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": "2019-10-27T07:18:47.693673",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST000998/EBI-a-GCST000998_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-GCST000998/EBI-a-GCST000998.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST000998/EBI-a-GCST000998_data.vcf.gz; Date=Sun Oct 27 07:22:55 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST000998/ebi-a-GCST000998.vcf.gz; Date=Sun May 10 14:11:07 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-GCST000998/EBI-a-GCST000998.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-GCST000998/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 Sun Oct 27 07:45:40 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST000998/EBI-a-GCST000998.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 Sun Oct 27 07:45:56 2019
Total time elapsed: 15.75sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9212,
"inflation_factor": 1.0966,
"mean_EFFECT": 0,
"n": "-Inf",
"n_snps": 2415017,
"n_clumped_hits": 15,
"n_p_sig": 159,
"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": 18814,
"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 | 42 | 0 | 2408875 | 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 | 2408881 | 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 | 8.574173e+00 | 5.648785e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.200000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.890547e+07 | 5.563996e+07 | 1.15230e+04 | 3.274525e+07 | 7.037483e+07 | 1.143482e+08 | 2.492190e+08 | ▇▇▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.190000e-05 | 2.776550e-02 | -1.10961e+00 | -1.413890e-02 | -1.052000e-04 | 1.391550e-02 | 1.086030e+00 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.298130e-02 | 1.417830e-02 | 1.36136e-02 | 1.509380e-02 | 1.804230e-02 | 2.471860e-02 | 5.506900e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.845573e-01 | 2.938421e-01 | 0.00000e+00 | 2.261674e-01 | 4.799876e-01 | 7.397773e-01 | 9.999996e-01 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.845573e-01 | 2.938421e-01 | 0.00000e+00 | 2.261676e-01 | 4.799876e-01 | 7.397764e-01 | 9.999996e-01 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.644524e-01 | 2.633891e-01 | 1.00000e-02 | 1.376580e-01 | 3.022260e-01 | 5.567510e-01 | 9.900000e-01 | ▇▅▃▃▂ |
| numeric | AF_reference | 18814 | 0.9921897 | NA | NA | NA | NA | NA | NA | NA | 3.632832e-01 | 2.544372e-01 | 1.99700e-04 | 1.493610e-01 | 3.021170e-01 | 5.469250e-01 | 1.000000e+00 | ▇▆▅▃▂ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 721290 | rs12565286 | G | C | 0.1282010 | 0.0695073 | 0.0651208 | 0.0651212 | 0.0538073 | 0.0371406 | NA |
| 1 | 723819 | rs11804171 | T | A | 0.1297870 | 0.0698828 | 0.0632820 | 0.0632814 | 0.0540315 | 0.1345850 | NA |
| 1 | 752566 | rs3094315 | G | A | -0.0016609 | 0.0291187 | 0.9545153 | 0.9545142 | 0.8249000 | 0.7182510 | NA |
| 1 | 754192 | rs3131968 | A | G | -0.0289617 | 0.0314537 | 0.3571692 | 0.3571692 | 0.7698700 | 0.6785140 | NA |
| 1 | 775659 | rs2905035 | A | G | -0.0040285 | 0.0272131 | 0.8823145 | 0.8823149 | 0.8198740 | 0.7450080 | NA |
| 1 | 777122 | rs2980319 | A | T | -0.0009125 | 0.0270433 | 0.9730835 | 0.9730827 | 0.8205390 | 0.7472040 | NA |
| 1 | 779322 | rs4040617 | A | G | -0.0017451 | 0.0268361 | 0.9481510 | 0.9481516 | 0.1365300 | 0.2264380 | NA |
