT | 0.1135 | 0.0983 | 0.2484002 | 0.2482425 | 0.0065 | NA | NA |
| 23 | 154927185 | rs185685661 | T | C | 0.0065 | 0.0145 | 0.6552002 | 0.6539541 | 0.1118 | 0.1796030 | NA |
| 23 | 154927199 | rs645904 | C | T | -0.0008 | 0.0077 | 0.9157000 | 0.9172518 | 0.2398 | 0.3674170 | NA |
| 23 | 154927581 | rs644138 | G | A | 0.0007 | 0.0074 | 0.9255000 | 0.9246368 | 0.2880 | 0.4635760 | NA |
| 23 | 154928151 | rs144607509 | C | T | -0.0269 | 0.0552 | 0.6261004 | 0.6260324 | 0.0215 | 0.0084768 | NA |
| 23 | 154929412 | rs557132 | C | T | -0.0010 | 0.0077 | 0.8918001 | 0.8966692 | 0.2383 | 0.3568210 | NA |
| 23 | 154930230 | rs781880 | A | G | -0.0012 | 0.0077 | 0.8801000 | 0.8761559 | 0.2382 | 0.3618540 | NA |
bcf preview
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C . PASS AF=0.9925 ES:SE:LP:AF:ID 0.0001:0.0578:0.00056495:0.9925:rs376342519
1 10711 rs1434325972 A G . PASS AF=0.9924 ES:SE:LP:AF:ID -0.0303:0.0814:0.149048:0.9924:rs1434325972
1 11012 rs544419019 C G . PASS AF=0.0959 ES:SE:LP:AF:ID -0.0251:0.0158:0.948462:0.0959:rs544419019
1 13110 rs540538026 G A . PASS AF=0.0554 ES:SE:LP:AF:ID 0.0112:0.0297:0.150519:0.0554:rs540538026
1 13116 rs62635286 T G . PASS AF=0.1693 ES:SE:LP:AF:ID 0.0071:0.0141:0.211125:0.1693:rs62635286
1 13118 rs62028691 A G . PASS AF=0.1693 ES:SE:LP:AF:ID 0.0071:0.0141:0.211125:0.1693:rs62028691
1 13273 rs531730856 G C . PASS AF=0.1422 ES:SE:LP:AF:ID 0.0123:0.0154:0.373865:0.1422:rs531730856
1 13550 rs554008981 G A . PASS AF=0.0084 ES:SE:LP:AF:ID 0.1081:0.0927:0.613679:0.0084:rs554008981
1 13624 rs1304990809 C G . PASS AF=0.3062 ES:SE:LP:AF:ID -0.027:0.0165:0.993534:0.3062:rs1304990809
1 14464 rs546169444 A T . PASS AF=0.1614 ES:SE:LP:AF:ID -0.0105:0.0147:0.322393:0.1614:rs546169444
1 14521 rs1378626194 C T . PASS AF=0.9933 ES:SE:LP:AF:ID -0.1204:0.0603:1.34037:0.9933:rs1378626194
1 14523 rs1215163109 C T . PASS AF=0.9933 ES:SE:LP:AF:ID -0.1204:0.0603:1.34037:0.9933:rs1215163109
1 14599 rs707680 T A . PASS AF=0.1747 ES:SE:LP:AF:ID -0.0138:0.0172:0.372737:0.1747:rs707680
1 14604 rs541940975 A G . PASS AF=0.1747 ES:SE:LP:AF:ID -0.0138:0.0172:0.372634:0.1747:rs541940975
1 14867 rs1361043022 A G . PASS AF=0.543 ES:SE:LP:AF:ID 0.0341:0.015:1.64455:0.543:rs1361043022
1 14930 rs6682385 A G . PASS AF=0.5224 ES:SE:LP:AF:ID -0.0108:0.0103:0.527536:0.5224:rs6682385
1 14933 rs199856693 G A . PASS AF=0.0397 ES:SE:LP:AF:ID 0.0125:0.0282:0.182104:0.0397:rs199856693
1 15031 rs568188357 G A . PASS AF=0.9668 ES:SE:LP:AF:ID -0.003:0.0426:0.025074:0.9668:rs568188357
1 15211 rs3982632 T G . PASS AF=0.7087 ES:SE:LP:AF:ID 0.0047:0.0116:0.165134:0.7087:rs3982632
1 15274 rs2758118 A G . PASS AF=0.2916 ES:SE:LP:AF:ID -0.0029:0.0112:0.0999061:0.2916:rs2758118
1 15274 rs2758118 A T . PASS AF=0.7053 ES:SE:LP:AF:ID 0.0026:0.0112:0.0876716:0.7053:rs2758118
