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-1128/ieu-a-1128.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-1128/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 16:24:55 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1128/ieu-a-1128.vcf.gz ...
Read summary statistics for 10180043 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, 1220210 SNPs remain.
After merging with regression SNP LD, 1220210 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0731 (0.0065)
Lambda GC: 1.2101
Mean Chi^2: 1.2595
Intercept: 1.08 (0.0075)
Ratio: 0.3083 (0.0291)
Analysis finished at Tue Feb 4 16:26:20 2020
Total time elapsed: 1.0m:24.99sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9511,
"inflation_factor": 1.1572,
"mean_EFFECT": -0.0764,
"n": 127442,
"n_snps": 10180043,
"n_clumped_hits": 37,
"n_p_sig": 1784,
"n_mono": 0,
"n_ns": 620075,
"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": 131542,
"n_est": 128246.2922,
"ratio_se_n": 1.0032,
"mean_diff": 0.0768,
"ratio_diff": 3.0032,
"sd_y_est1": 3.0261,
"sd_y_est2": 3.0356,
"r2_sum1": 0.1333,
"r2_sum2": 0.0146,
"r2_sum3": 0.0145,
"r2_sum4": 0.0161,
"ldsc_nsnp_merge_refpanel_ld": 1220210,
"ldsc_nsnp_merge_regression_ld": 1220210,
"ldsc_observed_scale_h2_beta": 0.0731,
"ldsc_observed_scale_h2_se": 0.0065,
"ldsc_intercept_beta": 1.08,
"ldsc_intercept_se": 0.0075,
"ldsc_lambda_gc": 1.2101,
"ldsc_mean_chisq": 1.2595,
"ldsc_ratio": 0.3083
}
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 | 10180041 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 99 | 0 | 30503 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 103 | 0 | 16154 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.958547e+00 | 6.304243e+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 | 7.911752e+07 | 5.683071e+07 | 8.28000e+02 | 3.228420e+07 | 6.944298e+07 | 1.156271e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -7.641560e-02 | 2.014530e+01 | -8.85217e+03 | -1.570000e-02 | 6.000000e-04 | 1.740000e-02 | 9.770600e+00 | ▁▁▁▁▇ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.464993e-01 | 1.355920e+02 | 1.10000e-02 | 1.350000e-02 | 2.050000e-02 | 4.540000e-02 | 5.974190e+04 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.764947e-01 | 2.951276e-01 | 0.00000e+00 | 2.149998e-01 | 4.681004e-01 | 7.322999e-01 | 1.000000e+00 | ▇▇▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.764957e-01 | 2.951309e-01 | 0.00000e+00 | 2.150286e-01 | 4.680449e-01 | 7.323743e-01 | 1.000000e+00 | ▇▇▆▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.292171e-01 | 2.639464e-01 | 1.00000e-03 | 2.190000e-02 | 1.095000e-01 | 3.651000e-01 | 