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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"gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_3144.vcf.gz --id UKB-b:15851 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_3144.txt.gz --cohort_controls 265737 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
"file_date": "2019-09-12T19:35:20.456322",
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"bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-15851/ukb-b-15851.vcf.gz; Date=Sun May 10 10:41:27 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/public/UKB-b-15851/UKB-b-15851_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15851/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:44:30 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-15851/UKB-b-15851_data.vcf.gz ...
Read summary statistics for 9674813 SNPs.
Dropped 13097 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1288733 SNPs remain.
After merging with regression SNP LD, 1288733 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2545 (0.0213)
Lambda GC: 1.6369
Mean Chi^2: 2.6092
Intercept: 1.1852 (0.0166)
Ratio: 0.1151 (0.0103)
Analysis finished at Thu Oct 17 14:46:11 2019
Total time elapsed: 1.0m:41.27sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9495,
"inflation_factor": 1.4295,
"mean_EFFECT": 0,
"n": "-Inf",
"n_snps": 9851866,
"n_clumped_hits": 327,
"n_p_sig": 53334,
"n_mono": 0,
"n_ns": 0,
"n_mac": 0,
"is_snpid_unique": true,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 159220,
"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": 1288733,
"ldsc_nsnp_merge_regression_ld": 1288733,
"ldsc_observed_scale_h2_beta": 0.2545,
"ldsc_observed_scale_h2_se": 0.0213,
"ldsc_intercept_beta": 1.1852,
"ldsc_intercept_se": 0.0166,
"ldsc_lambda_gc": 1.6369,
"ldsc_mean_chisq": 2.6092,
"ldsc_ratio": 0.1151
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | TRUE |
| n | TRUE |
| is_snpid_non_unique | FALSE |
| 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 | FALSE |
| ldsc_intercept_beta | FALSE |
| 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 | 9661781 | 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 | 9674813 | 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 | 8.625682e+00 | 5.749909e+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 | 7.884110e+07 | 5.629180e+07 | 828.0000000 | 3.256554e+07 | 6.944565e+07 | 1.145705e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.930000e-05 | 1.216030e-02 | -0.2207200 | -4.333900e-03 | 7.100000e-06 | 4.349500e-03 | 3.047960e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.156300e-03 | 7.255400e-03 | 0.0024301 | 2.959600e-03 | 4.865600e-03 | 1.098060e-02 | 1.250840e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.404668e-01 | 3.054876e-01 | 0.0000000 | 1.600000e-01 | 4.199997e-01 | 7.099994e-01 | 1.000000e+00 | ▇▆▅▅▅ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.404685e-01 | 3.054645e-01 | 0.0000000 | 1.600684e-01 | 4.194388e-01 | 7.051489e-01 | 1.000000e+00 | ▇▅▅▅▅ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.065162e-01 | 2.569902e-01 | 0.0013180 | 1.442100e-02 | 8.227800e-02 | 3.224240e-01 | 9.986820e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 159220 | 0.9835428 | NA | NA | NA | NA | NA | NA | NA | 2.089749e-01 | 2.486177e-01 | 0.0000000 | 1.257990e-02 | 1.030350e-01 | 3.248800e-01 | 1.000000e+00 | ▇▂▁▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 49298 | rs200943160 | T | C | -0.0062866 | 0.0044599 | 0.1600000 | 0.1586597 | 0.623765 | 0.7821490 | NA |
| 1 | 54676 | rs2462492 | C | T | 0.0099556 | 0.0044104 | 0.0239999 | 0.0239904 | 0.400852 | NA | NA |
| 1 | 86028 | rs114608975 | T | C | -0.0034851 | 0.0070767 | 0.6200004 | 0.6223864 | 0.103357 | 0.0277556 | NA |
