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_2492.vcf.gz --id UKB-b:20292 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_2492.txt.gz --cohort_cases 216598 --cohort_controls 244734 --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": "2019-09-12T19:35:54.617560",
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"bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-20292/ukb-b-20292.vcf.gz; Date=Sat May 9 18:38:40 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-20292/UKB-b-20292_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20292/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:42:07 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-20292/UKB-b-20292_data.vcf.gz ...
Read summary statistics for 9552460 SNPs.
Dropped 12029 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, 1288483 SNPs remain.
After merging with regression SNP LD, 1288483 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0403 (0.0018)
Lambda GC: 1.324
Mean Chi^2: 1.3968
Intercept: 1.035 (0.0077)
Ratio: 0.0882 (0.0193)
Analysis finished at Thu Oct 17 14:43:54 2019
Total time elapsed: 1.0m:46.81sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9492,
"inflation_factor": 1.1999,
"mean_EFFECT": 6.2457e-06,
"n": "-Inf",
"n_snps": 9851866,
"n_clumped_hits": 27,
"n_p_sig": 4128,
"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": 140087,
"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": 1288483,
"ldsc_nsnp_merge_regression_ld": 1288483,
"ldsc_observed_scale_h2_beta": 0.0403,
"ldsc_observed_scale_h2_se": 0.0018,
"ldsc_intercept_beta": 1.035,
"ldsc_intercept_se": 0.0077,
"ldsc_lambda_gc": 1.324,
"ldsc_mean_chisq": 1.3968,
"ldsc_ratio": 0.0882
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| 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 | 1.000000 | 3 | 58 | 0 | 9540492 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | N | 9552460 | 0.000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 8.628277e+00 | 5.751183e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▃▂▂ |
| numeric | POS | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 7.883395e+07 | 5.630286e+07 | 828.0000000 | 3.254714e+07 | 6.942603e+07 | 1.145670e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 6.200000e-06 | 4.386300e-03 | -0.0680821 | -1.588400e-03 | 2.200000e-06 | 1.602100e-03 | 8.495430e-02 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 3.215300e-03 | 2.739300e-03 | 0.0009996 | 1.211900e-03 | 1.966100e-03 | 4.363400e-03 | 3.654350e-02 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 4.666615e-01 | 2.979536e-01 | 0.0000000 | 2.000000e-01 | 4.600002e-01 | 7.199992e-01 | 1.000000e+00 | ▇▆▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 4.666610e-01 | 2.979282e-01 | 0.0000000 | 2.001317e-01 | 4.554609e-01 | 7.246232e-01 | 9.999997e-01 | ▇▆▆▆▆ |
| numeric | AF | 0 | 1.000000 | NA | NA | NA | NA | NA | NA | NA | 2.088221e-01 | 2.572246e-01 | 0.0016160 | 1.536800e-02 | 8.551800e-02 | 3.265150e-01 | 9.983840e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 140087 | 0.985335 | NA | NA | NA | NA | NA | NA | NA | 2.107165e-01 | 2.489174e-01 | 0.0000000 | 1.317890e-02 | 1.054310e-01 | 3.280750e-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 | 0.0021996 | 0.0018392 | 0.2300001 | 0.2316994 | 0.623766 | 0.7821490 | NA |
| 1 | 54676 | rs2462492 | C | T | -0.0007341 | 0.0018218 | 0.6899999 | 0.6869714 | 0.400402 | NA | NA |
| 1 | 86028 | rs114608975 | T | C | -0.0045124 | 0.0029129 | 0.1199999 | 0.1213520 | 0.103563 | 0.0277556 | NA |
| 1 | 91536 | rs6702460 | G | T | 0.0010550 | 0.0017939 | 0.5600000 | 0.5564749 | 0.456841 | 0.4207270 | NA |
