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/ukb-d-import/processed/ukb-d-30190_irnt/ukb-d-30190_irnt.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/ukb-d-import/processed/ukb-d-30190_irnt/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Mon Nov 25 14:52:28 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-30190_irnt/ukb-d-30190_irnt.vcf.gz ...
Read summary statistics for 13586282 SNPs.
Dropped 12710 SNPs with duplicated rs numbers.
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, 1283504 SNPs remain.
After merging with regression SNP LD, 1283504 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1748 (0.0195)
Lambda GC: 1.4204
Mean Chi^2: 2.302
Intercept: 1.1643 (0.0215)
Ratio: 0.1262 (0.0165)
Analysis finished at Mon Nov 25 14:54:45 2019
Total time elapsed: 2.0m:17.17sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9521,
"inflation_factor": 1.2862,
"mean_EFFECT": -0.0001,
"n": 349861,
"n_snps": 13586282,
"n_clumped_hits": 324,
"n_p_sig": 63422,
"n_mono": 0,
"n_ns": 1251790,
"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": 569186,
"n_est": 351190.5877,
"ratio_se_n": 1.0019,
"mean_diff": -3.0698e-06,
"ratio_diff": 19.7084,
"sd_y_est1": 0.9695,
"sd_y_est2": 0.9713,
"r2_sum1": 0.1189,
"r2_sum2": 0.1265,
"r2_sum3": 0.126,
"r2_sum4": 0.1246,
"ldsc_nsnp_merge_refpanel_ld": 1283504,
"ldsc_nsnp_merge_regression_ld": 1283504,
"ldsc_observed_scale_h2_beta": 0.1748,
"ldsc_observed_scale_h2_se": 0.0195,
"ldsc_intercept_beta": 1.1643,
"ldsc_intercept_se": 0.0215,
"ldsc_lambda_gc": 1.4204,
"ldsc_mean_chisq": 2.302,
"ldsc_ratio": 0.1262
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | TRUE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | TRUE |
| 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 | 94 | 0 | 13574236 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 57080 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 33337 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
| numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.051329e+00 | 6.184984e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.902513e+07 | 5.591486e+07 | 3.02000e+02 | 3.293100e+07 | 7.013871e+07 | 1.148589e+08 | 2.492309e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -9.870000e-05 | 1.444310e-02 | -5.43604e-01 | -4.325900e-03 | -6.060000e-05 | 4.162500e-03 | 4.435560e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.739200e-03 | 9.394800e-03 | 1.90500e-03 | 2.772800e-03 | 5.109600e-03 | 1.399600e-02 | 4.768680e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.576464e-01 | 3.018987e-01 | 0.00000e+00 | 1.860602e-01 | 4.443099e-01 | 7.192850e-01 | 1.000000e+00 | ▇▆▆▆▆ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.576460e-01 | 3.018989e-01 | 0.00000e+00 | 1.860596e-01 | 4.443098e-01 | 7.192849e-01 | 9.999999e-01 | ▇▆▆▆▆ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.908059e-01 | 2.544033e-01 | 1.00000e-03 | 7.430400e-03 | 6.003370e-02 | 2.953180e-01 | 9.989990e-01 | ▇▂▁▁▁ |