9.989000e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 131542 | 0.9870784 | NA | NA | NA | NA | NA | 2.273098e-01 | 2.511934e-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 | 1.274420e+05 | 0.000000e+00 | 1.27442e+05 | 1.274420e+05 | 1.274420e+05 | 1.274420e+05 | 1.274420e+05 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 10616 | rs376342519 | CCGCCGTTGCAAAGGCGCGCCG | C | 0.1702 | 0.1101 | 0.1221001 | 0.1221366 | 0.9925 | 0.9930110 | 127442 |
| 1 | 14933 | rs199856693 | G | A | -0.0019 | 0.0534 | 0.9719000 | 0.9716168 | 0.0396 | 0.0283546 | 127442 |
| 1 | 15774 | rs374029747 | G | A | -0.4691 | 0.1809 | 0.0095100 | 0.0095103 | 0.0070 | 0.0119808 | 127442 |
| 1 | 16949 | rs199745162 | A | C | -0.0722 | 0.0932 | 0.4388004 | 0.4385299 | 0.0192 | 0.0139776 | 127442 |
| 1 | 51479 | rs116400033 | T | A | -0.0278 | 0.0239 | 0.2442997 | 0.2447565 | 0.2300 | 0.1281950 | 127442 |
| 1 | 52185 | rs201374420 | TTAA | T | -0.0268 | 0.1883 | 0.8867000 | 0.8868225 | 0.0066 | 0.0053914 | 127442 |
| 1 | 54490 | rs141149254 | G | A | -0.0606 | 0.0270 | 0.0248399 | 0.0248038 | 0.1677 | 0.0960463 | 127442 |
| 1 | 55164 | rs3091274 | C | A | 0.0432 | 0.0776 | 0.5773006 | 0.5777317 | 0.9809 | 0.9233230 | 127442 |
| 1 | 55326 | rs3107975 | T | C | 0.0503 | 0.0700 | 0.4718001 | 0.4724050 | 0.0243 | 0.0459265 | 127442 |
| 1 | 55545 | rs28396308 | C | T | 0.0085 | 0.0305 | 0.7790996 | 0.7804839 | 0.2307 | 0.2392170 | 127442 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154925045 | rs509981 | C | T | 0.0008 | 0.0141 | 0.9561999 | 0.9547542 | 0.2393 | 0.3634440 | 127442 |
| 23 | 154925895 | rs538470 | C | T | -0.0011 | 0.0142 | 0.9402999 | 0.9382538 | 0.2463 | 0.3634440 | 127442 |
| 23 | 154927185 | rs185685661 | T | C | 0.0376 | 0.0264 | 0.1543999 | 0.1543763 | 0.1130 | 0.1796030 | 127442 |
| 23 | 154927199 | rs645904 | C | T | 0.0007 | 0.0142 | 0.9580999 | 0.9606836 | 0.2402 | 0.3674170 | 127442 |
| 23 | 154927581 | rs644138 | G | A | -0.0018 | 0.0137 | 0.8941000 | 0.8954693 | 0.2885 | 0.4635760 | 127442 |
| 23 | 154928151 | rs144607509 | C | T | -0.0804 | 0.1007 | 0.4245003 | 0.4246320 | 0.0215 | 0.0084768 | 127442 |
| 23 | 154929412 | rs557132 | C | T | 0.0014 | 0.0141 | 0.9218000 | 0.9209074 | 0.2388 | 0.3568210 | 127442 |
| 23 | 154929952 | rs4012982 | CAA | C | 0.0029 | 0.0201 | 0.8844999 | 0.8852805 | 0.2037 | 0.3165560 | 127442 |
| 23 | 154930230 | rs781880 | A | G | 0.0013 | 0.0142 | 0.9272000 | 0.9270561 | 0.2386 | 0.3618540 | 127442 |
| 24 | 13537468 | rs7203107 | A | G | -0.0563 | 0.0833 | 0.4990005 | 0.4991230 | 0.9868 | NA | 127442 |
bcf preview
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C . PASS AF=0.9925 ES:SE:LP:AF:SS:ID 0.1702:0.1101:0.913284:0.9925:127442:rs376342519