| 1 | 234313 | rs8179466 | C | T | 0.0063175 | 0.0035375 | 0.0739997 | 0.0741194 | 0.074508 | NA | NA |
| 1 | 534192 | rs6680723 | C | T | 0.0014101 | 0.0020492 | 0.4899999 | 0.4913956 | 0.240961 | NA | NA |
| 1 | 546697 | rs12025928 | A | G | 0.0040064 | 0.0025556 | 0.1199999 | 0.1169539 | 0.913445 | NA | NA |
| 1 | 693731 | rs12238997 | A | G | 0.0008794 | 0.0017171 | 0.6100002 | 0.6085597 | 0.116343 | 0.1417730 | NA |
| 1 | 705882 | rs72631875 | G | A | -0.0042354 | 0.0025160 | 0.0920005 | 0.0923086 | 0.067300 | 0.0315495 | NA |
| 1 | 706368 | rs55727773 | A | G | -0.0034833 | 0.0012720 | 0.0062000 | 0.0061743 | 0.515656 | 0.2751600 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51219704 | rs147475742 | G | A | 0.0038990 | 0.0026709 | 0.1400000 | 0.1443441 | 0.041952 | 0.0473243 | NA |
| 22 | 51219766 | rs182321900 | C | T | -0.0012999 | 0.0124821 | 0.9199999 | 0.9170554 | 0.001928 | NA | NA |
| 22 | 51220146 | rs868950473 | C | T | -0.0017162 | 0.0123618 | 0.8900000 | 0.8895818 | 0.001977 | NA | NA |
| 22 | 51221190 | rs369304721 | G | A | -0.0007338 | 0.0026666 | 0.7800007 | 0.7831771 | 0.049733 | NA | NA |
| 22 | 51221731 | rs115055839 | T | C | -0.0001124 | 0.0019944 | 0.9599999 | 0.9550521 | 0.073242 | 0.0625000 | NA |
| 22 | 51222100 | rs114553188 | G | T | -0.0040501 | 0.0023476 | 0.0840001 | 0.0844902 | 0.054466 | 0.0880591 | NA |
| 22 | 51223637 | rs375798137 | G | A | -0.0042539 | 0.0023590 | 0.0710003 | 0.0713462 | 0.054095 | 0.0788738 | NA |
| 22 | 51229805 | rs9616985 | T | C | -0.0000558 | 0.0020016 | 0.9800000 | 0.9777449 | 0.073076 | 0.0730831 | NA |
| 22 | 51232488 | rs376461333 | A | G | -0.0090856 | 0.0047147 | 0.0539995 | 0.0539672 | 0.020044 | NA | NA |
| 22 | 51237063 | rs3896457 | T | C | 0.0044413 | 0.0012240 | 0.0002900 | 0.0002851 | 0.297968 | 0.2050720 | NA |
bcf preview
1 49298 rs10399793 T C . PASS AF=0.623766 ES:SE:LP:AF:ID 0.00219961:0.00183915:0.638272:0.623766:rs10399793
1 54676 rs2462492 C T . PASS AF=0.400402 ES:SE:LP:AF:ID -0.00073414:0.00182183:0.161151:0.400402:rs2462492
1 86028 rs114608975 T C . PASS AF=0.103563 ES:SE:LP:AF:ID -0.00451238:0.00291286:0.920819:0.103563:rs114608975
1 91536 rs6702460 G T . PASS AF=0.456841 ES:SE:LP:AF:ID 0.00105499:0.00179394:0.251812:0.456841:rs6702460
1 234313 rs8179466 C T . PASS AF=0.074508 ES:SE:LP:AF:ID 0.0063175:0.00353748:1.13077:0.074508:rs8179466
1 534192 rs6680723 C T . PASS AF=0.240961 ES:SE:LP:AF:ID 0.00141007:0.00204925:0.309804:0.240961:rs6680723
1 546697 rs12025928 A G . PASS AF=0.913445 ES:SE:LP:AF:ID 0.0040064:0.00255561:0.920819:0.913445:rs12025928
1 693731 rs12238997 A G . PASS AF=0.116343 ES:SE:LP:AF:ID 0.000879374:0.00171709:0.21467:0.116343:rs12238997
1 705882 rs72631875 G A . PASS AF=0.0673 ES:SE:LP:AF:ID -0.00423536:0.00251604:1.03621:0.0673:rs72631875
1 706368 rs12029736 A G . PASS AF=0.515656 ES:SE:LP:AF:ID -0.0034833:0.00127203:2.20761:0.515656:rs12029736
1 714596 rs149887893 T C . PASS AF=0.032984 ES:SE:LP:AF:ID -0.00548519:0.00320817:1.06048:0.032984:rs149887893
1 715265 rs12184267 C T . PASS AF=0.036603 ES:SE:LP:AF:ID -0.00509074:0.00291374:1.09151:0.036603:rs12184267
1 715367 rs12184277 A G . PASS AF=0.036719 ES:SE:LP:AF:ID -0.00524778:0.00290277:1.14874:0.036719:rs12184277
1 717485 rs12184279 C A . PASS AF=0.036418 ES:SE:LP:AF:ID -0.00546555:0.00292372:1.20761:0.036418:rs12184279
1 717587 rs144155419 G A . PASS AF=0.016412 ES:SE:LP:AF:ID -0.00142063:0.00450007:0.124939:0.016412:rs144155419
1 720381 rs116801199 G T . PASS AF=0.036959 ES:SE:LP:AF:ID -0.00514495:0.00289121:1.12494:0.036959:rs116801199
1 721290 rs12565286 G C . PASS AF=0.037054 ES:SE:LP:AF:ID -0.00505664:0.00288136:1.10237:0.037054:rs12565286