| numeric | AF_reference | 569186 | 0.9581058 | NA | NA | NA | NA | NA | 1.963355e-01 | 2.471013e-01 | 0.00000e+00 | 5.591000e-03 | 8.426520e-02 | 3.081070e-01 | 1.000000e+00 | ▇▂▁▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.498610e+05 | 0.000000e+00 | 3.49861e+05 | 3.498610e+05 | 3.498610e+05 | 3.498610e+05 | 3.498610e+05 | ▁▁▇▁▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 692794 | rs530212009 | CA | C | 0.0016317 | 0.0040578 | 0.6876050 | 0.6876056 | 0.1106490 | 0.1894970 | 349861 |
| 1 | 693731 | rs12238997 | A | G | 0.0033160 | 0.0038344 | 0.3871346 | 0.3871349 | 0.1158220 | 0.1417730 | 349861 |
| 1 | 707522 | rs371890604 | G | C | 0.0059343 | 0.0043121 | 0.1687641 | 0.1687635 | 0.0972503 | 0.1293930 | 349861 |
| 1 | 717587 | rs144155419 | G | A | -0.0009170 | 0.0102750 | 0.9288860 | 0.9288859 | 0.0157178 | 0.0045926 | 349861 |
| 1 | 723329 | rs189787166 | A | T | -0.0739004 | 0.0305011 | 0.0153986 | 0.0153982 | 0.0017201 | 0.0003994 | 349861 |
| 1 | 730087 | rs148120343 | T | C | -0.0016021 | 0.0053396 | 0.7641489 | 0.7641487 | 0.0564796 | 0.0127796 | 349861 |
| 1 | 731718 | rs142557973 | T | C | 0.0028719 | 0.0036363 | 0.4296512 | 0.4296510 | 0.1217450 | 0.1543530 | 349861 |
| 1 | 732032 | rs61770163 | A | C | 0.0049571 | 0.0038794 | 0.2013219 | 0.2013215 | 0.1211440 | 0.1555510 | 349861 |
| 1 | 734349 | rs141242758 | T | C | 0.0029139 | 0.0036382 | 0.4231896 | 0.4231902 | 0.1209740 | 0.1525560 | 349861 |
| 1 | 740284 | rs61770167 | C | T | 0.0026839 | 0.0166445 | 0.8719000 | 0.8719001 | 0.0057855 | 0.0023962 | 349861 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 23 | 154923311 | rs141127553 | C | T | 0.0018841 | 0.0041993 | 0.6536692 | 0.6536684 | 0.0561652 | 0.0309934 | 349861 |
| 23 | 154923374 | rs111332691 | T | A | -0.0081440 | 0.0046165 | 0.0777159 | 0.0777155 | 0.0447935 | 0.0116556 | 349861 |
| 23 | 154925045 | rs509981 | C | T | 0.0085339 | 0.0022216 | 0.0001224 | 0.0001224 | 0.2454440 | 0.3634440 | 349861 |
| 23 | 154925895 | rs538470 | C | T | 0.0083432 | 0.0022724 | 0.0002412 | 0.0002412 | 0.2417890 | 0.3634440 | 349861 |
| 23 | 154927581 | rs644138 | G | A | 0.0078866 | 0.0020890 | 0.0001599 | 0.0001598 | 0.3020040 | 0.4635760 | 349861 |
| 23 | 154929412 | rs557132 | C | T | 0.0084853 | 0.0022223 | 0.0001344 | 0.0001344 | 0.2452990 | 0.3568210 | 349861 |
| 23 | 154929637 | rs35185538 | CT | C | 0.0074496 | 0.0023196 | 0.0013199 | 0.0013197 | 0.2295300 | 0.3011920 | 349861 |
| 23 | 154929952 | rs4012982 | CAA | C | 0.0086751 | 0.0023374 | 0.0002061 | 0.0002060 | 0.2392530 | 0.3165560 | 349861 |
| 23 | 154930230 | rs781880 | A | G | 0.0085900 | 0.0022219 | 0.0001106 | 0.0001106 | 0.2457090 | 0.3618540 | 349861 |
| 23 | 154930487 | rs781879 | T | A | 0.0024456 | 0.0076275 | 0.7484865 | 0.7484860 | 0.0195209 | 0.1263580 | 349861 |
bcf preview
