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"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-d-41220_7/ukb-d-41220_7.vcf.gz; Date=Sun May 10 05:37:18 2020"
}
*********************************************************************
* 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-41220_7/ukb-d-41220_7.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-41220_7/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 16:52:55 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-41220_7/ukb-d-41220_7.vcf.gz ...
Read summary statistics for 9685742 SNPs.
Dropped 7299 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, 1274777 SNPs remain.
After merging with regression SNP LD, 1274777 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0252 (0.2942)
Lambda GC: 1.0021
Mean Chi^2: 0.999
Intercept: 0.9983 (0.0058)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 16:54:22 2019
Total time elapsed: 1.0m:27.08s
{
"af_correlation": 0.9397,
"inflation_factor": 0.9999,
"mean_EFFECT": 0,
"n": 1460,
"n_snps": 9685742,
"n_clumped_hits": 0,
"n_p_sig": 0,
"n_mono": 0,
"n_ns": 1062489,
"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": 192962,
"n_est": 1457.6572,
"ratio_se_n": 0.9992,
"mean_diff": 0,
"ratio_diff": 42.4874,
"sd_y_est1": 0.5027,
"sd_y_est2": 0.5023,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1274777,
"ldsc_nsnp_merge_regression_ld": 1274777,
"ldsc_observed_scale_h2_beta": 0.0252,
"ldsc_observed_scale_h2_se": 0.2942,
"ldsc_intercept_beta": 0.9983,
"ldsc_intercept_se": 0.0058,
"ldsc_lambda_gc": 1.0021,
"ldsc_mean_chisq": 0.999,
"ldsc_ratio": 1.7
}
name | value |
---|---|
af_correlation | FALSE |
inflation_factor | FALSE |
n | TRUE |
is_snpid_non_unique | TRUE |
mean_EFFECT_nonfinite | FALSE |
mean_EFFECT_05 | FALSE |
mean_EFFECT_01 | FALSE |
mean_chisq | FALSE |
n_p_sig | FALSE |
miss_EFFECT | FALSE |
miss_SE | FALSE |
miss_PVAL | FALSE |
ldsc_ratio | TRUE |
ldsc_intercept_beta | FALSE |
n_clumped_hits | FALSE |
r2_sum1 | FALSE |
r2_sum2 | FALSE |
r2_sum3 | FALSE |
r2_sum4 | FALSE |
General metrics
af_correlation
: Correlation coefficient between AF
and AF_reference
.inflation_factor
(lambda
): Genomic inflation factor.mean_EFFECT
: Mean of EFFECT
size.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 below 5e-8
.n_mono
: Number of monomorphic (MAF == 1
or MAF == 0
) SNPs.n_ns
: Number of SNPs with nonsense values:
A, C, G or T
.< 0
or > 1
.<= 0
or = Infinity
).< 0
or > 1
.n_mac
: Number of cases where MAC
(\(2 \times N \times MAF\)) is less than 6
.is_snpid_unique
: true
if the combination of ID
REF
ALT
is unique and therefore no duplication in snpid.n_miss_<*>
: Number of NA
observations 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 expect ratio_se_n
to 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.
ratio_diff
: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff
and the mean of diff2
(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.
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.
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.