| 1 | 91536 | rs6702460 | G | T | -0.0013214 | 0.0043466 | 0.7600007 | 0.7611228 | 0.456895 | 0.4207270 | NA |
| 1 | 234313 | rs8179466 | C | T | -0.0138828 | 0.0085500 | 0.1000000 | 0.1044369 | 0.074613 | NA | NA |
| 1 | 534192 | rs6680723 | C | T | -0.0020507 | 0.0049632 | 0.6800001 | 0.6794743 | 0.240670 | NA | NA |
| 1 | 546697 | rs12025928 | A | G | 0.0165512 | 0.0061922 | 0.0075000 | 0.0075198 | 0.913407 | NA | NA |
| 1 | 693731 | rs12238997 | A | G | -0.0037191 | 0.0041573 | 0.3700002 | 0.3710076 | 0.116482 | 0.1417730 | NA |
| 1 | 705882 | rs72631875 | G | A | -0.0065979 | 0.0060955 | 0.2800000 | 0.2790685 | 0.067530 | 0.0315495 | NA |
| 1 | 706368 | rs55727773 | A | G | -0.0038392 | 0.0030861 | 0.2099999 | 0.2134901 | 0.516344 | 0.2751600 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51219704 | rs147475742 | G | A | -0.0038457 | 0.0065123 | 0.5500004 | 0.5548354 | 0.042043 | 0.0473243 | NA |
| 22 | 51219766 | rs182321900 | C | T | -0.0216515 | 0.0300946 | 0.4700002 | 0.4718649 | 0.001975 | NA | NA |
| 22 | 51220146 | rs868950473 | C | T | -0.0236361 | 0.0298930 | 0.4299995 | 0.4291248 | 0.002015 | NA | NA |
| 22 | 51221190 | rs369304721 | G | A | 0.0009197 | 0.0064928 | 0.8900000 | 0.8873570 | 0.049831 | NA | NA |
| 22 | 51221731 | rs115055839 | T | C | -0.0043961 | 0.0048606 | 0.3700002 | 0.3657708 | 0.073399 | 0.0625000 | NA |
| 22 | 51222100 | rs114553188 | G | T | 0.0021138 | 0.0057208 | 0.7099994 | 0.7117643 | 0.054625 | 0.0880591 | NA |
| 22 | 51223637 | rs375798137 | G | A | 0.0017394 | 0.0057476 | 0.7600007 | 0.7621708 | 0.054265 | 0.0788738 | NA |
| 22 | 51229805 | rs9616985 | T | C | -0.0041529 | 0.0048780 | 0.3900004 | 0.3945793 | 0.073235 | 0.0730831 | NA |
| 22 | 51232488 | rs376461333 | A | G | -0.0028879 | 0.0115040 | 0.8000000 | 0.8017841 | 0.020020 | NA | NA |
| 22 | 51237063 | rs3896457 | T | C | -0.0027616 | 0.0029901 | 0.3599996 | 0.3556941 | 0.297735 | 0.2050720 | NA |
bcf preview
1 49298 rs10399793 T C . PASS AF=0.623765 ES:SE:LP:AF:ID -0.00628659:0.00445986:0.79588:0.623765:rs10399793
1 54676 rs2462492 C T . PASS AF=0.400852 ES:SE:LP:AF:ID 0.00995561:0.00441044:1.61979:0.400852:rs2462492
1 86028 rs114608975 T C . PASS AF=0.103357 ES:SE:LP:AF:ID -0.00348508:0.00707672:0.207608:0.103357:rs114608975
1 91536 rs6702460 G T . PASS AF=0.456895 ES:SE:LP:AF:ID -0.00132138:0.00434655:0.119186:0.456895:rs6702460
1 234313 rs8179466 C T . PASS AF=0.074613 ES:SE:LP:AF:ID -0.0138828:0.00855003:1:0.074613:rs8179466
1 534192 rs6680723 C T . PASS AF=0.24067 ES:SE:LP:AF:ID -0.00205069:0.00496318:0.167491:0.24067:rs6680723
1 546697 rs12025928 A G . PASS AF=0.913407 ES:SE:LP:AF:ID 0.0165512:0.00619222:2.12494:0.913407:rs12025928
1 693731 rs12238997 A G . PASS AF=0.116482 ES:SE:LP:AF:ID -0.00371906:0.00415729:0.431798:0.116482:rs12238997
1 705882 rs72631875 G A . PASS AF=0.06753 ES:SE:LP:AF:ID -0.0065979:0.00609554:0.552842:0.06753:rs72631875
1 706368 rs12029736 A G . PASS AF=0.516344 ES:SE:LP:AF:ID -0.0038392:0.00308611:0.677781:0.516344:rs12029736
1 714596 rs149887893 T C . PASS AF=0.032865 ES:SE:LP:AF:ID -0.00260938:0.00780234:0.130768:0.032865:rs149887893
1 715265 rs12184267 C T . PASS AF=0.036468 ES:SE:LP:AF:ID -0.00308246:0.00708622:0.180456:0.036468:rs12184267
1 715367 rs12184277 A G . PASS AF=0.036588 ES:SE:LP:AF:ID -0.00155577:0.0070591:0.0809219:0.036588:rs12184277
1 717485 rs12184279 C A . PASS AF=0.036301 ES:SE:LP:AF:ID -0.00169466:0.00710912:0.091515:0.036301:rs12184279
1 717587 rs144155419 G A . PASS AF=0.016402 ES:SE:LP:AF:ID 0.00561168:0.0109025:0.21467:0.016402:rs144155419
1 720381 rs116801199 G T . PASS AF=0.036811 ES:SE:LP:AF:ID -0.00121185:0.00703259:0.0655015:0.036811:rs116801199
