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-1121/ieu-a-1121.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-1121/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 16:13:26 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1121/ieu-a-1121.vcf.gz ...
Read summary statistics for 15635757 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: 0.0602 (0.0133)
Lambda GC: 1.0604
Mean Chi^2: 1.0871
Intercept: 1.0243 (0.0069)
Ratio: 0.2784 (0.0786)
Analysis finished at Tue Feb 4 16:16:03 2020
Total time elapsed: 2.0m:36.99sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9604,
"inflation_factor": 1.0552,
"mean_EFFECT": -0.2376,
"n": 53978,
"n_snps": 15635757,
"n_clumped_hits": 16,
"n_p_sig": 4156,
"n_mono": 0,
"n_ns": 786352,
"n_mac": 269927,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 5006,
"n_miss_AF_reference": 162878,
"n_est": 51651.4528,
"ratio_se_n": 0.9782,
"mean_diff": 0.2467,
"ratio_diff": 2.7103,
"sd_y_est1": 2.8548,
"sd_y_est2": 2.7926,
"r2_sum1": 0.1401,
"r2_sum2": 0.0172,
"r2_sum3": 0.018,
"r2_sum4": 0.021,
"ldsc_nsnp_merge_refpanel_ld": 1218951,
"ldsc_nsnp_merge_regression_ld": 1218951,
"ldsc_observed_scale_h2_beta": 0.0602,
"ldsc_observed_scale_h2_se": 0.0133,
"ldsc_intercept_beta": 1.0243,
"ldsc_intercept_se": 0.0069,
"ldsc_lambda_gc": 1.0604,
"ldsc_mean_chisq": 1.0871,
"ldsc_ratio": 0.279
}
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 | 15635755 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 101 | 0 | 37882 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 105 | 0 | 18193 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.958477e+00 | 6.312051e+00 | 1.0000e+00 | 4.000000e+00 | 7.000000e+00 | 1.400000e+01 | 2.400000e+01 | ▇▆▂▃▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.932522e+07 | 5.676282e+07 | 5.6000e+01 | 3.254872e+07 | 6.974966e+07 | 1.158559e+08 | 2.492402e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -2.376291e-01 | 2.406417e+00 | -2.0410e+01 | -4.081000e-02 | -2.197000e-04 | 3.887000e-02 | 2.037000e+01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.231001e-01 | 6.108504e+00 | 1.5820e-03 | 2.208000e-02 | 6.466000e-02 | 2.513000e-01 | 1.000000e+03 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.915288e-01 | 2.905065e-01 | 0.0000e+00 | 2.375998e-01 | 4.884004e-01 | 7.434008e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.915523e-01 | 2.904962e-01 | 0.0000e+00 | 2.376748e-01 | 4.883844e-01 | 7.433909e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 5006 | 0.9996798 | NA | NA | NA | NA | NA | 1.534350e-01 | 2.447970e-01 | 0.0000e+00 | 1.995000e-03 | 1.989000e-02 | 2.061000e-01 | 9.999980e-01 | ▇▁▁▁▁ |