| 1 | 780785 | rs2977612 | T | A | -0.0000365 | 0.0271406 | 0.9989267 | 0.9989270 | 0.8634140 | 0.6693290 | NA |
| 1 | 785050 | rs2905062 | G | A | 0.0002458 | 0.0270487 | 0.9927509 | 0.9927495 | 0.8619550 | 0.6269970 | NA |
| 1 | 785989 | rs2980300 | T | C | 0.0054738 | 0.0259561 | 0.8329753 | 0.8329756 | 0.8537800 | 0.6269970 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51163138 | rs715586 | C | T | -0.0094937 | 0.0231196 | 0.6813402 | 0.6813407 | 0.1594360 | 0.0902556 | NA |
| 22 | 51165664 | rs8137951 | G | A | 0.0125211 | 0.0182524 | 0.4927118 | 0.4927147 | 0.3178670 | 0.4063500 | NA |
| 22 | 51171693 | rs756638 | G | A | -0.0486490 | 0.0248341 | 0.0501176 | 0.0501175 | 0.2416790 | 0.3049120 | NA |
| 22 | 51175626 | rs3810648 | A | G | 0.0072231 | 0.0345634 | 0.8344619 | 0.8344629 | 0.0531682 | 0.1084270 | NA |
| 22 | 51178090 | rs2285395 | G | A | -0.0070760 | 0.0377561 | 0.8513374 | 0.8513365 | 0.0834911 | 0.0666933 | NA |
| 22 | 51196164 | rs8136603 | A | T | -0.0258867 | 0.0548093 | 0.6367090 | 0.6367092 | 0.0434938 | 0.1427720 | NA |
| 22 | 51222100 | rs114553188 | G | T | -0.0301543 | 0.0550702 | 0.5839935 | 0.5839933 | 0.0472308 | 0.0880591 | NA |
| 22 | 51223637 | rs375798137 | G | A | -0.0297975 | 0.0551675 | 0.5891081 | 0.5891089 | 0.0469412 | 0.0788738 | NA |
| 23 | 91415872 | rs6562597 | G | A | 0.0540302 | 0.0516399 | 0.2954282 | 0.2954282 | 0.0192669 | 0.0021192 | NA |
| 23 | 118495837 | rs12882977 | G | A | -0.0037640 | 0.0140319 | 0.7885078 | 0.7885100 | 0.5037110 | 0.2307280 | NA |
bcf preview
1 721290 rs12565286 G C . PASS AF=0.0538073 ES:SE:LP:AF:ID 0.128201:0.0695073:1.18628:0.0538073:rs12565286
1 723819 rs11804171 T A . PASS AF=0.0540315 ES:SE:LP:AF:ID 0.129787:0.0698828:1.19872:0.0540315:rs11804171
1 752566 rs3094315 G A . PASS AF=0.8249 ES:SE:LP:AF:ID -0.0016609:0.0291187:0.0202171:0.8249:rs3094315
1 754192 rs3131968 A G . PASS AF=0.76987 ES:SE:LP:AF:ID -0.0289617:0.0314537:0.447126:0.76987:rs3131968
1 775659 rs2905035 A G . PASS AF=0.819874 ES:SE:LP:AF:ID -0.0040285:0.0272131:0.0543766:0.819874:rs2905035
1 777122 rs2980319 A T . PASS AF=0.820539 ES:SE:LP:AF:ID -0.0009125:0.0270433:0.0118499:0.820539:rs2980319
1 779322 rs4040617 A G . PASS AF=0.13653 ES:SE:LP:AF:ID -0.0017451:0.0268361:0.0231225:0.13653:rs4040617
1 780785 rs2977612 T A . PASS AF=0.863414 ES:SE:LP:AF:ID -3.65e-05:0.0271406:0.000466379:0.863414:rs2977612
1 785050 rs2905062 G A . PASS AF=0.861955 ES:SE:LP:AF:ID 0.0002458:0.0270487:0.00315971:0.861955:rs2905062
1 785989 rs2980300 T C . PASS AF=0.85378 ES:SE:LP:AF:ID 0.0054738:0.0259561:0.0793679:0.85378:rs2980300
1 798959 rs11240777 G A . PASS AF=0.206126 ES:SE:LP:AF:ID 0.008975:0.0302654:0.115309:0.206126:rs11240777
1 990380 rs3121561 C T . PASS AF=0.295 ES:SE:LP:AF:ID 0.028:0.0329999:0.402123:0.295:rs3121561
1 998501 rs3813193 G C . PASS AF=0.182651 ES:SE:LP:AF:ID 0.0034016:0.0303734:0.0405632:0.182651:rs3813193
1 1003629 rs4075116 C T . PASS AF=0.742152 ES:SE:LP:AF:ID -0.0187703:0.0217113:0.41196:0.742152:rs4075116
1 1005806 rs3934834 C T . PASS AF=0.159137 ES:SE:LP:AF:ID -0.0070263:0.0292219:0.0915229:0.159137:rs3934834
1 1017170 rs3766193 C G . PASS AF=0.550892 ES:SE:LP:AF:ID -0.0157586:0.0210754:0.342345:0.550892:rs3766193
1 1017197 rs3766192 C T . PASS AF=0.561968 ES:SE:LP:AF:ID -0.0051995:0.0283805:0.0682184:0.561968:rs3766192
1 1017587 rs3766191 C T . PASS AF=0.144423 ES:SE:LP:AF:ID 0.0099465:0.0314343:0.123965:0.144423:rs3766191