1 14933 rs199856693 G A . PASS AF=0.0396 ES:SE:LP:AF:SS:ID -0.0019:0.0534:0.0123784:0.0396:127442:rs199856693
1 15774 rs374029747 G A . PASS AF=0.007 ES:SE:LP:AF:SS:ID -0.4691:0.1809:2.02182:0.007:127442:rs374029747
1 16949 rs199745162 A C . PASS AF=0.0192 ES:SE:LP:AF:SS:ID -0.0722:0.0932:0.357733:0.0192:127442:rs199745162
1 51479 rs116400033 T A . PASS AF=0.23 ES:SE:LP:AF:SS:ID -0.0278:0.0239:0.612077:0.23:127442:rs116400033
1 52185 rs201374420 TTAA T . PASS AF=0.0066 ES:SE:LP:AF:SS:ID -0.0268:0.1883:0.0522233:0.0066:127442:rs201374420
1 54490 rs141149254 G A . PASS AF=0.1677 ES:SE:LP:AF:SS:ID -0.0606:0.027:1.60485:0.1677:127442:rs141149254
1 55164 rs3091274 C A . PASS AF=0.9809 ES:SE:LP:AF:SS:ID 0.0432:0.0776:0.238598:0.9809:127442:rs3091274
1 55326 rs3107975 T C . PASS AF=0.0243 ES:SE:LP:AF:SS:ID 0.0503:0.07:0.326242:0.0243:127442:rs3107975
1 55545 rs28396308 C T . PASS AF=0.2307 ES:SE:LP:AF:SS:ID 0.0085:0.0305:0.108407:0.2307:127442:rs28396308
1 57292 rs201418760 C T . PASS AF=0.0238 ES:SE:LP:AF:SS:ID 0.0472:0.0704:0.298864:0.0238:127442:rs201418760
1 58814 rs114420996 G A . PASS AF=0.0949 ES:SE:LP:AF:SS:ID -0.0029:0.0441:0.0235125:0.0949:127442:rs114420996
1 61743 rs184286948 G C . PASS AF=0.0087 ES:SE:LP:AF:SS:ID -0.1813:0.123:0.851706:0.0087:127442:rs184286948
1 61920 rs62637820 G A . PASS AF=0.028 ES:SE:LP:AF:SS:ID 0.026:0.0755:0.136558:0.028:127442:rs62637820
1 63093 rs200092917 G A . PASS AF=0.023 ES:SE:LP:AF:SS:ID 0.1439:0.07:1.40023:0.023:127442:rs200092917
1 64649 rs181431124 A C . PASS AF=0.0242 ES:SE:LP:AF:SS:ID 0.0579:0.0816:0.3203:0.0242:127442:rs181431124
1 66219 rs181028663 A T . PASS AF=0.0153 ES:SE:LP:AF:SS:ID -0.0136:0.1017:0.0487111:0.0153:127442:rs181028663
1 68082 rs367789441 T C . PASS AF=0.0734 ES:SE:LP:AF:SS:ID 0.0096:0.0388:0.0940962:0.0734:127442:rs367789441
1 69428 rs140739101 T G . PASS AF=0.0422 ES:SE:LP:AF:SS:ID -0.0258:0.0488:0.223953:0.0422:127442:rs140739101
1 69761 rs200505207 A T . PASS AF=0.0778 ES:SE:LP:AF:SS:ID -0.0065:0.038:0.063436:0.0778:127442:rs200505207
1 69897 rs200676709 T C . PASS AF=0.7545 ES:SE:LP:AF:SS:ID -0.0252:0.0237:0.540155:0.7545:127442:rs200676709
1 72297 rs200651397 G GTAT . PASS AF=0.0055 ES:SE:LP:AF:SS:ID 0.0178:0.1937:0.0330608:0.0055:127442:rs200651397
1 74790 rs13328700 C G . PASS AF=0.0316 ES:SE:LP:AF:SS:ID 0.0566:0.0618:0.443939:0.0316:127442:rs13328700
1 74792 rs13328684 G A . PASS AF=0.0316 ES:SE:LP:AF:SS:ID 0.0566:0.0618:0.443939:0.0316:127442:rs13328684
1 76854 rs367666799 A G . PASS AF=0.0635 ES:SE:LP:AF:SS:ID -0.0009:0.0418:0.0072698:0.0635:127442:rs367666799
