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-1228/ieu-a-1228.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-1228/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 13:09:12 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1228/ieu-a-1228.vcf.gz ...
Read summary statistics for 15561503 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, 1218951 SNPs remain.
After merging with regression SNP LD, 1218951 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0595 (0.0129)
Lambda GC: 1.0581
Mean Chi^2: 1.0873
Intercept: 1.0239 (0.0067)
Ratio: 0.2735 (0.0772)
Analysis finished at Tue Feb 4 13:11:50 2020
Total time elapsed: 2.0m:37.16sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9604,
"inflation_factor": 1.0542,
"mean_EFFECT": -0.2205,
"n": 54990,
"n_snps": 15561503,
"n_clumped_hits": 15,
"n_p_sig": 4193,
"n_mono": 0,
"n_ns": 781721,
"n_mac": 260659,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 4954,
"n_miss_AF_reference": 161549,
"n_est": 53124.1723,
"ratio_se_n": 0.9829,
"mean_diff": 0.2298,
"ratio_diff": 2.6702,
"sd_y_est1": 2.8068,
"sd_y_est2": 2.7588,
"r2_sum1": 0.1257,
"r2_sum2": 0.016,
"r2_sum3": 0.0165,
"r2_sum4": 0.0198,
"ldsc_nsnp_merge_refpanel_ld": 1218951,
"ldsc_nsnp_merge_regression_ld": 1218951,
"ldsc_observed_scale_h2_beta": 0.0595,
"ldsc_observed_scale_h2_se": 0.0129,
"ldsc_intercept_beta": 1.0239,
"ldsc_intercept_se": 0.0067,
"ldsc_lambda_gc": 1.0581,
"ldsc_mean_chisq": 1.0873,
"ldsc_ratio": 0.2738
}
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 | TRUE |
| 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 | 15561501 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 101 | 0 | 37618 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 105 | 0 | 18069 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.889588e+00 | 6.250269e+00 | 1.000e+00 | 4.000000e+00 | 7.000000e+00 | 1.400000e+01 | 2.400000e+01 | ▇▆▂▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.931933e+07 | 5.681826e+07 | 5.600e+01 | 3.252494e+07 | 6.965202e+07 | 1.158357e+08 | 2.492402e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -2.205223e-01 | 2.339569e+00 | -2.040e+01 | -3.946000e-02 | -1.967000e-04 | 3.769000e-02 | 2.038000e+01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.855469e-01 | 5.972393e+00 | 6.776e-04 | 2.149000e-02 | 6.248000e-02 | 2.423000e-01 | 1.000000e+03 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.916922e-01 | 2.906435e-01 | 0.000e+00 | 2.376999e-01 | 4.885995e-01 | 7.435000e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.917155e-01 | 2.906331e-01 | 0.000e+00 | 2.376989e-01 | 4.885977e-01 | 7.435471e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 4954 | 0.9996817 | NA | NA | NA | NA | NA | 1.539349e-01 | 2.450572e-01 | 0.000e+00 | 2.032000e-03 | 2.022000e-02 | 2.073000e-01 | 9.999980e-01 | ▇▁▁▁▁ |