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>
: r2
statistics under various assumptions
1
: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).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
: NOT is_snpid_unique
.mean_EFFECT_nonfinite
: mean(EFFECT)
is NA
, NaN
, or Inf
.mean_EFFECT_05
: abs(mean(EFFECT))
> 0.5.mean_EFFECT_01
: abs(mean(EFFECT))
> 0.1.mean_chisq
: ldsc_mean_chisq
> 1.3 or ldsc_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<*>
> 0.5Plots
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 | 9678989 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 98 | 0 | 47032 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 29681 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.079802e+00 | 6.175351e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.873251e+07 | 5.611160e+07 | 302.0000000 | 3.243354e+07 | 6.961084e+07 | 1.147459e+08 | 2.492297e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.420000e-05 | 4.181490e-02 | -0.4117890 | -1.996380e-02 | -1.730000e-05 | 2.005020e-02 | 3.957120e-01 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.638360e-02 | 2.070990e-02 | 0.0175037 | 2.037690e-02 | 2.716640e-02 | 4.654000e-02 | 1.192600e-01 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.002748e-01 | 2.884610e-01 | 0.0000015 | 2.506998e-01 | 5.000265e-01 | 7.499374e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.001637e-01 | 2.885278e-01 | 0.0000014 | 2.505076e-01 | 4.999188e-01 | 7.498914e-01 | 9.999999e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.619298e-01 | 2.628627e-01 | 0.0099060 | 4.432720e-02 | 1.598680e-01 | 4.167570e-01 | 9.900940e-01 | ▇▂▂▁▁ |
numeric | AF_reference | 192962 | 0.9800777 | NA | NA | NA | NA | NA | 2.613654e-01 | 2.536764e-01 | 0.0000000 | 5.031950e-02 | 1.751200e-01 | 4.123400e-01 | 1.000000e+00 | ▇▃▂▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.460000e+03 | 0.000000e+00 | 1460.0000000 | 1.460000e+03 | 1.460000e+03 | 1.460000e+03 | 1.460000e+03 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | -0.0404234 | 0.0309245 | 0.1913670 | 0.1911569 | 0.1185430 | 0.1894970 | 1460 |
1 | 693731 | rs12238997 | A | G | -0.0208518 | 0.0298441 | 0.4848585 | 0.4847452 | 0.1239850 | 0.1417730 | 1460 |
1 | 707522 | rs371890604 | G | C | -0.0292280 | 0.0329951 | 0.3758590 | 0.3757099 | 0.1050130 | 0.1293930 | 1460 |
1 | 717587 | rs144155419 | G | A | -0.0593015 | 0.0844093 | 0.4824530 | 0.4823381 | 0.0154768 | 0.0045926 | 1460 |
1 | 730087 | rs148120343 | T | C | -0.0338285 | 0.0408409 | 0.4076402 | 0.4075009 | 0.0634515 | 0.0127796 | 1460 |
1 | 731718 | rs142557973 | T | C | -0.0165202 | 0.0284344 | 0.5613361 | 0.5612449 | 0.1301520 | 0.1543530 | 1460 |
1 | 732032 | rs61770163 | A | C | -0.0232824 | 0.0299059 | 0.4363892 | 0.4362614 | 0.1299570 | 0.1555510 | 1460 |
1 | 734349 | rs141242758 | T | C | -0.0192172 | 0.0283532 | 0.4980214 | 0.4979119 | 0.1292980 | 0.1525560 | 1460 |
1 | 749963 | rs529266287 | T | TAA | 0.0232823 | 0.0275823 | 0.3987521 | 0.3986119 | 0.8603010 | 0.7641770 | 1460 |
1 | 751343 | rs28544273 | T | A | -0.0241191 | 0.0273148 | 0.3773810 | 0.3772337 | 0.1339860 | 0.2426120 | 1460 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0089661 | 0.0407236 | 0.8257700 | 0.8257385 | 0.0556433 | 0.0309934 | 1460 |
23 | 154923374 | rs111332691 | T | A | -0.0009268 | 0.0427101 | 0.9826900 | 0.9826867 | 0.0482877 | 0.0116556 | 1460 |
