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-1133/ieu-a-1133.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-1133/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Tue Feb 4 18:19:01 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1133/ieu-a-1133.vcf.gz ...
Read summary statistics for 10167543 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, 1220160 SNPs remain.
After merging with regression SNP LD, 1220160 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1482 (0.0149)
Lambda GC: 1.1603
Mean Chi^2: 1.2418
Intercept: 1.0408 (0.0087)
Ratio: 0.1688 (0.0359)
Analysis finished at Tue Feb 4 18:20:44 2020
Total time elapsed: 1.0m:42.85sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9535,
"inflation_factor": 1.1267,
"mean_EFFECT": -0.0003,
"n": 69970,
"n_snps": 10167543,
"n_clumped_hits": 41,
"n_p_sig": 4389,
"n_mono": 0,
"n_ns": 619887,
"n_mac": 3,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 131472,
"n_est": 68143.2314,
"ratio_se_n": 0.9869,
"mean_diff": 0.0003,
"ratio_diff": 1.9255,
"sd_y_est1": 2.4134,
"sd_y_est2": 2.3817,
"r2_sum1": 0.2261,
"r2_sum2": 0.0388,
"r2_sum3": 0.0399,
"r2_sum4": 0.0499,
"ldsc_nsnp_merge_refpanel_ld": 1220160,
"ldsc_nsnp_merge_regression_ld": 1220160,
"ldsc_observed_scale_h2_beta": 0.1482,
"ldsc_observed_scale_h2_se": 0.0149,
"ldsc_intercept_beta": 1.0408,
"ldsc_intercept_se": 0.0087,
"ldsc_lambda_gc": 1.1603,
"ldsc_mean_chisq": 1.2418,
"ldsc_ratio": 0.1687
}
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 | 10167541 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 99 | 0 | 30496 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 103 | 0 | 16152 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.953877e+00 | 6.300553e+00 | 1.00000e+00 | 4.00000e+00 | 7.000000e+00 | 1.400000e+01 | 2.400000e+01 | ▇▆▂▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.912673e+07 | 5.684443e+07 | 8.28000e+02 | 3.22685e+07 | 6.948202e+07 | 1.156569e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -2.847000e-04 | 4.742850e-02 | -7.27963e+00 | -1.73200e-02 | -3.000000e-05 | 1.723000e-02 | 3.671840e+00 | ▁▁▁▇▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.551100e-02 | 2.914100e-02 | 1.13100e-02 | 1.45900e-02 | 2.204000e-02 | 4.821000e-02 | 4.779340e+00 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.804330e-01 | 2.942489e-01 | 0.00000e+00 | 2.20710e-01 | 4.740204e-01 | 7.352195e-01 | 1.000000e+00 | ▇▇▇▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.804330e-01 | 2.942490e-01 | 0.00000e+00 | 2.20709e-01 | 4.740139e-01 | 7.352246e-01 | 1.000000e+00 | ▇▇▇▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.290550e-01 | 2.639257e-01 | 1.46000e-05 | 2.16379e-02 | 1.098050e-01 | 3.652500e-01 | 9.998460e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 131472 | 0.9870694 | NA | NA | NA | NA | NA | 2.275301e-01 | 2.512103e-01 | 1.99700e-04 | 2.45607e-02 | 1.263980e-01 | 3.581460e-01 | 9.996010e-01 | ▇▂▂▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 6.997000e+04 | 0.000000e+00 | 6.99700e+04 | 6.99700e+04 | 6.997000e+04 | 6.997000e+04 | 6.997000e+04 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 10616 | rs376342519 | CCGCCGTTGCAAAGGCGCGCCG | C | -0.01889 | 0.15469 | 0.9028001 | 0.9028078 | 0.9947560 | 0.9930110 | 69970 |
| 1 | 14933 | rs199856693 | G | A | -0.02842 | 0.05392 | 0.5981499 | 0.5981400 | 0.0389227 | 0.0283546 | 69970 |
| 1 | 15774 | rs374029747 | G | A | 0.15158 | 0.14258 | 0.2877299 | 0.2877264 | 0.0069392 | 0.0119808 | 69970 |
| 1 | 16949 | rs199745162 | A | C | -0.03399 | 0.08913 | 0.7029800 | 0.7029413 | 0.0155071 | 0.0139776 | 69970 |
| 1 | 51479 | rs116400033 | T | A | -0.00874 | 0.02385 | 0.7140194 | 0.7140241 | 0.2229620 | 0.1281950 | 69970 |
| 1 | 52185 | rs201374420 | TTAA | T | -0.10278 | 0.11354 | 0.3653600 | 0.3653427 | 0.0065747 | 0.0053914 | 69970 |
| 1 | 54490 | rs141149254 | G | A | -0.00878 | 0.02751 | 0.7495300 | 0.7496077 | 0.1596000 | 0.0960463 | 69970 |
| 1 | 55164 | rs3091274 | C | A | 0.05140 | 0.06855 | 0.4533796 | 0.4533645 | 0.9788550 | 0.9233230 | 69970 |
| 1 | 55326 | rs3107975 | T | C | -0.01440 | 0.05921 | 0.8078600 | 0.8078488 | 0.0287371 | 0.0459265 | 69970 |
| 1 | 55545 | rs28396308 | C | T | -0.01818 | 0.02468 | 0.4614599 | 0.4613481 | 0.2398610 | 0.2392170 | 69970 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154925045 | rs509981 | C | T | 0.00725 | 0.01353 | 0.5922295 | 0.5920648 | 0.2382800 | 0.3634440 | 69970 |
| 23 | 154925895 | rs538470 | C | T | 0.00763 | 0.01356 | 0.5735404 | 0.5736498 | 0.2462810 | 0.3634440 | 69970 |
| 23 | 154927185 | rs185685661 | T | C | -0.01356 | 0.02595 | 0.6012900 | 0.6012921 | 0.1104900 | 0.1796030 | 69970 |
| 23 | 154927199 | rs645904 | C | T | 0.00753 | 0.01355 | 0.5785994 | 0.5784026 | 0.2397300 | 0.3674170 | 69970 |
| 23 | 154927581 | rs644138 | G | A | 0.01050 | 0.01313 | 0.4239396 | 0.4238873 | 0.2890030 | 0.4635760 | 69970 |
| 23 | 154928151 | rs144607509 | C | T | 0.01126 | 0.08482 | 0.8943899 | 0.8943897 | 0.0225182 | 0.0084768 | 69970 |
| 23 | 154929412 | rs557132 | C | T | 0.00722 | 0.01353 | 0.5938298 | 0.5935983 | 0.2378980 | 0.3568210 | 69970 |
| 23 | 154929952 | rs4012982 | CAA | C | 0.00269 | 0.01980 | 0.8917300 | 0.8919331 | 0.2084030 | 0.3165560 | 69970 |
| 23 | 154930230 | rs781880 | A | G | 0.00731 | 0.01354 | 0.5893903 | 0.5892785 | 0.2377670 | 0.3618540 | 69970 |
| 24 | 13537468 | rs7203107 | A | G | 0.18955 | 0.07917 | 0.0166498 | 0.0166560 | 0.9833080 | NA | 69970 |
bcf preview
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C . PASS AF=0.994756 ES:SE:LP:AF:SS:ID -0.01889:0.15469:0.0444084:0.994756:69970:rs376342519
