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": "2019-10-26T21:59:22.146995",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006586/EBI-a-GCST006586_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-GCST006586/EBI-a-GCST006586.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006586/EBI-a-GCST006586_data.vcf.gz; Date=Sat Oct 26 22:18:10 2019",
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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006586/ebi-a-GCST006586.vcf.gz; Date=Sun May 10 11:16:35 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-GCST006586/EBI-a-GCST006586.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-GCST006586/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 22:42:34 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006586/EBI-a-GCST006586.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 22:43:55 2019
Total time elapsed: 1.0m:20.98sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9533,
"inflation_factor": 1.1653,
"mean_EFFECT": -4.1639e-06,
"n": "-Inf",
"n_snps": 11684850,
"n_clumped_hits": 38,
"n_p_sig": 1675,
"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": 518145,
"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 | 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 | 64 | 0 | 11656289 | 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 | 11667950 | 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 | 8.632741e+00 | 5.759831e+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 | 7.892424e+07 | 5.624972e+07 | 828.0000000 | 3.270011e+07 | 6.961637e+07 | 1.145811e+08 | 2.492283e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -4.200000e-06 | 1.131080e-02 | -0.1295420 | -3.220800e-03 | -1.760000e-05 | 3.176200e-03 | 3.839540e-01 | ▁▇▁▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.124100e-03 | 7.566300e-03 | 0.0016538 | 2.112900e-03 | 4.494400e-03 | 1.254230e-02 | 4.914880e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.750860e-01 | 2.952425e-01 | 0.0000000 | 2.133138e-01 | 4.665530e-01 | 7.309388e-01 | 1.000000e+00 | ▇▇▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.750855e-01 | 2.952427e-01 | 0.0000000 | 2.133128e-01 | 4.665526e-01 | 7.309375e-01 | 9.999998e-01 | ▇▇▆▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.697883e-01 | 2.458976e-01 | 0.0010000 | 4.878400e-03 | 3.871630e-02 | 2.465700e-01 | 9.989990e-01 | ▇▁▁▁▁ |
| numeric | AF_reference | 518145 | 0.9555925 | NA | NA | NA | NA | NA | NA | NA | 1.770107e-01 | 2.405649e-01 | 0.0000000 | 3.394600e-03 | 6.010380e-02 | 2.663740e-01 | 1.000000e+00 | ▇▂▁▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 13169 | rs1436530583 | A | G | -0.0058613 | 0.0226964 | 0.7962151 | 0.7962148 | 0.9985420 | NA | NA |
| 1 | 15850 | rs575961614 | G | A | 0.0005526 | 0.0082323 | 0.9464860 | 0.9464862 | 0.0126043 | 0.0005990 | NA |
| 1 | 55326 | rs3107975 | T | C | 0.0138664 | 0.0164503 | 0.3992685 | 0.3992693 | 0.0024628 | 0.0459265 | NA |
| 1 | 55389 | rs1190986229 | T | C | 0.0060919 | 0.0163360 | 0.7092119 | 0.7092112 | 0.0037647 | NA | NA |
| 1 | 74356 | rs1374516807 | T | C | -0.0531140 | 0.0222333 | 0.0168978 | 0.0168971 | 0.9986180 | NA | NA |
| 1 | 82103 | rs2020400 | T | C | 0.0013912 | 0.0041094 | 0.7349537 | 0.7349526 | 0.9424290 | NA | NA |
| 1 | 86028 | rs114608975 | T | C | -0.0003634 | 0.0046830 | 0.9381401 | 0.9381400 | 0.0423959 | 0.0277556 | NA |
| 1 | 91311 | rs1354585492 | T | C | 0.0031813 | 0.0234575 | 0.8921229 | 0.8921229 | 0.9987490 | NA | NA |