| numeric | AF_reference | 161549 | 0.9896187 | NA | NA | NA | NA | NA | 1.536722e-01 | 2.325612e-01 | 0.000e+00 | 2.595800e-03 | 3.115020e-02 | 2.134580e-01 | 1.000000e+00 | ▇▁▁▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.499000e+04 | 0.000000e+00 | 5.499e+04 | 5.499000e+04 | 5.499000e+04 | 5.499000e+04 | 5.499000e+04 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 10616 | rs376342519 | CCGCCGTTGCAAAGGCGCGCCG | C | 0.039220 | 0.11170 | 0.7254993 | 0.7254990 | 0.991000 | 0.9930110 | 54990 |
| 1 | 14933 | rs199856693 | G | A | 0.034140 | 0.07154 | 0.6332001 | 0.6332086 | 0.047970 | 0.0283546 | 54990 |
| 1 | 15774 | rs374029747 | G | A | -0.032640 | 0.17780 | 0.8543999 | 0.8543453 | 0.006579 | 0.0119808 | 54990 |
| 1 | 16949 | rs199745162 | A | C | -0.111100 | 0.09843 | 0.2589000 | 0.2590156 | 0.016750 | 0.0139776 | 54990 |
| 1 | 51479 | rs116400033 | T | A | -0.011490 | 0.03065 | 0.7076003 | 0.7077515 | 0.232100 | 0.1281950 | 54990 |
| 1 | 52185 | rs201374420 | TTAA | T | 0.463000 | 1.15900 | 0.6894996 | 0.6895379 | 0.005882 | 0.0053914 | 54990 |
| 1 | 54353 | rs140052487 | C | A | -0.797200 | 0.48950 | 0.1034001 | 0.1033976 | 0.001339 | 0.0089856 | 54990 |
| 1 | 54490 | rs141149254 | G | A | -0.007739 | 0.03446 | 0.8223000 | 0.8223066 | 0.166100 | 0.0960463 | 54990 |
| 1 | 55164 | rs3091274 | C | A | 0.046940 | 0.10340 | 0.6499007 | 0.6498539 | 0.980700 | 0.9233230 | 54990 |
| 1 | 55326 | rs3107975 | T | C | 0.027350 | 0.20130 | 0.8919001 | 0.8919265 | 0.028260 | 0.0459265 | 54990 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154925045 | rs509981 | C | T | -0.001569 | 0.02020 | 0.9380999 | 0.9380880 | 0.250000 | 0.3634440 | 54990 |
| 23 | 154925895 | rs538470 | C | T | -0.000839 | 0.02093 | 0.9680001 | 0.9680246 | 0.252700 | 0.3634440 | 54990 |
| 23 | 154926376 | rs116490668 | C | T | -0.074440 | 0.34470 | 0.8289999 | 0.8290221 | 0.001859 | 0.0349669 | 54990 |
| 23 | 154927185 | rs185685661 | T | C | -0.008165 | 0.03551 | 0.8181000 | 0.8181421 | 0.139300 | 0.1796030 | 54990 |
| 23 | 154927199 | rs645904 | C | T | -0.005376 | 0.02023 | 0.7905002 | 0.7904364 | 0.248000 | 0.3674170 | 54990 |
| 23 | 154927581 | rs644138 | G | A | -0.010160 | 0.01977 | 0.6072996 | 0.6073149 | 0.299900 | 0.4635760 | 54990 |
| 23 | 154929412 | rs557132 | C | T | -0.002431 | 0.02025 | 0.9044001 | 0.9044440 | 0.250400 | 0.3568210 | 54990 |
| 23 | 154929952 | rs4012982 | CAA | C | -0.003023 | 0.02027 | 0.8813999 | 0.8814458 | 0.250900 | 0.3165560 | 54990 |
| 23 | 154930230 | rs781880 | A | G | -0.002925 | 0.02038 | 0.8859000 | 0.8858771 | 0.249000 | 0.3618540 | 54990 |
| 24 | 13537468 | rs7203107 | A | G | 0.217800 | 0.11120 | 0.0501395 | 0.0501558 | 0.985590 | NA | 54990 |