1 14933 rs199856693 G A . PASS AF=0.0389227 ES:SE:LP:AF:SS:ID -0.02842:0.05392:0.22319:0.0389227:69970:rs199856693
1 15774 rs374029747 G A . PASS AF=0.00693915 ES:SE:LP:AF:SS:ID 0.15158:0.14258:0.541015:0.00693915:69970:rs374029747
1 16949 rs199745162 A C . PASS AF=0.0155071 ES:SE:LP:AF:SS:ID -0.03399:0.08913:0.153057:0.0155071:69970:rs199745162
1 51479 rs116400033 T A . PASS AF=0.222962 ES:SE:LP:AF:SS:ID -0.00874:0.02385:0.14629:0.222962:69970:rs116400033
1 52185 rs201374420 TTAA T . PASS AF=0.00657471 ES:SE:LP:AF:SS:ID -0.10278:0.11354:0.437279:0.00657471:69970:rs201374420
1 54490 rs141149254 G A . PASS AF=0.1596 ES:SE:LP:AF:SS:ID -0.00878:0.02751:0.125211:0.1596:69970:rs141149254
1 55164 rs3091274 C A . PASS AF=0.978855 ES:SE:LP:AF:SS:ID 0.0514:0.06855:0.343538:0.978855:69970:rs3091274
1 55326 rs3107975 T C . PASS AF=0.0287371 ES:SE:LP:AF:SS:ID -0.0144:0.05921:0.0926639:0.0287371:69970:rs3107975
1 55545 rs28396308 C T . PASS AF=0.239861 ES:SE:LP:AF:SS:ID -0.01818:0.02468:0.335866:0.239861:69970:rs28396308
1 57292 rs201418760 C T . PASS AF=0.0277881 ES:SE:LP:AF:SS:ID -0.01462:0.05936:0.0939237:0.0277881:69970:rs201418760
1 58814 rs114420996 G A . PASS AF=0.0984707 ES:SE:LP:AF:SS:ID -0.02719:0.03694:0.335612:0.0984707:69970:rs114420996
1 61743 rs184286948 G C . PASS AF=0.00808821 ES:SE:LP:AF:SS:ID -0.08979:0.11868:0.347464:0.00808821:69970:rs184286948
1 61920 rs62637820 G A . PASS AF=0.0208917 ES:SE:LP:AF:SS:ID -0.06139:0.08425:0.331418:0.0208917:69970:rs62637820
1 63093 rs200092917 G A . PASS AF=0.0249512 ES:SE:LP:AF:SS:ID -0.00157:0.06648:0.00827345:0.0249512:69970:rs200092917
1 64649 rs181431124 A C . PASS AF=0.0180759 ES:SE:LP:AF:SS:ID -0.02843:0.08891:0.125425:0.0180759:69970:rs181431124
1 66219 rs181028663 A T . PASS AF=0.0127416 ES:SE:LP:AF:SS:ID -0.00444:0.09517:0.016482:0.0127416:69970:rs181028663
1 68082 rs367789441 T C . PASS AF=0.0694076 ES:SE:LP:AF:SS:ID -0.00825:0.03991:0.0776587:0.0694076:69970:rs367789441
1 69428 rs140739101 T G . PASS AF=0.0377467 ES:SE:LP:AF:SS:ID -0.01831:0.05399:0.133967:0.0377467:69970:rs140739101
1 69761 rs200505207 A T . PASS AF=0.0731735 ES:SE:LP:AF:SS:ID -0.01064:0.03936:0.104042:0.0731735:69970:rs200505207
1 69897 rs200676709 T C . PASS AF=0.754808 ES:SE:LP:AF:SS:ID 0.021:0.02411:0.415918:0.754808:69970:rs200676709
1 72297 rs200651397 G GTAT . PASS AF=0.00267097 ES:SE:LP:AF:SS:ID 0.38859:0.24234:0.963251:0.00267097:69970:rs200651397
1 74790 rs13328700 C G . PASS AF=0.0243687 ES:SE:LP:AF:SS:ID -0.06602:0.07:0.461414:0.0243687:69970:rs13328700
1 74792 rs13328684 G A . PASS AF=0.0243687 ES:SE:LP:AF:SS:ID -0.06602:0.07:0.461414:0.0243687:69970:rs13328684
1 76854 rs367666799 A G . PASS AF=0.0553168 ES:SE:LP:AF:SS:ID 0.01321:0.04484:0.114447:0.0553168:69970:rs367666799
