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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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/ieu-a-import/processed/ieu-a-1132/ieu-a-1132.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/ieu-a-import/processed/ieu-a-1132/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Wed Feb 5 09:23:33 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1132/ieu-a-1132.vcf.gz ...
Read summary statistics for 10179532 SNPs.
Reading reference panel LD Score from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1220208 SNPs remain.
After merging with regression SNP LD, 1220208 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1387 (0.0141)
Lambda GC: 1.1614
Mean Chi^2: 1.2678
Intercept: 1.0443 (0.0084)
Ratio: 0.1654 (0.0314)
Analysis finished at Wed Feb 5 09:25:11 2020
Total time elapsed: 1.0m:37.64sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9496,
"inflation_factor": 1.1214,
"mean_EFFECT": -0.0001,
"n": 83691,
"n_snps": 10179532,
"n_clumped_hits": 58,
"n_p_sig": 4882,
"n_mono": 0,
"n_ns": 620064,
"n_mac": 322,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 112,
"n_miss_AF_reference": 131545,
"n_est": 81017.3514,
"ratio_se_n": 0.9839,
"mean_diff": 0.0003,
"ratio_diff": 1.5049,
"sd_y_est1": 2.1315,
"sd_y_est2": 2.0972,
"r2_sum1": 0.2384,
"r2_sum2": 0.0525,
"r2_sum3": 0.0542,
"r2_sum4": 0.0561,
"ldsc_nsnp_merge_refpanel_ld": 1220208,
"ldsc_nsnp_merge_regression_ld": 1220208,
"ldsc_observed_scale_h2_beta": 0.1387,
"ldsc_observed_scale_h2_se": 0.0141,
"ldsc_intercept_beta": 1.0443,
"ldsc_intercept_se": 0.0084,
"ldsc_lambda_gc": 1.1614,
"ldsc_mean_chisq": 1.2678,
"ldsc_ratio": 0.1654
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | FALSE |
| 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 | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| character | ID | 0 | 1.0000000 | 3 | 47 | 0 | 10179530 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 99 | 0 | 30504 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 103 | 0 | 16148 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.958649e+00 | 6.304321e+00 | 1.00000e+00 | 4.000000e+00 | 7.000000e+00 | 1.400000e+01 | 2.400000e+01 | ▇▆▂▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.911759e+07 | 5.683102e+07 | 8.28000e+02 | 3.228369e+07 | 6.944316e+07 | 1.156278e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -5.730000e-05 | 8.814740e-02 | -1.68745e+01 | -1.417000e-02 | -1.500000e-04 | 1.386000e-02 | 1.780230e+01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.009710e-02 | 4.315011e+00 | 1.00000e-02 | 1.174000e-02 | 1.783000e-02 | 3.828000e-02 | 9.999500e+02 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.809911e-01 | 2.943232e-01 | 0.00000e+00 | 2.215001e-01 | 4.750704e-01 | 7.362105e-01 | 1.000000e+00 | ▇▇▇▇▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.809911e-01 | 2.943232e-01 | 0.00000e+00 | 2.215053e-01 | 4.750505e-01 | 7.362034e-01 | 1.000000e+00 | ▇▇▇▇▆ |