1 82163 rs139113303 G A . PASS AF=0.0628 ES:SE:LP:AF:SS:ID -0.0016:0.0419:0.0132283:0.0628:127442:rs139113303
1 82609 rs149189449 C G . PASS AF=0.0635 ES:SE:LP:AF:SS:ID -0.004:0.0416:0.0345631:0.0635:127442:rs149189449
1 83514 rs201754587 C T . PASS AF=0.3408 ES:SE:LP:AF:SS:ID 0.0064:0.0217:0.113848:0.3408:127442:rs201754587
1 84139 rs183605470 A T . PASS AF=0.0215 ES:SE:LP:AF:SS:ID 0.0382:0.076:0.210631:0.0215:127442:rs183605470
1 86028 rs114608975 T C . PASS AF=0.0447 ES:SE:LP:AF:SS:ID -0.0525:0.0502:0.530325:0.0447:127442:rs114608975
1 86065 rs116504101 G C . PASS AF=0.0653 ES:SE:LP:AF:SS:ID -0.0128:0.0411:0.122053:0.0653:127442:rs116504101
1 86331 rs115209712 A G . PASS AF=0.1041 ES:SE:LP:AF:SS:ID 0.0319:0.0426:0.343327:0.1041:127442:rs115209712
1 87021 rs188486692 T C . PASS AF=0.0086 ES:SE:LP:AF:SS:ID 0.2369:0.1086:1.53566:0.0086:127442:rs188486692
1 87360 rs180907504 C T . PASS AF=0.0243 ES:SE:LP:AF:SS:ID 0.0599:0.0677:0.424466:0.0243:127442:rs180907504
1 87409 rs139490478 C T . PASS AF=0.0664 ES:SE:LP:AF:SS:ID -0.0071:0.0407:0.064896:0.0664:127442:rs139490478
1 88169 rs940550 C T . PASS AF=0.211 ES:SE:LP:AF:SS:ID -0.0345:0.0241:0.817015:0.211:127442:rs940550
1 88172 rs940551 G A . PASS AF=0.072 ES:SE:LP:AF:SS:ID 0.0067:0.0393:0.0633857:0.072:127442:rs940551
1 88177 rs143215837 G C . PASS AF=0.0713 ES:SE:LP:AF:SS:ID 0.0066:0.0394:0.0617305:0.0713:127442:rs143215837
1 88188 rs148331237 C A . PASS AF=0.0073 ES:SE:LP:AF:SS:ID -0.203:0.1254:0.976336:0.0073:127442:rs148331237
1 88236 rs186918018 C T . PASS AF=0.0141 ES:SE:LP:AF:SS:ID 0.2155:0.1193:1.14991:0.0141:127442:rs186918018
1 88316 rs113759966 G A . PASS AF=0.0712 ES:SE:LP:AF:SS:ID 0.0039:0.0393:0.0354104:0.0712:127442:rs113759966
1 88338 rs55700207 G A . PASS AF=0.0832 ES:SE:LP:AF:SS:ID 0.0335:0.0476:0.316683:0.0832:127442:rs55700207
1 88710 rs186575039 C G . PASS AF=0.0664 ES:SE:LP:AF:SS:ID -0.0073:0.0407:0.0668165:0.0664:127442:rs186575039
1 89599 rs375955515 A T . PASS AF=0.0664 ES:SE:LP:AF:SS:ID -0.0073:0.0407:0.0668165:0.0664:127442:rs375955515
1 89946 rs138808727 A T . PASS AF=0.2283 ES:SE:LP:AF:SS:ID -0.0174:0.0238:0.331428:0.2283:127442:rs138808727
1 91190 rs143856811 G A . PASS AF=0.0671 ES:SE:LP:AF:SS:ID -0.0018:0.0407:0.0156978:0.0671:127442:rs143856811
1 91421 rs28619159 T C . PASS AF=0.0122 ES:SE:LP:AF:SS:ID -0.1525:0.0876:1.08794:0.0122:127442:rs28619159
1 91515 rs376723915 A C . PASS AF=0.5559 ES:SE:LP:AF:SS:ID 0.0089:0.0204:0.179142:0.5559:127442:rs376723915
1 92633 rs149776517 C T . PASS AF=0.0318 ES:SE:LP:AF:SS:ID 0.0065:0.0565:0.0414361:0.0318:127442:rs149776517
1 92858 rs147061536 G T . PASS AF=0.235 ES:SE:LP:AF:SS:ID -0.0223:0.0236:0.462433:0.235:127442:rs147061536