| 1 | 121759 | rs975013924 | C | A | -0.0090759 | 0.0116137 | 0.4345212 | 0.4345194 | 0.0059176 | NA | NA |
| 1 | 123130 | rs1235743598 | T | C | 0.0164346 | 0.0179126 | 0.3588847 | 0.3588868 | 0.9977020 | NA | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51223637 | rs375798137 | G | A | -0.0023509 | 0.0037865 | 0.5346801 | 0.5346798 | 0.0540039 | 0.0788738 | NA |
| 22 | 51226692 | rs150189434 | G | A | 0.0106743 | 0.0229291 | 0.6415463 | 0.6415483 | 0.0013634 | 0.0155751 | NA |
| 22 | 51227766 | rs186062720 | T | C | -0.0102087 | 0.0215646 | 0.6359266 | 0.6359272 | 0.0018954 | 0.0005990 | NA |
| 22 | 51229805 | rs9616985 | T | C | 0.0032316 | 0.0032122 | 0.3143953 | 0.3143936 | 0.0734549 | 0.0730831 | NA |
| 22 | 51230673 | rs555680442 | G | C | -0.0007524 | 0.0220637 | 0.9727981 | 0.9727981 | 0.0016196 | 0.0017971 | NA |
| 22 | 51231424 | rs539541647 | A | G | -0.0101306 | 0.0259226 | 0.6959451 | 0.6959437 | 0.0014902 | 0.0011981 | NA |
| 22 | 51232488 | rs376461333 | A | G | -0.0025878 | 0.0075624 | 0.7322055 | 0.7322051 | 0.0123739 | NA | NA |
| 22 | 51234033 | rs764597437 | C | T | -0.0078950 | 0.0278643 | 0.7769177 | 0.7769171 | 0.0011464 | NA | NA |
| 22 | 51237063 | rs3896457 | T | C | -0.0009278 | 0.0019643 | 0.6366856 | 0.6366841 | 0.2968430 | 0.2050720 | NA |
| 22 | 51239586 | rs535432390 | T | G | 0.0351125 | 0.0177109 | 0.0474198 | 0.0474193 | 0.0032797 | 0.0001997 | NA |
bcf preview
1 13169 rs1436530583 A G . PASS AF=0.998542 ES:SE:LP:AF:ID -0.00586132:0.0226964:0.0989696:0.998542:rs1436530583
1 15850 rs575961614 G A . PASS AF=0.0126043 ES:SE:LP:AF:ID 0.000552552:0.0082323:0.0238858:0.0126043:rs575961614
1 55326 rs3107975 T C . PASS AF=0.00246275 ES:SE:LP:AF:ID 0.0138664:0.0164503:0.398735:0.00246275:rs3107975
1 55389 rs1190986229 T C . PASS AF=0.00376471 ES:SE:LP:AF:ID 0.00609195:0.016336:0.149224:0.00376471:rs1190986229
1 74356 rs1374516807 T C . PASS AF=0.998618 ES:SE:LP:AF:ID -0.053114:0.0222333:1.77217:0.998618:rs1374516807
1 82103 rs2020400 T C . PASS AF=0.942429 ES:SE:LP:AF:ID 0.00139123:0.00410944:0.13374:0.942429:rs2020400
1 86028 rs114608975 T C . PASS AF=0.0423959 ES:SE:LP:AF:ID -0.000363436:0.00468298:0.0277323:0.0423959:rs114608975
1 91311 rs1354585492 T C . PASS AF=0.998749 ES:SE:LP:AF:ID 0.00318127:0.0234575:0.0495753:0.998749:rs1354585492
1 121759 rs975013924 C A . PASS AF=0.00591765 ES:SE:LP:AF:ID -0.00907589:0.0116137:0.361989:0.00591765:rs975013924
1 123130 rs1235743598 T C . PASS AF=0.997702 ES:SE:LP:AF:ID 0.0164346:0.0179126:0.445045:0.997702:rs1235743598
1 174747 rs1399732465 C T . PASS AF=0.0114147 ES:SE:LP:AF:ID -0.00294248:0.00823842:0.142084:0.0114147:rs1399732465
1 234313 rs8179466 C T . PASS AF=0.0260356 ES:SE:LP:AF:ID 0.0102588:0.00567661:1.1504:0.0260356:rs8179466
1 526736 rs28863004 C G . PASS AF=0.00165098 ES:SE:LP:AF:ID 0.0113547:0.0199902:0.244105:0.00165098:rs28863004
1 534583 rs6683466 C G . PASS AF=0.00176341 ES:SE:LP:AF:ID -0.00713949:0.0187023:0.15326:0.00176341:rs6683466
1 565130 rs371431021 G A . PASS AF=0.00155425 ES:SE:LP:AF:ID -0.0338676:0.0206282:0.997268:0.00155425:rs371431021
1 567006 rs565235853 G T . PASS AF=0.0032732 ES:SE:LP:AF:ID -0.0119283:0.0182295:0.289975:0.0032732:rs565235853
1 568800 rs375217967 G A . PASS AF=0.00546677 ES:SE:LP:AF:ID -0.00740214:0.0113419:0.289044:0.00546677:rs375217967
1 601550 rs2491328 G A . PASS AF=0.00112157 ES:SE:LP:AF:ID 0.00637399:0.0240084:0.102025:0.00112157:rs2491328
1 612758 rs4387125 T C . PASS AF=0.00217647 ES:SE:LP:AF:ID -0.0283236:0.0170508:1.01463:0.00217647:rs4387125