| numeric | AF | 112 | 0.9999890 | NA | NA | NA | NA | NA | 2.290606e-01 | 2.643845e-01 | 5.30000e-06 | 2.147150e-02 | 1.094490e-01 | 3.656260e-01 | 9.999890e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 131545 | 0.9870775 | NA | NA | NA | NA | NA | 2.273201e-01 | 2.511927e-01 | 1.99700e-04 | 2.436100e-02 | 1.261980e-01 | 3.578270e-01 | 9.996010e-01 | ▇▂▂▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.369100e+04 | 0.000000e+00 | 8.36910e+04 | 8.369100e+04 | 8.369100e+04 | 8.369100e+04 | 8.369100e+04 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 10616 | rs376342519 | CCGCCGTTGCAAAGGCGCGCCG | C | -0.04371 | 0.06455 | 0.4982703 | 0.4983111 | 0.9925440 | 0.9930110 | 83691 |
| 1 | 14933 | rs199856693 | G | A | 0.01032 | 0.04386 | 0.8139799 | 0.8139805 | 0.0404558 | 0.0283546 | 83691 |
| 1 | 15774 | rs374029747 | G | A | -0.20865 | 0.10505 | 0.0470165 | 0.0470114 | 0.0069306 | 0.0119808 | 83691 |
| 1 | 16949 | rs199745162 | A | C | -0.04900 | 0.05894 | 0.4057803 | 0.4057737 | 0.0196591 | 0.0139776 | 83691 |
| 1 | 51479 | rs116400033 | T | A | -0.01210 | 0.01981 | 0.5413797 | 0.5413303 | 0.2356130 | 0.1281950 | 83691 |
| 1 | 52185 | rs201374420 | TTAA | T | -0.17699 | 0.16476 | 0.2827203 | 0.2827200 | 0.0037120 | 0.0053914 | 83691 |
| 1 | 54490 | rs141149254 | G | A | -0.01570 | 0.02208 | 0.4768799 | 0.4770528 | 0.1739770 | 0.0960463 | 83691 |
| 1 | 55164 | rs3091274 | C | A | 0.10276 | 0.07024 | 0.1434399 | 0.1434717 | 0.9829230 | 0.9233230 | 83691 |
| 1 | 55326 | rs3107975 | T | C | 0.08421 | 0.06548 | 0.1984002 | 0.1984286 | 0.0198551 | 0.0459265 | 83691 |
| 1 | 55545 | rs28396308 | C | T | -0.00070 | 0.02026 | 0.9725401 | 0.9724379 | 0.2294300 | 0.2392170 | 83691 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154925045 | rs509981 | C | T | -0.00232 | 0.01183 | 0.8444000 | 0.8445228 | 0.238955 | 0.3634440 | 83691 |
| 23 | 154925895 | rs538470 | C | T | -0.00104 | 0.01188 | 0.9304701 | 0.9302406 | 0.246312 | 0.3634440 | 83691 |
| 23 | 154927185 | rs185685661 | T | C | 0.01855 | 0.02200 | 0.3991499 | 0.3991268 | 0.111979 | 0.1796030 | 83691 |
| 23 | 154927199 | rs645904 | C | T | -0.00195 | 0.01184 | 0.8694099 | 0.8691833 | 0.239551 | 0.3674170 | 83691 |
| 23 | 154927581 | rs644138 | G | A | -0.00284 | 0.01141 | 0.8034601 | 0.8034347 | 0.286904 | 0.4635760 | 83691 |
| 23 | 154928151 | rs144607509 | C | T | -0.01415 | 0.06153 | 0.8180800 | 0.8181158 | 0.021457 | 0.0084768 | 83691 |
| 23 | 154929412 | rs557132 | C | T | -0.00229 | 0.01184 | 0.8463800 | 0.8466362 | 0.238374 | 0.3568210 | 83691 |
| 23 | 154929952 | rs4012982 | CAA | C | 0.01146 | 0.01746 | 0.5117502 | 0.5115942 | 0.190981 | 0.3165560 | 83691 |
| 23 | 154930230 | rs781880 | A | G | -0.00246 | 0.01185 | 0.8355499 | 0.8355453 | 0.238265 | 0.3618540 | 83691 |