1 722670 rs116030099 T C . PASS AF=0.101223 ES:SE:LP:AF:ID 0.00405925:0.00209843:1.27572:0.101223:rs116030099
1 723891 rs2977670 G C . PASS AF=0.959121 ES:SE:LP:AF:ID 0.00543356:0.00277921:1.29243:0.959121:rs2977670
1 724849 rs12126395 C A . PASS AF=0.031452 ES:SE:LP:AF:ID 0.00587469:0.00504314:0.619789:0.031452:rs12126395
1 725060 rs865924913 A T . PASS AF=0.053254 ES:SE:LP:AF:ID -0.00066173:0.00401249:0.0604807:0.053254:rs865924913
1 726794 rs28454925 C G . PASS AF=0.036573 ES:SE:LP:AF:ID -0.00515791:0.00289999:1.12494:0.036573:rs28454925
1 729632 rs116720794 C T . PASS AF=0.036888 ES:SE:LP:AF:ID -0.00474828:0.00287364:1.00877:0.036888:rs116720794
1 729679 rs4951859 C G . PASS AF=0.84322 ES:SE:LP:AF:ID 0.000308602:0.00148827:0.0757207:0.84322:rs4951859
1 730087 rs148120343 T C . PASS AF=0.055919 ES:SE:LP:AF:ID 0.00268086:0.00240945:0.568636:0.055919:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122322 ES:SE:LP:AF:ID 0.0012261:0.00162889:0.346787:0.122322:rs58276399
1 732989 rs369030935 C T . PASS AF=0.025719 ES:SE:LP:AF:ID 0.00646447:0.00400642:0.958607:0.025719:rs369030935
1 734349 rs141242758 T C . PASS AF=0.121565 ES:SE:LP:AF:ID 0.00116368:0.00162957:0.318759:0.121565:rs141242758
1 736289 rs79010578 T A . PASS AF=0.132326 ES:SE:LP:AF:ID -0.000405218:0.00160617:0.09691:0.132326:rs79010578
1 736689 rs181876450 T C . PASS AF=0.011128 ES:SE:LP:AF:ID 0.00165432:0.00584097:0.107905:0.011128:rs181876450
1 740284 rs61770167 C T . PASS AF=0.005698 ES:SE:LP:AF:ID -0.0125615:0.00754042:1.01773:0.005698:rs61770167
1 742813 rs112573343 C T . PASS AF=0.002265 ES:SE:LP:AF:ID -0.009728:0.0126907:0.356547:0.002265:rs112573343
1 752478 rs146277091 G A . PASS AF=0.036802 ES:SE:LP:AF:ID -0.00513786:0.00284464:1.14874:0.036802:rs146277091
1 752566 rs3094315 G A . PASS AF=0.838957 ES:SE:LP:AF:ID 0.000133044:0.00144133:0.0315171:0.838957:rs3094315
1 752721 rs3131972 A G . PASS AF=0.838587 ES:SE:LP:AF:ID 7.55343e-05:0.00143978:0.0177288:0.838587:rs3131972
1 753405 rs3115860 C A . PASS AF=0.869769 ES:SE:LP:AF:ID -0.00102299:0.00154487:0.29243:0.869769:rs3115860
1 753541 rs2073813 G A . PASS AF=0.12988 ES:SE:LP:AF:ID 0.0011966:0.00154802:0.356547:0.12988:rs2073813
1 754063 rs12184312 G T . PASS AF=0.037315 ES:SE:LP:AF:ID -0.00459518:0.00279635:1:0.037315:rs12184312
1 754105 rs12184325 C T . PASS AF=0.037558 ES:SE:LP:AF:ID -0.00438588:0.00277869:0.958607:0.037558:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869113 ES:SE:LP:AF:ID -0.00102127:0.00154185:0.29243:0.869113:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869211 ES:SE:LP:AF:ID -0.00101268:0.00154246:0.29243:0.869211:rs3131968
1 754211 rs12184313 G A . PASS AF=0.037517 ES:SE:LP:AF:ID -0.00464442:0.00279069:1.01773:0.037517:rs12184313
1 754334 rs3131967 T C . PASS AF=0.869116 ES:SE:LP:AF:ID -0.00104221:0.00154181:0.30103:0.869116:rs3131967
1 754433 rs150578204 G A . PASS AF=0.005122 ES:SE:LP:AF:ID 0.0107997:0.00791567:0.769551:0.005122:rs150578204
1 754458 rs142682604 G T . PASS AF=0.005088 ES:SE:LP:AF:ID 0.0108041:0.00793644:0.769551:0.005088:rs142682604
1 754503 rs3115859 G A . PASS AF=0.838039 ES:SE:LP:AF:ID 0.000258505:0.00143577:0.0655015:0.838039:rs3115859
1 754629 rs10454459 A G . PASS AF=0.03753 ES:SE:LP:AF:ID -0.00463263:0.00279463:1.01323:0.03753:rs10454459
1 754964 rs3131966 C T . PASS AF=0.83867 ES:SE:LP:AF:ID 0.000165348:0.0014398:0.0409586:0.83867:rs3131966
1 755240 rs181660517 T G . PASS AF=0.013773 ES:SE:LP:AF:ID -4.39793e-05:0.0050257:0.00436481:0.013773:rs181660517
1 755435 rs184270342 T G . PASS AF=0.005542 ES:SE:LP:AF:ID 0.000917474:0.00775806:0.0409586:0.005542:rs184270342