1 721290 rs12565286 G C . PASS AF=0.036914 ES:SE:LP:AF:ID -0.00175664:0.00700729:0.09691:0.036914:rs12565286
1 722670 rs116030099 T C . PASS AF=0.101107 ES:SE:LP:AF:ID 0.00100152:0.00509643:0.0757207:0.101107:rs116030099
1 723891 rs2977670 G C . PASS AF=0.959294 ES:SE:LP:AF:ID 0.000469982:0.00675632:0.0268721:0.959294:rs2977670
1 724849 rs12126395 C A . PASS AF=0.031365 ES:SE:LP:AF:ID 0.00126504:0.0122435:0.0362122:0.031365:rs12126395
1 725060 rs865924913 A T . PASS AF=0.053453 ES:SE:LP:AF:ID 0.014519:0.0096753:0.886057:0.053453:rs865924913
1 726794 rs28454925 C G . PASS AF=0.036457 ES:SE:LP:AF:ID -0.0030164:0.00705041:0.173925:0.036457:rs28454925
1 729632 rs116720794 C T . PASS AF=0.036764 ES:SE:LP:AF:ID -0.00317168:0.00698629:0.187087:0.036764:rs116720794
1 729679 rs4951859 C G . PASS AF=0.843248 ES:SE:LP:AF:ID 0.00327419:0.00360713:0.443698:0.843248:rs4951859
1 730087 rs148120343 T C . PASS AF=0.056046 ES:SE:LP:AF:ID -0.00940236:0.00582929:0.958607:0.056046:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122479 ES:SE:LP:AF:ID -0.00501411:0.00394361:0.69897:0.122479:rs58276399
1 732989 rs369030935 C T . PASS AF=0.025603 ES:SE:LP:AF:ID -0.000799212:0.00974202:0.0315171:0.025603:rs369030935
1 734349 rs141242758 T C . PASS AF=0.121733 ES:SE:LP:AF:ID -0.00521525:0.00394479:0.721246:0.121733:rs141242758
1 736289 rs79010578 T A . PASS AF=0.132454 ES:SE:LP:AF:ID -0.00524626:0.00389092:0.744727:0.132454:rs79010578
1 736689 rs181876450 T C . PASS AF=0.010992 ES:SE:LP:AF:ID -0.00633008:0.0142883:0.180456:0.010992:rs181876450
1 740284 rs61770167 C T . PASS AF=0.005761 ES:SE:LP:AF:ID -0.00579178:0.0181798:0.124939:0.005761:rs61770167
1 742813 rs112573343 C T . PASS AF=0.002278 ES:SE:LP:AF:ID 0.0562084:0.0305429:1.18046:0.002278:rs112573343
1 752478 rs146277091 G A . PASS AF=0.036683 ES:SE:LP:AF:ID -0.00167499:0.00691449:0.091515:0.036683:rs146277091
1 752566 rs3094315 G A . PASS AF=0.838959 ES:SE:LP:AF:ID 0.00203883:0.00349321:0.251812:0.838959:rs3094315
1 752721 rs3131972 A G . PASS AF=0.838586 ES:SE:LP:AF:ID 0.00207645:0.00348949:0.259637:0.838586:rs3131972
1 753405 rs3115860 C A . PASS AF=0.869671 ES:SE:LP:AF:ID 0.00274604:0.0037433:0.337242:0.869671:rs3115860
1 753541 rs2073813 G A . PASS AF=0.129966 ES:SE:LP:AF:ID -0.00312612:0.00375052:0.39794:0.129966:rs2073813
1 754063 rs12184312 G T . PASS AF=0.037182 ES:SE:LP:AF:ID -0.00174731:0.00679738:0.09691:0.037182:rs12184312
1 754105 rs12184325 C T . PASS AF=0.037421 ES:SE:LP:AF:ID -0.00168752:0.00675477:0.09691:0.037421:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869014 ES:SE:LP:AF:ID 0.00264896:0.00373598:0.318759:0.869014:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869095 ES:SE:LP:AF:ID 0.00265201:0.00373723:0.318759:0.869095:rs3131968
1 754211 rs12184313 G A . PASS AF=0.037395 ES:SE:LP:AF:ID -0.0020438:0.0067835:0.119186:0.037395:rs12184313
1 754334 rs3131967 T C . PASS AF=0.869018 ES:SE:LP:AF:ID 0.00263047:0.00373601:0.318759:0.869018:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00515 ES:SE:LP:AF:ID 0.0163971:0.0191142:0.408935:0.00515:rs150578204
1 754458 rs142682604 G T . PASS AF=0.005114 ES:SE:LP:AF:ID 0.0170712:0.0191668:0.431798:0.005114:rs142682604
1 754503 rs3115859 G A . PASS AF=0.838018 ES:SE:LP:AF:ID 0.00195862:0.00347934:0.244125:0.838018:rs3115859
1 754629 rs10454459 A G . PASS AF=0.037413 ES:SE:LP:AF:ID -0.00233755:0.00679295:0.136677:0.037413:rs10454459
1 754964 rs3131966 C T . PASS AF=0.838653 ES:SE:LP:AF:ID 0.00206906:0.00348918:0.259637:0.838653:rs3131966
1 755240 rs181660517 T G . PASS AF=0.014036 ES:SE:LP:AF:ID 0.023372:0.0120443:1.284:0.014036:rs181660517
1 755435 rs184270342 T G . PASS AF=0.005534 ES:SE:LP:AF:ID -0.0294268:0.0188549:0.920819:0.005534:rs184270342