bcf preview
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C . PASS AF=0.991 ES:SE:LP:AF:SS:ID 0.03922:0.1117:0.139363:0.991:54990:rs376342519
1 14933 rs199856693 G A . PASS AF=0.04797 ES:SE:LP:AF:SS:ID 0.03414:0.07154:0.198459:0.04797:54990:rs199856693
1 15774 rs374029747 G A . PASS AF=0.006579 ES:SE:LP:AF:SS:ID -0.03264:0.1778:0.0683388:0.006579:54990:rs374029747
1 16949 rs199745162 A C . PASS AF=0.01675 ES:SE:LP:AF:SS:ID -0.1111:0.09843:0.586868:0.01675:54990:rs199745162
1 51479 rs116400033 T A . PASS AF=0.2321 ES:SE:LP:AF:SS:ID -0.01149:0.03065:0.150212:0.2321:54990:rs116400033
1 52185 rs201374420 TTAA T . PASS AF=0.005882 ES:SE:LP:AF:SS:ID 0.463:1.159:0.161466:0.005882:54990:rs201374420
1 54353 rs140052487 C A . PASS AF=0.001339 ES:SE:LP:AF:SS:ID -0.7972:0.4895:0.985479:0.001339:54990:rs140052487
1 54490 rs141149254 G A . PASS AF=0.1661 ES:SE:LP:AF:SS:ID -0.007739:0.03446:0.0849697:0.1661:54990:rs141149254
1 55164 rs3091274 C A . PASS AF=0.9807 ES:SE:LP:AF:SS:ID 0.04694:0.1034:0.187153:0.9807:54990:rs3091274
1 55326 rs3107975 T C . PASS AF=0.02826 ES:SE:LP:AF:SS:ID 0.02735:0.2013:0.0496838:0.02826:54990:rs3107975
1 55545 rs28396308 C T . PASS AF=0.2248 ES:SE:LP:AF:SS:ID 0.02941:0.0337:0.417028:0.2248:54990:rs28396308
1 57183 rs368339209 A G . PASS AF=0.0007041 ES:SE:LP:AF:SS:ID -0.1715:0.579:0.115205:0.0007041:54990:rs368339209
1 57292 rs201418760 C T . PASS AF=0.02393 ES:SE:LP:AF:SS:ID 0.02425:0.1984:0.0444566:0.02393:54990:rs201418760
1 58814 rs114420996 G A . PASS AF=0.1003 ES:SE:LP:AF:SS:ID 0.05074:0.04762:0.542724:0.1003:54990:rs114420996
1 61543 rs201849102 T C . PASS AF=0.0003079 ES:SE:LP:AF:SS:ID -1.343:1.497:0.432151:0.0003079:54990:rs201849102
1 61743 rs184286948 G C . PASS AF=0.009155 ES:SE:LP:AF:SS:ID 0.1013:0.1408:0.32615:0.009155:54990:rs184286948
1 61920 rs62637820 G A . PASS AF=0.02945 ES:SE:LP:AF:SS:ID 0.08439:0.08137:0.523313:0.02945:54990:rs62637820
1 63093 rs200092917 G A . PASS AF=0.0207 ES:SE:LP:AF:SS:ID 0.2043:0.1038:1.3106:0.0207:54990:rs200092917
1 64649 rs181431124 A C . PASS AF=0.02715 ES:SE:LP:AF:SS:ID 0.1232:0.08864:0.783306:0.02715:54990:rs181431124
1 66219 rs181028663 A T . PASS AF=0.01624 ES:SE:LP:AF:SS:ID 0.06714:0.1122:0.260032:0.01624:54990:rs181028663
1 68082 rs367789441 T C . PASS AF=0.06526 ES:SE:LP:AF:SS:ID -0.02796:0.05295:0.223662:0.06526:54990:rs367789441
1 68596 rs372212855 T G . PASS AF=0.003797 ES:SE:LP:AF:SS:ID -0.2946:0.2104:0.791559:0.003797:54990:rs372212855
1 69428 rs140739101 T G . PASS AF=0.04215 ES:SE:LP:AF:SS:ID -0.09211:0.06756:0.762456:0.04215:54990:rs140739101
1 69534 rs190717287 T C . PASS AF=0.0003164 ES:SE:LP:AF:SS:ID -1.511:0.9223:0.994391:0.0003164:54990:rs190717287
1 69761 rs200505207 A T . PASS AF=0.06821 ES:SE:LP:AF:SS:ID -0.02635:0.05149:0.215525:0.06821:54990:rs200505207