1 15339 rs1419228067 C T . PASS AF=0.0322 ES:SE:LP:AF:ID 0.0924:0.0294:2.77989:0.0322:rs1419228067
1 15644 rs564003018 G A . PASS AF=0.0058 ES:SE:LP:AF:ID -0.364:0.1043:3.31489:0.0058:rs564003018
1 15761 rs1269189092 A G . PASS AF=0.3053 ES:SE:LP:AF:ID -0.0261:0.0165:0.942334:0.3053:rs1269189092
1 15774 rs374029747 G A . PASS AF=0.007 ES:SE:LP:AF:ID -0.2633:0.0925:2.35193:0.007:rs374029747
1 15777 rs2691317 A G . PASS AF=0.0186 ES:SE:LP:AF:ID 0.0482:0.041:0.620332:0.0186:rs2691317
1 15811 rs1359290710 T C . PASS AF=0.5662 ES:SE:LP:AF:ID -0.0341:0.0151:1.63097:0.5662:rs1359290710
1 15820 rs2691315 G T . PASS AF=0.2969 ES:SE:LP:AF:ID 0.0008:0.0121:0.0245682:0.2969:rs2691315
1 15850 rs575961614 G A . PASS AF=0.0178 ES:SE:LP:AF:ID 0.0875:0.0455:1.26648:0.0178:rs575961614
1 15893 rs555382915 T C . PASS AF=0.6947 ES:SE:LP:AF:ID 0.026:0.0165:0.941574:0.6947:rs555382915
1 15903 rs557514207 G GC . PASS AF=0.4484 ES:SE:LP:AF:ID 0.0092:0.0105:0.419189:0.4484:rs557514207
1 16949 rs199745162 A C . PASS AF=0.0191 ES:SE:LP:AF:ID -0.006:0.0495:0.044168:0.0191:rs199745162
1 18022 rs1421734331 G A . PASS AF=0.5395 ES:SE:LP:AF:ID -0.0086:0.0156:0.235525:0.5395:rs1421734331
1 18849 rs533090414 C G . PASS AF=0.9821 ES:SE:LP:AF:ID 0.038:0.0436:0.415895:0.9821:rs533090414
1 19161 rs1459947110 G A . PASS AF=0.7498 ES:SE:LP:AF:ID -0.0001:0.0188:0.002046:0.7498:rs1459947110
1 19390 rs1190989798 C T . PASS AF=0.9917 ES:SE:LP:AF:ID 0.0646:0.0548:0.622876:0.9917:rs1190989798
1 20210 rs1341566117 G A . PASS AF=0.1427 ES:SE:LP:AF:ID -0.0298:0.0224:0.736838:0.1427:rs1341566117
1 29656 rs1361902895 C T . PASS AF=0.7607 ES:SE:LP:AF:ID 0.0277:0.0176:0.937418:0.7607:rs1361902895
1 30923 rs806731 G T . PASS AF=0.9282 ES:SE:LP:AF:ID 0.0468:0.0278:1.03428:0.9282:rs806731
1 47159 rs540662756 T C . PASS AF=0.0516 ES:SE:LP:AF:ID -0.0213:0.0244:0.417937:0.0516:rs540662756
1 48015 rs1328248850 A G . PASS AF=0.734 ES:SE:LP:AF:ID -0.0084:0.0161:0.222066:0.734:rs1328248850
1 49298 rs10399793 T C . PASS AF=0.8474 ES:SE:LP:AF:ID 0.0032:0.0153:0.0784696:0.8474:rs10399793
1 49554 rs539322794 A G . PASS AF=0.0898 ES:SE:LP:AF:ID 0.0052:0.025:0.077586:0.0898:rs539322794
1 51479 rs116400033 T A . PASS AF=0.2298 ES:SE:LP:AF:ID -0.0101:0.0127:0.372429:0.2298:rs116400033
1 51649 rs1184795044 G A . PASS AF=0.6241 ES:SE:LP:AF:ID 0.0139:0.0145:0.472757:0.6241:rs1184795044
1 51762 rs559190862 A G . PASS AF=0.0154 ES:SE:LP:AF:ID 0.0053:0.0442:0.0436875:0.0154:rs559190862
1 51765 rs575564077 C G . PASS AF=0.0154 ES:SE:LP:AF:ID 0.0053:0.0442:0.0436875:0.0154:rs575564077
1 52185 rs201374420 TTAA T . PASS AF=0.0065 ES:SE:LP:AF:ID -0.037:0.0958:0.155399:0.0065:rs201374420
1 52238 rs2691277 T G . PASS AF=0.9675 ES:SE:LP:AF:ID 0.0466:0.0432:0.552222:0.9675:rs2691277
1 52253 rs530867301 C G . PASS AF=0.0113 ES:SE:LP:AF:ID -0.0161:0.0675:0.0904975:0.0113:rs530867301