1 692794 rs530212009 CA C . PASS AF=0.110649 ES:SE:LP:AF:SS:ID 0.00163166:0.00405778:0.162661:0.110649:349861:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.115822 ES:SE:LP:AF:SS:ID 0.00331605:0.00383436:0.412138:0.115822:349861:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0972503 ES:SE:LP:AF:SS:ID 0.0059343:0.00431213:0.77272:0.0972503:349861:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0157178 ES:SE:LP:AF:SS:ID -0.000917009:0.010275:0.0320376:0.0157178:349861:rs144155419
1 723329 rs189787166 A T . PASS AF=0.00172013 ES:SE:LP:AF:SS:ID -0.0739004:0.0305011:1.81252:0.00172013:349861:rs189787166
1 730087 rs148120343 T C . PASS AF=0.0564796 ES:SE:LP:AF:SS:ID -0.00160207:0.00533957:0.116822:0.0564796:349861:rs148120343
1 731718 rs58276399 T C . PASS AF=0.121745 ES:SE:LP:AF:SS:ID 0.00287191:0.0036363:0.366884:0.121745:349861:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121144 ES:SE:LP:AF:SS:ID 0.00495708:0.0038794:0.696109:0.121144:349861:rs61770163
1 734349 rs141242758 T C . PASS AF=0.120974 ES:SE:LP:AF:SS:ID 0.00291387:0.00363825:0.373465:0.120974:349861:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00578551 ES:SE:LP:AF:SS:ID 0.00268385:0.0166445:0.0595333:0.00578551:349861:rs61770167
1 742813 rs112573343 C T . PASS AF=0.00188271 ES:SE:LP:AF:SS:ID -0.0259068:0.0314338:0.387381:0.00188271:349861:rs112573343
1 749963 rs529266287 T TAA . PASS AF=0.869759 ES:SE:LP:AF:SS:ID -0.00412829:0.00358712:0.602427:0.869759:349861:rs529266287
1 750230 rs190826124 G C . PASS AF=0.00153174 ES:SE:LP:AF:SS:ID -0.0309416:0.0324536:0.468033:0.00153174:349861:rs190826124
1 751343 rs28544273 T A . PASS AF=0.122895 ES:SE:LP:AF:SS:ID 0.00358488:0.00355231:0.504603:0.122895:349861:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.142708 ES:SE:LP:AF:SS:ID 0.0045775:0.00351134:0.715887:0.142708:349861:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123012 ES:SE:LP:AF:SS:ID 0.00359086:0.00354734:0.506666:0.123012:349861:rs28527770
1 753405 rs3115860 C A . PASS AF=0.870893 ES:SE:LP:AF:SS:ID -0.00261845:0.00345672:0.347992:0.870893:349861:rs3115860
1 753425 rs3131970 T C . PASS AF=0.875492 ES:SE:LP:AF:SS:ID -0.00389256:0.00351411:0.571873:0.875492:349861:rs3131970
1 753541 rs2073813 G A . PASS AF=0.128631 ES:SE:LP:AF:SS:ID 0.00290638:0.00346533:0.396166:0.128631:349861:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0363487 ES:SE:LP:AF:SS:ID 0.00451351:0.00629004:0.325114:0.0363487:349861:rs12184325
1 754182 rs3131969 A G . PASS AF=0.870486 ES:SE:LP:AF:SS:ID -0.00281623:0.00345308:0.382218:0.870486:349861:rs3131969
1 754192 rs3131968 A G . PASS AF=0.870587 ES:SE:LP:AF:SS:ID -0.00282813:0.0034546:0.384067:0.870587:349861:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870481 ES:SE:LP:AF:SS:ID -0.00279268:0.00345294:0.378158:0.870481:349861:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00504546 ES:SE:LP:AF:SS:ID -0.00476762:0.0177299:0.103471:0.00504546:349861:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00501229 ES:SE:LP:AF:SS:ID -0.00439335:0.0177771:0.0943099:0.00501229:349861:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00558051 ES:SE:LP:AF:SS:ID 0.00260732:0.0171786:0.0558318:0.00558051:349861:rs184270342