23 | 154925045 | rs509981 | C | T | -0.0052043 | 0.0211243 | 0.8054330 | 0.8053978 | 0.2511710 | 0.3634440 | 1460 |
23 | 154925895 | rs538470 | C | T | -0.0053763 | 0.0217077 | 0.8044269 | 0.8043910 | 0.2471760 | 0.3634440 | 1460 |
23 | 154927581 | rs644138 | G | A | -0.0031828 | 0.0199353 | 0.8731750 | 0.8731521 | 0.3071170 | 0.4635760 | 1460 |
23 | 154929412 | rs557132 | C | T | -0.0052317 | 0.0211251 | 0.8044360 | 0.8044012 | 0.2511500 | 0.3568210 | 1460 |
23 | 154929637 | rs35185538 | CT | C | -0.0059923 | 0.0221833 | 0.7871020 | 0.7870625 | 0.2348470 | 0.3011920 | 1460 |
23 | 154929952 | rs4012982 | CAA | C | -0.0095592 | 0.0223668 | 0.6691631 | 0.6690994 | 0.2431870 | 0.3165560 | 1460 |
23 | 154930230 | rs781880 | A | G | -0.0064720 | 0.0211518 | 0.7596648 | 0.7596202 | 0.2508150 | 0.3618540 | 1460 |
23 | 154930487 | rs781879 | T | A | -0.0396515 | 0.0715965 | 0.5797890 | 0.5797027 | 0.0201638 | 0.1263580 | 1460 |
1 692794 rs530212009 CA C . PASS AF=0.118543 ES:SE:LP:AF:SS:ID -0.0404234:0.0309245:0.718133:0.118543:1460:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.123985 ES:SE:LP:AF:SS:ID -0.0208518:0.0298441:0.314385:0.123985:1460:rs12238997
1 707522 rs371890604 G C . PASS AF=0.105013 ES:SE:LP:AF:SS:ID -0.029228:0.0329951:0.424975:0.105013:1460:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0154768 ES:SE:LP:AF:SS:ID -0.0593015:0.0844093:0.316545:0.0154768:1460:rs144155419
1 730087 rs148120343 T C . PASS AF=0.0634515 ES:SE:LP:AF:SS:ID -0.0338285:0.0408409:0.389723:0.0634515:1460:rs148120343
1 731718 rs58276399 T C . PASS AF=0.130152 ES:SE:LP:AF:SS:ID -0.0165202:0.0284344:0.250777:0.130152:1460:rs58276399
1 732032 rs61770163 A C . PASS AF=0.129957 ES:SE:LP:AF:SS:ID -0.0232824:0.0299059:0.360126:0.129957:1460:rs61770163
1 734349 rs141242758 T C . PASS AF=0.129298 ES:SE:LP:AF:SS:ID -0.0192172:0.0283532:0.302752:0.129298:1460:rs141242758
1 749963 rs529266287 T TAA . PASS AF=0.860301 ES:SE:LP:AF:SS:ID 0.0232823:0.0275823:0.399297:0.860301:1460:rs529266287
1 751343 rs28544273 T A . PASS AF=0.133986 ES:SE:LP:AF:SS:ID -0.0241191:0.0273148:0.42322:0.133986:1460:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.150936 ES:SE:LP:AF:SS:ID -0.0192479:0.027236:0.318883:0.150936:1460:rs200141114
1 751756 rs28527770 T C . PASS AF=0.134012 ES:SE:LP:AF:SS:ID -0.0241804:0.0272972:0.424972:0.134012:1460:rs28527770
1 753405 rs3115860 C A . PASS AF=0.860564 ES:SE:LP:AF:SS:ID 0.0191677:0.0267385:0.324608:0.860564:1460:rs3115860
1 753425 rs3131970 T C . PASS AF=0.8639 ES:SE:LP:AF:SS:ID 0.0199649:0.0270515:0.336662:0.8639:1460:rs3131970
1 753541 rs2073813 G A . PASS AF=0.138899 ES:SE:LP:AF:SS:ID -0.017529:0.0267967:0.28978:0.138899:1460:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0380137 ES:SE:LP:AF:SS:ID -0.0343473:0.0491277:0.314638:0.0380137:1460:rs12184325
1 754182 rs3131969 A G . PASS AF=0.860423 ES:SE:LP:AF:SS:ID 0.0195473:0.0267441:0.332587:0.860423:1460:rs3131969
1 754192 rs3131968 A G . PASS AF=0.860426 ES:SE:LP:AF:SS:ID 0.0195528:0.0267454:0.332682:0.860426:1460:rs3131968
1 754334 rs3131967 T C . PASS AF=0.860412 ES:SE:LP:AF:SS:ID 0.0195972:0.0267431:0.333666:0.860412:1460:rs3131967
1 755890 rs3115858 A T . PASS AF=0.859905 ES:SE:LP:AF:SS:ID 0.0200563:0.0266458:0.345098:0.859905:1460:rs3115858