1 1018562 rs9442371 C T . PASS AF=0.573923 ES:SE:LP:AF:ID -0.011991:0.0182782:0.290895:0.573923:rs9442371
1 1018704 rs9442372 A G . PASS AF=0.57237 ES:SE:LP:AF:ID -0.0130313:0.0181211:0.325997:0.57237:rs9442372
1 1021346 rs10907177 A G . PASS AF=0.143209 ES:SE:LP:AF:ID 0.0180932:0.0324983:0.238296:0.143209:rs10907177
1 1021415 rs3737728 A G . PASS AF=0.722623 ES:SE:LP:AF:ID -0.0074473:0.0223225:0.131552:0.722623:rs3737728
1 1021583 rs10907178 A C . PASS AF=0.142127 ES:SE:LP:AF:ID 0.0197099:0.0325366:0.263871:0.142127:rs10907178
1 1021695 rs9442398 A G . PASS AF=0.729993 ES:SE:LP:AF:ID -0.0036201:0.0235499:0.0565891:0.729993:rs9442398
1 1022037 rs6701114 C T . PASS AF=0.5547 ES:SE:LP:AF:ID -0.0185:0.0519:0.141764:0.5547:rs6701114
1 1026707 rs4074137 C A . PASS AF=0.626 ES:SE:LP:AF:ID -0.046:0.0252999:1.16093:0.626:rs4074137
1 1030565 rs6687776 C T . PASS AF=0.144064 ES:SE:LP:AF:ID 0.0497435:0.0281564:1.11193:0.144064:rs6687776
1 1030633 rs6678318 G A . PASS AF=0.142872 ES:SE:LP:AF:ID 0.0509073:0.0282022:1.14836:0.142872:rs6678318
1 1031540 rs9651273 A G . PASS AF=0.747557 ES:SE:LP:AF:ID -0.014647:0.0248585:0.255145:0.747557:rs9651273
1 1036959 rs11579015 T C . PASS AF=0.0898438 ES:SE:LP:AF:ID 0.0532598:0.0296054:1.14254:0.0898438:rs11579015
1 1040026 rs6671356 T C . PASS AF=0.129024 ES:SE:LP:AF:ID 0.0409805:0.0289901:0.802777:0.129024:rs6671356
1 1046164 rs6666280 C T . PASS AF=0.119357 ES:SE:LP:AF:ID 0.0437258:0.0260782:1.02874:0.119357:rs6666280
1 1048955 rs4970405 A G . PASS AF=0.0942422 ES:SE:LP:AF:ID 0.0707107:0.0283715:1.89649:0.0942422:rs4970405
1 1049950 rs12726255 A G . PASS AF=0.12066 ES:SE:LP:AF:ID 0.0488419:0.0275424:1.1182:0.12066:rs12726255
1 1053452 rs4970409 G A . PASS AF=0.0907357 ES:SE:LP:AF:ID 0.0510508:0.0291704:1.09635:0.0907357:rs4970409
1 1060174 rs7548798 C T . PASS AF=0.322014 ES:SE:LP:AF:ID 0.0331473:0.0290897:0.594312:0.322014:rs7548798
1 1060235 rs7540009 G A . PASS AF=0.035 ES:SE:LP:AF:ID -0.011:0.0626997:0.0651308:0.035:rs7540009
1 1060608 rs17160824 G A . PASS AF=0.0974642 ES:SE:LP:AF:ID 0.0511532:0.0293633:1.08887:0.0974642:rs17160824
1 1061115 rs17160826 T C . PASS AF=0.089626 ES:SE:LP:AF:ID 0.0505149:0.029373:1.06817:0.089626:rs17160826
1 1061152 rs12748370 T C . PASS AF=0.0919812 ES:SE:LP:AF:ID 0.0441971:0.0300373:0.850224:0.0919812:rs12748370
1 1061166 rs11807848 T C . PASS AF=0.401254 ES:SE:LP:AF:ID 0.0674:0.0257956:2.04676:0.401254:rs11807848
1 1062015 rs9659914 C T . PASS AF=0.034 ES:SE:LP:AF:ID -0.012:0.0648997:0.0688947:0.034:rs9659914
1 1062638 rs9442373 C A . PASS AF=0.557813 ES:SE:LP:AF:ID -0.0657354:0.0247604:2.1005:0.557813:rs9442373
1 1064535 rs6682475 G C . PASS AF=0.73 ES:SE:LP:AF:ID -0.027:0.0340999:0.368068:0.73:rs6682475
1 1064979 rs2298217 C T . PASS AF=0.126426 ES:SE:LP:AF:ID 0.0435369:0.0292475:0.864547:0.126426:rs2298217
1 1077064 rs4970357 C A . PASS AF=0.918735 ES:SE:LP:AF:ID 0.0117037:0.0462911:0.0966923:0.918735:rs4970357
1 1079198 rs11260603 T C . PASS AF=0.227 ES:SE:LP:AF:ID 0.031:0.0329999:0.459012:0.227:rs11260603
1 1087683 rs9442380 T C . PASS AF=0.914628 ES:SE:LP:AF:ID 0.007653:0.0364682:0.0789475:0.914628:rs9442380
1 1089262 rs4970358 A G . PASS AF=0.954487 ES:SE:LP:AF:ID 0.0374554:0.0554406:0.301641:0.954487:rs4970358
1 1094738 rs4970362 A G . PASS AF=0.615243 ES:SE:LP:AF:ID -0.0058565:0.0217067:0.103853:0.615243:rs4970362