1 755890 rs3115858 A T . PASS AF=0.870566 ES:SE:LP:AF:SS:ID -0.00274967:0.00344689:0.371579:0.870566:349861:rs3115858
1 756434 rs61768170 G C . PASS AF=0.125972 ES:SE:LP:AF:SS:ID 0.00320924:0.00351736:0.441821:0.125972:349861:rs61768170
1 756604 rs3131962 A G . PASS AF=0.87013 ES:SE:LP:AF:SS:ID -0.0028164:0.00343858:0.384309:0.87013:349861:rs3131962
1 757640 rs3115853 G A . PASS AF=0.869408 ES:SE:LP:AF:SS:ID -0.00289924:0.00343532:0.399357:0.869408:349861:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870284 ES:SE:LP:AF:SS:ID -0.00301374:0.00344156:0.418848:0.870284:349861:rs4951929
1 757936 rs4951862 C A . PASS AF=0.87029 ES:SE:LP:AF:SS:ID -0.00301716:0.00344181:0.419425:0.87029:349861:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870299 ES:SE:LP:AF:SS:ID -0.00302102:0.00344192:0.420103:0.870299:349861:rs3131956
1 758626 rs3131954 C T . PASS AF=0.87074 ES:SE:LP:AF:SS:ID -0.00280572:0.00345068:0.380734:0.87074:349861:rs3131954
1 759293 rs10157329 T A . PASS AF=0.098799 ES:SE:LP:AF:SS:ID 0.0046386:0.00401111:0.60642:0.098799:349861:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00647255 ES:SE:LP:AF:SS:ID 0.000210369:0.0155194:0.00472248:0.00647255:349861:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.874649 ES:SE:LP:AF:SS:ID -0.00388264:0.00350224:0.572519:0.874649:349861:rs3115851
1 761732 rs2286139 C T . PASS AF=0.864035 ES:SE:LP:AF:SS:ID -0.00246702:0.00343435:0.325551:0.864035:349861:rs2286139
1 761752 rs1057213 C T . PASS AF=0.869419 ES:SE:LP:AF:SS:ID -0.00359517:0.00346771:0.523094:0.869419:349861:rs1057213
1 762273 rs3115849 G A . PASS AF=0.866376 ES:SE:LP:AF:SS:ID -0.00211853:0.00346851:0.266531:0.866376:349861:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0987125 ES:SE:LP:AF:SS:ID 0.00282151:0.00415389:0.303659:0.0987125:349861:rs12095200
1 762589 rs3115848 G C . PASS AF=0.871561 ES:SE:LP:AF:SS:ID -0.0035874:0.00350801:0.513594:0.871561:349861:rs3115848
1 762592 rs3131950 C G . PASS AF=0.871561 ES:SE:LP:AF:SS:ID -0.00358751:0.00350801:0.513615:0.871561:349861:rs3131950
1 762601 rs3131949 T C . PASS AF=0.87156 ES:SE:LP:AF:SS:ID -0.00358511:0.00350807:0.513145:0.87156:349861:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871932 ES:SE:LP:AF:SS:ID -0.003657:0.00351007:0.526547:0.871932:349861:rs3131948
1 764191 rs7515915 T G . PASS AF=0.125555 ES:SE:LP:AF:SS:ID 0.00376918:0.00351281:0.547784:0.125555:349861:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105385 ES:SE:LP:AF:SS:ID 0.00501327:0.00382498:0.72131:0.105385:349861:rs61768174
1 766105 rs2519015 T A . PASS AF=0.855372 ES:SE:LP:AF:SS:ID -0.00107985:0.00343339:0.123129:0.855372:349861:rs2519015
1 767393 rs538667473 A C . PASS AF=0.00164253 ES:SE:LP:AF:SS:ID -0.0647629:0.0305541:1.46802:0.00164253:349861:rs538667473
1 768116 rs376645387 A AGTTTT . PASS AF=0.838283 ES:SE:LP:AF:SS:ID -0.00172163:0.00338173:0.214183:0.838283:349861:rs376645387