1 69897 rs200676709 T C . PASS AF=0.7661 ES:SE:LP:AF:SS:ID -0.01373:0.03316:0.168194:0.7661:54990:rs200676709
1 72297 rs200651397 G GTAT . PASS AF=0.006341 ES:SE:LP:AF:SS:ID -0.001512:0.1841:0.00287584:0.006341:54990:rs200651397
1 74790 rs13328700 C G . PASS AF=0.03421 ES:SE:LP:AF:SS:ID 0.0602:0.06729:0.430626:0.03421:54990:rs13328700
1 74792 rs13328684 G A . PASS AF=0.03421 ES:SE:LP:AF:SS:ID 0.0602:0.06729:0.430626:0.03421:54990:rs13328684
1 76854 rs367666799 A G . PASS AF=0.06856 ES:SE:LP:AF:SS:ID -0.04211:0.05731:0.334888:0.06856:54990:rs367666799
1 78942 rs372315362 C G . PASS AF=0.01116 ES:SE:LP:AF:SS:ID -1.103:0.9616:0.599635:0.01116:54990:rs372315362
1 80454 rs144226842 G C . PASS AF=0.0004404 ES:SE:LP:AF:SS:ID -20.13:21.35:0.461175:0.0004404:54990:rs144226842
1 81590 rs202072409 AC A . PASS AF=0.004955 ES:SE:LP:AF:SS:ID 1.164:0.9912:0.619066:0.004955:54990:rs202072409
1 82163 rs139113303 G A . PASS AF=0.06791 ES:SE:LP:AF:SS:ID -0.0446:0.05772:0.356844:0.06791:54990:rs139113303
1 82609 rs149189449 C G . PASS AF=0.06818 ES:SE:LP:AF:SS:ID -0.04034:0.05754:0.315873:0.06818:54990:rs149189449
1 83514 rs201754587 C T . PASS AF=0.3501 ES:SE:LP:AF:SS:ID 0.008727:0.03043:0.111091:0.3501:54990:rs201754587
1 84139 rs183605470 A T . PASS AF=0.02132 ES:SE:LP:AF:SS:ID -0.0282:0.1101:0.098106:0.02132:54990:rs183605470
1 86028 rs114608975 T C . PASS AF=0.04742 ES:SE:LP:AF:SS:ID -0.02757:0.06467:0.174055:0.04742:54990:rs114608975
1 86065 rs116504101 G C . PASS AF=0.06995 ES:SE:LP:AF:SS:ID -0.04234:0.05711:0.338755:0.06995:54990:rs116504101
1 86331 rs115209712 A G . PASS AF=0.1018 ES:SE:LP:AF:SS:ID 0.07397:0.04696:0.938547:0.1018:54990:rs115209712
1 87021 rs188486692 T C . PASS AF=0.00763 ES:SE:LP:AF:SS:ID 0.1024:0.1508:0.303469:0.00763:54990:rs188486692
1 87360 rs180907504 C T . PASS AF=0.01853 ES:SE:LP:AF:SS:ID 0.058:0.09429:0.268814:0.01853:54990:rs180907504
1 87409 rs139490478 C T . PASS AF=0.07088 ES:SE:LP:AF:SS:ID -0.04849:0.05661:0.407046:0.07088:54990:rs139490478
1 88169 rs940550 C T . PASS AF=0.2022 ES:SE:LP:AF:SS:ID 0.04623:0.03235:0.815025:0.2022:54990:rs940550
1 88172 rs940551 G A . PASS AF=0.06423 ES:SE:LP:AF:SS:ID -0.05043:0.0538:0.457673:0.06423:54990:rs940551
1 88177 rs143215837 G C . PASS AF=0.06377 ES:SE:LP:AF:SS:ID -0.04397:0.05407:0.380802:0.06377:54990:rs143215837
1 88188 rs148331237 C A . PASS AF=0.007142 ES:SE:LP:AF:SS:ID -0.1485:0.1518:0.484259:0.007142:54990:rs148331237
1 88236 rs186918018 C T . PASS AF=0.01279 ES:SE:LP:AF:SS:ID -0.001019:0.2408:0.00147912:0.01279:54990:rs186918018
1 88316 rs113759966 G A . PASS AF=0.06376 ES:SE:LP:AF:SS:ID -0.04171:0.05425:0.354578:0.06376:54990:rs113759966
1 88338 rs55700207 G A . PASS AF=0.08209 ES:SE:LP:AF:SS:ID 0.06568:0.05218:0.681728:0.08209:54990:rs55700207