| numeric | AF_reference | 162878 | 0.9895830 | NA | NA | NA | NA | NA | 1.531725e-01 | 2.322675e-01 | 0.0000e+00 | 2.595800e-03 | 3.055110e-02 | 2.122600e-01 | 1.000000e+00 | ▇▁▁▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.397800e+04 | 0.000000e+00 | 5.3978e+04 | 5.397800e+04 | 5.397800e+04 | 5.397800e+04 | 5.397800e+04 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 10616 | rs376342519 | CCGCCGTTGCAAAGGCGCGCCG | C | 0.03490 | 0.11470 | 0.7609007 | 0.7609207 | 0.991000 | 0.9930110 | 53978 |
| 1 | 14933 | rs199856693 | G | A | 0.03889 | 0.07369 | 0.5976006 | 0.5976719 | 0.047970 | 0.0283546 | 53978 |
| 1 | 15774 | rs374029747 | G | A | -0.12340 | 0.18690 | 0.5088995 | 0.5090959 | 0.006579 | 0.0119808 | 53978 |
| 1 | 16949 | rs199745162 | A | C | -0.11620 | 0.10220 | 0.2555001 | 0.2555440 | 0.016750 | 0.0139776 | 53978 |
| 1 | 51479 | rs116400033 | T | A | -0.01086 | 0.03159 | 0.7309994 | 0.7310120 | 0.232100 | 0.1281950 | 53978 |
| 1 | 52185 | rs201374420 | TTAA | T | 0.53560 | 1.16000 | 0.6442998 | 0.6442792 | 0.005882 | 0.0053914 | 53978 |
| 1 | 54353 | rs140052487 | C | A | -0.74990 | 0.50550 | 0.1380000 | 0.1379465 | 0.001339 | 0.0089856 | 53978 |
| 1 | 54490 | rs141149254 | G | A | -0.01122 | 0.03554 | 0.7522999 | 0.7522298 | 0.166100 | 0.0960463 | 53978 |
| 1 | 55164 | rs3091274 | C | A | 0.06106 | 0.10690 | 0.5677995 | 0.5678722 | 0.980700 | 0.9233230 | 53978 |
| 1 | 55326 | rs3107975 | T | C | 0.02660 | 0.20440 | 0.8965000 | 0.8964580 | 0.028260 | 0.0459265 | 53978 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154926843 | rs192521690 | T | C | -0.126500 | 0.34920 | 0.7171995 | 0.7171603 | 0.002532 | 0.0007947 | 53978 |
| 23 | 154927185 | rs185685661 | T | C | -0.003081 | 0.03367 | 0.9271000 | 0.9270907 | 0.139300 | 0.1796030 | 53978 |
| 23 | 154927199 | rs645904 | C | T | 0.003126 | 0.01820 | 0.8635999 | 0.8636276 | 0.248000 | 0.3674170 | 53978 |
| 23 | 154927581 | rs644138 | G | A | -0.006215 | 0.01757 | 0.7235008 | 0.7235428 | 0.299900 | 0.4635760 | 53978 |
| 23 | 154928151 | rs144607509 | C | T | 0.625300 | 0.80860 | 0.4393999 | 0.4393378 | 0.018780 | 0.0084768 | 53978 |
| 23 | 154928909 | rs148015245 | C | T | -5.230000 | 2.23300 | 0.0191801 | 0.0191735 | 0.004206 | 0.0007947 | 53978 |
| 23 | 154929412 | rs557132 | C | T | 0.002876 | 0.01818 | 0.8743000 | 0.8743025 | 0.250400 | 0.3568210 | 53978 |
| 23 | 154929952 | rs4012982 | CAA | C | 0.007709 | 0.02639 | 0.7702009 | 0.7701962 | 0.250900 | 0.3165560 | 53978 |
| 23 | 154930230 | rs781880 | A | G | 0.002489 | 0.01821 | 0.8913000 | 0.8912813 | 0.249000 | 0.3618540 | 53978 |
| 24 | 13537468 | rs7203107 | A | G | 0.234000 | 0.11460 | 0.0411604 | 0.0411630 | 0.985590 | NA | 53978 |
bcf preview
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C . PASS AF=0.991 ES:SE:LP:AF:SS:ID 0.0349:0.1147:0.118672:0.991:53978:rs376342519