1 756434 rs61768170 G C . PASS AF=0.136398 ES:SE:LP:AF:SS:ID -0.0174757:0.0271416:0.284196:0.136398:1460:rs61768170
1 756604 rs3131962 A G . PASS AF=0.859589 ES:SE:LP:AF:SS:ID 0.0198899:0.0265991:0.342251:0.859589:1460:rs3131962
1 757640 rs3115853 G A . PASS AF=0.858598 ES:SE:LP:AF:SS:ID 0.0218139:0.0265798:0.385149:0.858598:1460:rs3115853
1 757734 rs4951929 C T . PASS AF=0.859628 ES:SE:LP:AF:SS:ID 0.0200559:0.0266098:0.345679:0.859628:1460:rs4951929
1 757936 rs4951862 C A . PASS AF=0.859629 ES:SE:LP:AF:SS:ID 0.0200575:0.0266107:0.345699:0.859629:1460:rs4951862
1 758144 rs3131956 A G . PASS AF=0.859659 ES:SE:LP:AF:SS:ID 0.020105:0.0266151:0.346659:0.859659:1460:rs3131956
1 758626 rs3131954 C T . PASS AF=0.859984 ES:SE:LP:AF:SS:ID 0.020608:0.0266644:0.356815:0.859984:1460:rs3131954
1 759293 rs10157329 T A . PASS AF=0.107595 ES:SE:LP:AF:SS:ID -0.0186656:0.031024:0.261614:0.107595:1460:rs10157329
1 759837 rs3115851 T A . PASS AF=0.864017 ES:SE:LP:AF:SS:ID 0.0236532:0.0270527:0.417845:0.864017:1460:rs3115851
1 761732 rs2286139 C T . PASS AF=0.853446 ES:SE:LP:AF:SS:ID 0.023343:0.02657:0.420452:0.853446:1460:rs2286139
1 761752 rs1057213 C T . PASS AF=0.858163 ES:SE:LP:AF:SS:ID 0.0221696:0.0266972:0.390998:0.858163:1460:rs1057213
1 762273 rs3115849 G A . PASS AF=0.855672 ES:SE:LP:AF:SS:ID 0.0166048:0.0268502:0.270516:0.855672:1460:rs3115849
1 762485 rs12095200 C A . PASS AF=0.10646 ES:SE:LP:AF:SS:ID -0.024242:0.0323513:0.343157:0.10646:1460:rs12095200
1 762589 rs3115848 G C . PASS AF=0.861189 ES:SE:LP:AF:SS:ID 0.0199305:0.0271904:0.333783:0.861189:1460:rs3115848
1 762592 rs3131950 C G . PASS AF=0.861189 ES:SE:LP:AF:SS:ID 0.0199305:0.0271904:0.333783:0.861189:1460:rs3131950
1 762601 rs3131949 T C . PASS AF=0.861183 ES:SE:LP:AF:SS:ID 0.0199341:0.0271908:0.333851:0.861183:1460:rs3131949
1 762632 rs3131948 T A . PASS AF=0.861444 ES:SE:LP:AF:SS:ID 0.0207667:0.0271843:0.351603:0.861444:1460:rs3131948
1 764191 rs7515915 T G . PASS AF=0.136011 ES:SE:LP:AF:SS:ID -0.0245053:0.027133:0.435815:0.136011:1460:rs7515915
1 766007 rs61768174 A C . PASS AF=0.116038 ES:SE:LP:AF:SS:ID -0.0118633:0.0293913:0.163332:0.116038:1460:rs61768174
1 766105 rs2519015 T A . PASS AF=0.844562 ES:SE:LP:AF:SS:ID 0.0188783:0.0265073:0.321972:0.844562:1460:rs2519015
1 768116 rs376645387 A AGTTTT . PASS AF=0.837436 ES:SE:LP:AF:SS:ID 0.05989:0.027621:1.51853:0.837436:1460:rs376645387
1 768253 rs2977608 A C . PASS AF=0.754727 ES:SE:LP:AF:SS:ID 0.0434418:0.0214769:1.36364:0.754727:1460:rs2977608
1 768448 rs12562034 G A . PASS AF=0.103767 ES:SE:LP:AF:SS:ID -0.0557594:0.0305016:1.16912:0.103767:1460:rs12562034
1 769138 rs59306077 CAT C . PASS AF=0.139592 ES:SE:LP:AF:SS:ID -0.0207208:0.0267367:0.35806:0.139592:1460:rs762168062
1 769223 rs60320384 C G . PASS AF=0.139239 ES:SE:LP:AF:SS:ID -0.0199281:0.0267277:0.341004:0.139239:1460:rs60320384
1 769963 rs7518545 G A . PASS AF=0.103078 ES:SE:LP:AF:SS:ID -0.0553301:0.0307674:1.14066:0.103078:1460:rs7518545
1 770886 rs371458725 G A . PASS AF=0.101967 ES:SE:LP:AF:SS:ID -0.0549212:0.0311031:1.10988:0.101967:1460:rs371458725
1 771410 rs2519006 C T . PASS AF=0.817956 ES:SE:LP:AF:SS:ID 0.035201:0.02601:0.75411:0.817956:1460:rs2519006
1 771823 rs2977605 T C . PASS AF=0.859637 ES:SE:LP:AF:SS:ID 0.0202592:0.0266517:0.34941:0.859637:1460:rs2977605
1 771967 rs59066358 G A . PASS AF=0.13922 ES:SE:LP:AF:SS:ID -0.0203918:0.0267157:0.351233:0.13922:1460:rs59066358