| 24 | 13537468 | rs7203107 | A | G | -0.08727 | 0.07645 | 0.2536699 | 0.2536493 | 0.991260 | NA | 83691 |
bcf preview
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C . PASS AF=0.992544 ES:SE:LP:AF:SS:ID -0.04371:0.06455:0.302535:0.992544:83691:rs376342519
1 14933 rs199856693 G A . PASS AF=0.0404558 ES:SE:LP:AF:SS:ID 0.01032:0.04386:0.0893863:0.0404558:83691:rs199856693
1 15774 rs374029747 G A . PASS AF=0.00693057 ES:SE:LP:AF:SS:ID -0.20865:0.10505:1.32775:0.00693057:83691:rs374029747
1 16949 rs199745162 A C . PASS AF=0.0196591 ES:SE:LP:AF:SS:ID -0.049:0.05894:0.391709:0.0196591:83691:rs199745162
1 51479 rs116400033 T A . PASS AF=0.235613 ES:SE:LP:AF:SS:ID -0.0121:0.01981:0.266498:0.235613:83691:rs116400033
1 52185 rs201374420 TTAA T . PASS AF=0.003712 ES:SE:LP:AF:SS:ID -0.17699:0.16476:0.548643:0.003712:83691:rs201374420
1 54490 rs141149254 G A . PASS AF=0.173977 ES:SE:LP:AF:SS:ID -0.0157:0.02208:0.321591:0.173977:83691:rs141149254
1 55164 rs3091274 C A . PASS AF=0.982923 ES:SE:LP:AF:SS:ID 0.10276:0.07024:0.84333:0.982923:83691:rs3091274
1 55326 rs3107975 T C . PASS AF=0.0198551 ES:SE:LP:AF:SS:ID 0.08421:0.06548:0.702458:0.0198551:83691:rs3107975
1 55545 rs28396308 C T . PASS AF=0.22943 ES:SE:LP:AF:SS:ID -0.0007:0.02026:0.0120925:0.22943:83691:rs28396308
1 57292 rs201418760 C T . PASS AF=0.0197977 ES:SE:LP:AF:SS:ID 0.07179:0.06561:0.562424:0.0197977:83691:rs201418760
1 58814 rs114420996 G A . PASS AF=0.0949069 ES:SE:LP:AF:SS:ID -0.0128:0.02907:0.1807:0.0949069:83691:rs114420996
1 61743 rs184286948 G C . PASS AF=0.00908972 ES:SE:LP:AF:SS:ID -0.04849:0.09206:0.223016:0.00908972:83691:rs184286948
1 61920 rs62637820 G A . PASS AF=0.0281947 ES:SE:LP:AF:SS:ID 0.02161:0.0499:0.177165:0.0281947:83691:rs62637820
1 63093 rs200092917 G A . PASS AF=0.0214865 ES:SE:LP:AF:SS:ID -0.0036:0.06138:0.0207795:0.0214865:83691:rs200092917
1 64649 rs181431124 A C . PASS AF=0.0240029 ES:SE:LP:AF:SS:ID 0.04417:0.05481:0.37643:0.0240029:83691:rs181431124
1 66219 rs181028663 A T . PASS AF=0.0146975 ES:SE:LP:AF:SS:ID -0.09386:0.07016:0.742369:0.0146975:83691:rs181028663
1 68082 rs367789441 T C . PASS AF=0.0771585 ES:SE:LP:AF:SS:ID -0.00669:0.03159:0.0796888:0.0771585:83691:rs367789441
1 69428 rs140739101 T G . PASS AF=0.0438477 ES:SE:LP:AF:SS:ID 0.03833:0.03809:0.502642:0.0438477:83691:rs140739101
1 69761 rs200505207 A T . PASS AF=0.0819229 ES:SE:LP:AF:SS:ID -0.00896:0.03077:0.112946:0.0819229:83691:rs200505207
1 69897 rs200676709 T C . PASS AF=0.754936 ES:SE:LP:AF:SS:ID 0.00393:0.0197:0.0747343:0.754936:83691:rs200676709
1 72297 rs200651397 G GTAT . PASS AF=0.00546232 ES:SE:LP:AF:SS:ID 0.10443:0.11498:0.439197:0.00546232:83691:rs200651397
1 74790 rs13328700 C G . PASS AF=0.0320033 ES:SE:LP:AF:SS:ID 0.04009:0.04002:0.49964:0.0320033:83691:rs13328700
1 74792 rs13328684 G A . PASS AF=0.0320033 ES:SE:LP:AF:SS:ID 0.04009:0.04002:0.49964:0.0320033:83691:rs13328684