1 82163 rs139113303 G A . PASS AF=0.0546978 ES:SE:LP:AF:SS:ID 0.0171:0.0448:0.15323:0.0546978:69970:rs139113303
1 82609 rs149189449 C G . PASS AF=0.0561714 ES:SE:LP:AF:SS:ID 0.00523:0.04404:0.0431691:0.0561714:69970:rs149189449
1 83514 rs201754587 C T . PASS AF=0.350269 ES:SE:LP:AF:SS:ID 0.03594:0.02164:1.014:0.350269:69970:rs201754587
1 84139 rs183605470 A T . PASS AF=0.0243531 ES:SE:LP:AF:SS:ID 0.11239:0.06679:1.03424:0.0243531:69970:rs183605470
1 86028 rs114608975 T C . PASS AF=0.0405916 ES:SE:LP:AF:SS:ID -0.0433:0.05037:0.408869:0.0405916:69970:rs114608975
1 86065 rs116504101 G C . PASS AF=0.0591329 ES:SE:LP:AF:SS:ID 0.02274:0.04265:0.226301:0.0591329:69970:rs116504101
1 86331 rs115209712 A G . PASS AF=0.0993426 ES:SE:LP:AF:SS:ID 0.00325:0.03611:0.032307:0.0993426:69970:rs115209712
1 87021 rs188486692 T C . PASS AF=0.00831298 ES:SE:LP:AF:SS:ID 0.1176:0.10882:0.55309:0.00831298:69970:rs188486692
1 87360 rs180907504 C T . PASS AF=0.0283103 ES:SE:LP:AF:SS:ID -0.05533:0.0579:0.469531:0.0283103:69970:rs180907504
1 87409 rs139490478 C T . PASS AF=0.060043 ES:SE:LP:AF:SS:ID 0.01769:0.04238:0.169777:0.060043:69970:rs139490478
1 88169 rs940550 C T . PASS AF=0.218888 ES:SE:LP:AF:SS:ID -0.03905:0.02526:0.912964:0.218888:69970:rs940550
1 88172 rs940551 G A . PASS AF=0.0695693 ES:SE:LP:AF:SS:ID -0.01898:0.03998:0.197247:0.0695693:69970:rs940551
1 88177 rs143215837 G C . PASS AF=0.0686928 ES:SE:LP:AF:SS:ID -0.01855:0.04008:0.191458:0.0686928:69970:rs143215837
1 88188 rs148331237 C A . PASS AF=0.00632356 ES:SE:LP:AF:SS:ID 0.15034:0.11865:0.687971:0.00632356:69970:rs148331237
1 88236 rs186918018 C T . PASS AF=0.0141206 ES:SE:LP:AF:SS:ID -0.05744:0.07734:0.339429:0.0141206:69970:rs186918018
1 88316 rs113759966 G A . PASS AF=0.0689597 ES:SE:LP:AF:SS:ID -0.02411:0.03989:0.263213:0.0689597:69970:rs113759966
1 88338 rs55700207 G A . PASS AF=0.0847504 ES:SE:LP:AF:SS:ID -0.0043:0.03963:0.0392772:0.0847504:69970:rs55700207
1 88710 rs186575039 C G . PASS AF=0.0598735 ES:SE:LP:AF:SS:ID 0.01835:0.0424:0.177061:0.0598735:69970:rs186575039
1 89599 rs375955515 A T . PASS AF=0.0598735 ES:SE:LP:AF:SS:ID 0.01835:0.0424:0.177061:0.0598735:69970:rs375955515
1 89946 rs138808727 A T . PASS AF=0.221468 ES:SE:LP:AF:SS:ID -0.01702:0.02393:0.321463:0.221468:69970:rs138808727
1 91190 rs143856811 G A . PASS AF=0.0609153 ES:SE:LP:AF:SS:ID 0.02516:0.04189:0.261132:0.0609153:69970:rs143856811
1 91421 rs28619159 T C . PASS AF=0.0120596 ES:SE:LP:AF:SS:ID -0.24933:0.10486:1.75903:0.0120596:69970:rs28619159
1 91515 rs376723915 A C . PASS AF=0.552241 ES:SE:LP:AF:SS:ID 0.00978:0.02069:0.196304:0.552241:69970:rs376723915
1 92633 rs149776517 C T . PASS AF=0.033149 ES:SE:LP:AF:SS:ID -0.06046:0.05652:0.545567:0.033149:69970:rs149776517
1 92858 rs147061536 G T . PASS AF=0.227024 ES:SE:LP:AF:SS:ID -0.02117:0.02384:0.426629:0.227024:69970:rs147061536