1 14933 rs199856693 G A . PASS AF=0.04797 ES:SE:LP:AF:SS:ID 0.03889:0.07369:0.223589:0.04797:53978:rs199856693
1 15774 rs374029747 G A . PASS AF=0.006579 ES:SE:LP:AF:SS:ID -0.1234:0.1869:0.293368:0.006579:53978:rs374029747
1 16949 rs199745162 A C . PASS AF=0.01675 ES:SE:LP:AF:SS:ID -0.1162:0.1022:0.592609:0.01675:53978:rs199745162
1 51479 rs116400033 T A . PASS AF=0.2321 ES:SE:LP:AF:SS:ID -0.01086:0.03159:0.136083:0.2321:53978:rs116400033
1 52185 rs201374420 TTAA T . PASS AF=0.005882 ES:SE:LP:AF:SS:ID 0.5356:1.16:0.190912:0.005882:53978:rs201374420
1 54353 rs140052487 C A . PASS AF=0.001339 ES:SE:LP:AF:SS:ID -0.7499:0.5055:0.860121:0.001339:53978:rs140052487
1 54490 rs141149254 G A . PASS AF=0.1661 ES:SE:LP:AF:SS:ID -0.01122:0.03554:0.123609:0.1661:53978:rs141149254
1 55164 rs3091274 C A . PASS AF=0.9807 ES:SE:LP:AF:SS:ID 0.06106:0.1069:0.245805:0.9807:53978:rs3091274
1 55326 rs3107975 T C . PASS AF=0.02826 ES:SE:LP:AF:SS:ID 0.0266:0.2044:0.0474497:0.02826:53978:rs3107975
1 55545 rs28396308 C T . PASS AF=0.2248 ES:SE:LP:AF:SS:ID 0.03886:0.03473:0.579549:0.2248:53978:rs28396308
1 57183 rs368339209 A G . PASS AF=0.0007041 ES:SE:LP:AF:SS:ID -0.2126:0.6065:0.139123:0.0007041:53978:rs368339209
1 57292 rs201418760 C T . PASS AF=0.02393 ES:SE:LP:AF:SS:ID 0.02247:0.2013:0.040434:0.02393:53978:rs201418760
1 58814 rs114420996 G A . PASS AF=0.1003 ES:SE:LP:AF:SS:ID 0.04123:0.04913:0.396531:0.1003:53978:rs114420996
1 61543 rs201849102 T C . PASS AF=0.0003079 ES:SE:LP:AF:SS:ID -1.309:1.511:0.412963:0.0003079:53978:rs201849102
1 61743 rs184286948 G C . PASS AF=0.009155 ES:SE:LP:AF:SS:ID 0.09065:0.1453:0.273599:0.009155:53978:rs184286948
1 61920 rs62637820 G A . PASS AF=0.02945 ES:SE:LP:AF:SS:ID 0.09099:0.08392:0.555643:0.02945:53978:rs62637820
1 63093 rs200092917 G A . PASS AF=0.0207 ES:SE:LP:AF:SS:ID 0.2107:0.1072:1.30759:0.0207:53978:rs200092917
1 64649 rs181431124 A C . PASS AF=0.02715 ES:SE:LP:AF:SS:ID 0.1248:0.0915:0.762959:0.02715:53978:rs181431124
1 66219 rs181028663 A T . PASS AF=0.01624 ES:SE:LP:AF:SS:ID 0.063:0.1158:0.231806:0.01624:53978:rs181028663
1 68082 rs367789441 T C . PASS AF=0.06526 ES:SE:LP:AF:SS:ID -0.03789:0.05447:0.312739:0.06526:53978:rs367789441
1 68596 rs372212855 T G . PASS AF=0.003797 ES:SE:LP:AF:SS:ID -0.3325:0.2195:0.88706:0.003797:53978:rs372212855
1 69428 rs140739101 T G . PASS AF=0.04215 ES:SE:LP:AF:SS:ID -0.09426:0.06959:0.755475:0.04215:53978:rs140739101
1 69534 rs190717287 T C . PASS AF=0.0003164 ES:SE:LP:AF:SS:ID -1.265:0.9312:0.758703:0.0003164:53978:rs190717287
1 69761 rs200505207 A T . PASS AF=0.06821 ES:SE:LP:AF:SS:ID -0.03409:0.05295:0.284331:0.06821:53978:rs200505207