1 76854 rs367666799 A G . PASS AF=0.0672412 ES:SE:LP:AF:SS:ID -0.02031:0.0334:0.265056:0.0672412:83691:rs367666799
1 82163 rs139113303 G A . PASS AF=0.0665446 ES:SE:LP:AF:SS:ID -0.02615:0.03357:0.360514:0.0665446:83691:rs139113303
1 82609 rs149189449 C G . PASS AF=0.0669174 ES:SE:LP:AF:SS:ID -0.028:0.0335:0.394361:0.0669174:83691:rs149189449
1 83514 rs201754587 C T . PASS AF=0.331938 ES:SE:LP:AF:SS:ID 0.01332:0.01823:0.332332:0.331938:83691:rs201754587
1 84139 rs183605470 A T . PASS AF=0.0188246 ES:SE:LP:AF:SS:ID 0.00971:0.06544:0.0545363:0.0188246:83691:rs183605470
1 86028 rs114608975 T C . PASS AF=0.0463484 ES:SE:LP:AF:SS:ID 0.04958:0.0409:0.647065:0.0463484:83691:rs114608975
1 86065 rs116504101 G C . PASS AF=0.0684708 ES:SE:LP:AF:SS:ID -0.01856:0.03315:0.239887:0.0684708:83691:rs116504101
1 86331 rs115209712 A G . PASS AF=0.10333 ES:SE:LP:AF:SS:ID 0.01913:0.02847:0.299703:0.10333:83691:rs115209712
1 87021 rs188486692 T C . PASS AF=0.008657 ES:SE:LP:AF:SS:ID 0.00812:0.0946:0.0307612:0.008657:83691:rs188486692
1 87360 rs180907504 C T . PASS AF=0.0203922 ES:SE:LP:AF:SS:ID -0.03887:0.06327:0.268443:0.0203922:83691:rs180907504
1 87409 rs139490478 C T . PASS AF=0.0695736 ES:SE:LP:AF:SS:ID -0.01974:0.03293:0.260515:0.0695736:83691:rs139490478
1 88169 rs940550 C T . PASS AF=0.206193 ES:SE:LP:AF:SS:ID -0.04275:0.01945:1.5534:0.206193:83691:rs940550
1 88172 rs940551 G A . PASS AF=0.0748128 ES:SE:LP:AF:SS:ID -0.00892:0.03219:0.106893:0.0748128:83691:rs940551
1 88177 rs143215837 G C . PASS AF=0.0742194 ES:SE:LP:AF:SS:ID -0.00524:0.03232:0.059922:0.0742194:83691:rs143215837
1 88188 rs148331237 C A . PASS AF=0.00796695 ES:SE:LP:AF:SS:ID -0.06266:0.09345:0.298812:0.00796695:83691:rs148331237
1 88236 rs186918018 C T . PASS AF=0.0123822 ES:SE:LP:AF:SS:ID -0.08412:0.0862:0.482619:0.0123822:83691:rs186918018
1 88316 rs113759966 G A . PASS AF=0.0738751 ES:SE:LP:AF:SS:ID -0.00872:0.03236:0.103683:0.0738751:83691:rs113759966
1 88338 rs55700207 G A . PASS AF=0.0835214 ES:SE:LP:AF:SS:ID 0.01689:0.03173:0.225834:0.0835214:83691:rs55700207
1 88710 rs186575039 C G . PASS AF=0.0695547 ES:SE:LP:AF:SS:ID -0.01992:0.03293:0.263476:0.0695547:83691:rs186575039
1 89599 rs375955515 A T . PASS AF=0.0695547 ES:SE:LP:AF:SS:ID -0.01992:0.03293:0.263476:0.0695547:83691:rs375955515
1 89946 rs138808727 A T . PASS AF=0.232784 ES:SE:LP:AF:SS:ID -0.01269:0.01985:0.281889:0.232784:83691:rs138808727
1 91190 rs143856811 G A . PASS AF=0.0701592 ES:SE:LP:AF:SS:ID -0.03169:0.0333:0.466838:0.0701592:83691:rs143856811
1 91421 rs28619159 T C . PASS AF=0.0122252 ES:SE:LP:AF:SS:ID -0.06439:0.05465:0.62202:0.0122252:83691:rs28619159
1 91515 rs376723915 A C . PASS AF=0.55822 ES:SE:LP:AF:SS:ID -0.0004:0.01694:0.00826902:0.55822:83691:rs376723915
1 92633 rs149776517 C T . PASS AF=0.031027 ES:SE:LP:AF:SS:ID -0.04879:0.04846:0.503001:0.031027:83691:rs149776517
1 92858 rs147061536 G T . PASS AF=0.2399 ES:SE:LP:AF:SS:ID -0.0156:0.01959:0.370754:0.2399:83691:rs147061536