1 693731 rs12238997 A G . PASS AF=0.116467 ES:SE:LP:AF:ID 0.000906831:0.00276794:0.128894:0.116467:rs12238997
1 705882 rs72631875 G A . PASS AF=0.0632592 ES:SE:LP:AF:ID -0.00794317:0.00405655:1.29914:0.0632592:rs72631875
1 705942 rs544671234 A T . PASS AF=0.0029098 ES:SE:LP:AF:ID 0.00124731:0.0180853:0.0245613:0.0029098:rs544671234
1 713092 rs4565649 G A . PASS AF=0.00151765 ES:SE:LP:AF:ID -0.00938627:0.0228779:0.166468:0.00151765:rs4565649
1 714277 rs138660747 C A . PASS AF=0.00539739 ES:SE:LP:AF:ID -0.00504755:0.0128318:0.158607:0.00539739:rs138660747
1 715205 rs141090730 C G . PASS AF=0.00154248 ES:SE:LP:AF:ID -0.00114224:0.0225921:0.0178749:0.00154248:rs141090730
1 717474 rs141784362 C T . PASS AF=0.00152157 ES:SE:LP:AF:ID -0.00154655:0.0228756:0.0240639:0.00152157:rs141784362
1 717587 rs144155419 G A . PASS AF=0.0143346 ES:SE:LP:AF:ID 0.00665749:0.00744075:0.430708:0.0143346:rs144155419
1 718624 rs777092529 C G . PASS AF=0.00131503 ES:SE:LP:AF:ID 0.0356364:0.027977:0.693052:0.00131503:rs777092529
1 718625 rs762187552 T G . PASS AF=0.00131503 ES:SE:LP:AF:ID 0.0356364:0.027977:0.693052:0.00131503:rs762187552
1 720583 rs551231909 G A . PASS AF=0.00133987 ES:SE:LP:AF:ID 0.0336642:0.0246101:0.766134:0.00133987:rs551231909
1 720984 rs564367954 T G . PASS AF=0.0019268 ES:SE:LP:AF:ID 0.0381302:0.0247224:0.910116:0.0019268:rs564367954
1 722559 rs150361918 T C . PASS AF=0.00151503 ES:SE:LP:AF:ID 0.00318595:0.0227519:0.0512761:0.00151503:rs150361918
1 722603 rs138029171 T C . PASS AF=0.00132157 ES:SE:LP:AF:ID 0.027078:0.0247717:0.561695:0.00132157:rs138029171
1 722670 rs116030099 T C . PASS AF=0.0920042 ES:SE:LP:AF:ID 0.00188576:0.0033768:0.239171:0.0920042:rs116030099
1 722980 rs114222710 C T . PASS AF=0.00150588 ES:SE:LP:AF:ID 0.00198327:0.0229487:0.0309892:0.00150588:rs114222710
1 723918 rs144434834 G A . PASS AF=0.00146797 ES:SE:LP:AF:ID -0.00505648:0.0232434:0.082083:0.00146797:rs144434834
1 724849 rs12126395 C A . PASS AF=0.0113222 ES:SE:LP:AF:ID 0.00187556:0.00804775:0.0884594:0.0113222:rs12126395
1 725060 rs865924913 A T . PASS AF=0.0191918 ES:SE:LP:AF:ID 0.00143385:0.00644621:0.0840849:0.0191918:rs865924913
1 725401 rs553642122 C T . PASS AF=0.00824577 ES:SE:LP:AF:ID 0.00718524:0.0107379:0.298086:0.00824577:rs553642122
1 730087 rs148120343 T C . PASS AF=0.0552928 ES:SE:LP:AF:ID 0.00081714:0.0038541:0.0798281:0.0552928:rs148120343
1 731048 rs548444285 C T . PASS AF=0.00147059 ES:SE:LP:AF:ID -0.00376968:0.0233717:0.0595518:0.00147059:rs548444285
1 731453 rs186002080 G A . PASS AF=0.0113843 ES:SE:LP:AF:ID 0.00487301:0.00881204:0.236371:0.0113843:rs186002080
1 731718 rs58276399 T C . PASS AF=0.121258 ES:SE:LP:AF:ID 0.000442871:0.0026255:0.062458:0.121258:rs58276399
1 732120 rs114572157 T C . PASS AF=0.00158824 ES:SE:LP:AF:ID 0.00370861:0.0222313:0.061724:0.00158824:rs114572157
1 732801 rs144022023 A G . PASS AF=0.00151634 ES:SE:LP:AF:ID -0.00821051:0.0228274:0.143218:0.00151634:rs144022023
1 732989 rs369030935 C T . PASS AF=0.0256027 ES:SE:LP:AF:ID 0.00246054:0.00637778:0.155122:0.0256027:rs369030935
1 733013 rs4951860 T C . PASS AF=0.00285359 ES:SE:LP:AF:ID 0.0186517:0.0180312:0.521513:0.00285359:rs4951860
1 733819 rs187923271 A G . PASS AF=0.00366536 ES:SE:LP:AF:ID -0.0159901:0.0177458:0.434678:0.00366536:rs187923271
1 734349 rs141242758 T C . PASS AF=0.121124 ES:SE:LP:AF:ID 0.00033008:0.00262713:0.0457503:0.121124:rs141242758
1 734383 rs144952147 G A . PASS AF=0.0015281 ES:SE:LP:AF:ID 0.00635208:0.0226188:0.108552:0.0015281:rs144952147