1 69897 rs200676709 T C . PASS AF=0.7661 ES:SE:LP:AF:SS:ID -0.02085:0.03419:0.266001:0.7661:53978:rs200676709
1 72297 rs200651397 G GTAT . PASS AF=0.006341 ES:SE:LP:AF:SS:ID -0.06657:0.1908:0.138406:0.006341:53978:rs200651397
1 74790 rs13328700 C G . PASS AF=0.03421 ES:SE:LP:AF:SS:ID 0.06374:0.06936:0.445996:0.03421:53978:rs13328700
1 74792 rs13328684 G A . PASS AF=0.03421 ES:SE:LP:AF:SS:ID 0.06374:0.06936:0.445996:0.03421:53978:rs13328684
1 76854 rs367666799 A G . PASS AF=0.06856 ES:SE:LP:AF:SS:ID -0.03686:0.05907:0.273599:0.06856:53978:rs367666799
1 78942 rs372315362 C G . PASS AF=0.01116 ES:SE:LP:AF:SS:ID -2.338:1.251:1.21021:0.01116:53978:rs372315362
1 80454 rs144226842 G C . PASS AF=0.0004404 ES:SE:LP:AF:SS:ID -20.13:21.55:0.455436:0.0004404:53978:rs144226842
1 81590 rs202072409 AC A . PASS AF=0.004955 ES:SE:LP:AF:SS:ID 1.196:0.9898:0.644357:0.004955:53978:rs202072409
1 82163 rs139113303 G A . PASS AF=0.06791 ES:SE:LP:AF:SS:ID -0.03982:0.05948:0.298259:0.06791:53978:rs139113303
1 82609 rs149189449 C G . PASS AF=0.06818 ES:SE:LP:AF:SS:ID -0.03689:0.05931:0.27254:0.06818:53978:rs149189449
1 83514 rs201754587 C T . PASS AF=0.3501 ES:SE:LP:AF:SS:ID 0.001985:0.03137:0.022505:0.3501:53978:rs201754587
1 84139 rs183605470 A T . PASS AF=0.02132 ES:SE:LP:AF:SS:ID -0.1017:0.1146:0.426548:0.02132:53978:rs183605470
1 86028 rs114608975 T C . PASS AF=0.04742 ES:SE:LP:AF:SS:ID -0.03854:0.06659:0.249723:0.04742:53978:rs114608975
1 86065 rs116504101 G C . PASS AF=0.06995 ES:SE:LP:AF:SS:ID -0.03729:0.0588:0.279014:0.06995:53978:rs116504101
1 86331 rs115209712 A G . PASS AF=0.1018 ES:SE:LP:AF:SS:ID 0.09207:0.04824:1.24941:0.1018:53978:rs115209712
1 87021 rs188486692 T C . PASS AF=0.00763 ES:SE:LP:AF:SS:ID 0.1007:0.1547:0.288108:0.00763:53978:rs188486692
1 87360 rs180907504 C T . PASS AF=0.01853 ES:SE:LP:AF:SS:ID 0.04605:0.09713:0.196953:0.01853:53978:rs180907504
1 87409 rs139490478 C T . PASS AF=0.07088 ES:SE:LP:AF:SS:ID -0.04254:0.05829:0.33208:0.07088:53978:rs139490478
1 88169 rs940550 C T . PASS AF=0.2022 ES:SE:LP:AF:SS:ID 0.05078:0.03333:0.894149:0.2022:53978:rs940550
1 88172 rs940551 G A . PASS AF=0.06423 ES:SE:LP:AF:SS:ID -0.06005:0.05532:0.556424:0.06423:53978:rs940551
1 88177 rs143215837 G C . PASS AF=0.06377 ES:SE:LP:AF:SS:ID -0.05466:0.0556:0.487316:0.06377:53978:rs143215837
1 88188 rs148331237 C A . PASS AF=0.007142 ES:SE:LP:AF:SS:ID -0.1546:0.157:0.488651:0.007142:53978:rs148331237
1 88236 rs186918018 C T . PASS AF=0.01279 ES:SE:LP:AF:SS:ID 0.01523:0.246:0.0220022:0.01279:53978:rs186918018
1 88316 rs113759966 G A . PASS AF=0.06376 ES:SE:LP:AF:SS:ID -0.05522:0.0558:0.49174:0.06376:53978:rs113759966
1 88338 rs55700207 G A . PASS AF=0.08209 ES:SE:LP:AF:SS:ID 0.05008:0.05396:0.451733:0.08209:53978:rs55700207