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}
*********************************************************************
* 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-22617_2132/ukb-d-22617_2132.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-22617_2132/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 14:48:08 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22617_2132/ukb-d-22617_2132.vcf.gz ...
Read summary statistics for 11426982 SNPs.
Dropped 9678 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, 1282545 SNPs remain.
After merging with regression SNP LD, 1282545 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0153 (0.005)
Lambda GC: 1.037
Mean Chi^2: 1.0363
Intercept: 1.0088 (0.0056)
Ratio: 0.2413 (0.1553)
Analysis finished at Mon Nov 25 14:50:01 2019
Total time elapsed: 1.0m:52.95s
{
"af_correlation": 0.9474,
"inflation_factor": 1.0279,
"mean_EFFECT": -9.7175e-06,
"n": 91149,
"n_snps": 11426982,
"n_clumped_hits": 0,
"n_p_sig": 0,
"n_mono": 0,
"n_ns": 1158622,
"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": 239567,
"n_est": 91317.9694,
"ratio_se_n": 1.0009,
"mean_diff": -0,
"ratio_diff": 23.166,
"sd_y_est1": 0.1919,
"sd_y_est2": 0.1921,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1282545,
"ldsc_nsnp_merge_regression_ld": 1282545,
"ldsc_observed_scale_h2_beta": 0.0153,
"ldsc_observed_scale_h2_se": 0.005,
"ldsc_intercept_beta": 1.0088,
"ldsc_intercept_se": 0.0056,
"ldsc_lambda_gc": 1.037,
"ldsc_mean_chisq": 1.0363,
"ldsc_ratio": 0.2424
}
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 | FALSE |
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 |
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 | 1.000000 | 3 | 94 | 0 | 11417903 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.000000 | 1 | 100 | 0 | 52096 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.000000 | 1 | 342 | 0 | 31667 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.000000 | NA | NA | NA | NA | NA | 9.074065e+00 | 6.183268e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
numeric | POS | 0 | 1.000000 | NA | NA | NA | NA | NA | 7.884232e+07 | 5.599910e+07 | 3.02000e+02 | 3.263427e+07 | 6.984525e+07 | 1.147288e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.000000 | NA | NA | NA | NA | NA | -9.700000e-06 | 3.076100e-03 | -3.21116e-02 | -1.171200e-03 | -1.750000e-05 | 1.129800e-03 | 3.915130e-02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.000000 | NA | NA | NA | NA | NA | 2.423800e-03 | 1.863400e-03 | 7.42600e-04 | 1.019800e-03 | 1.542100e-03 | 3.287200e-03 | 1.089020e-02 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.000000 | NA | NA | NA | NA | NA | 4.955888e-01 | 2.899511e-01 | 1.00000e-07 | 2.434423e-01 | 4.940751e-01 | 7.465244e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.000000 | NA | NA | NA | NA | NA | 4.955870e-01 | 2.899521e-01 | 1.00000e-07 | 2.434391e-01 | 4.940734e-01 | 7.465225e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.000000 | NA | NA | NA | NA | NA | 2.248568e-01 | 2.608815e-01 | 3.55220e-03 | 1.998230e-02 | 1.069060e-01 | 3.593320e-01 | 9.964480e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 239567 | 0.979035 | NA | NA | NA | NA | NA | 2.254635e-01 | 2.521128e-01 | 0.00000e+00 | 1.737220e-02 | 1.252980e-01 | 3.590260e-01 | 1.000000e+00 | ▇▂▂▁▁ |
numeric | N | 0 | 1.000000 | NA | NA | NA | NA | NA | 9.114900e+04 | 0.000000e+00 | 9.11490e+04 | 9.114900e+04 | 9.114900e+04 | 9.114900e+04 | 9.114900e+04 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | -0.0017589 | 0.0015708 | 0.2628331 | 0.2628321 | 0.1114870 | 0.1894970 | 91149 |
1 | 693731 | rs12238997 | A | G | -0.0019330 | 0.0014877 | 0.1938438 | 0.1938407 | 0.1164590 | 0.1417730 | 91149 |
1 | 707522 | rs371890604 | G | C | -0.0017068 | 0.0016718 | 0.3073031 | 0.3072994 | 0.0978765 | 0.1293930 | 91149 |
1 | 717587 | rs144155419 | G | A | -0.0021772 | 0.0039853 | 0.5848561 | 0.5848556 | 0.0157837 | 0.0045926 | 91149 |
1 | 730087 | rs148120343 | T | C | -0.0011030 | 0.0020621 | 0.5927097 | 0.5927112 | 0.0569973 | 0.0127796 | 91149 |
1 | 731718 | rs142557973 | T | C | -0.0016254 | 0.0014117 | 0.2495991 | 0.2495961 | 0.1223590 | 0.1543530 | 91149 |
1 | 732032 | rs61770163 | A | C | -0.0015323 | 0.0015052 | 0.3086832 | 0.3086794 | 0.1220470 | 0.1555510 | 91149 |
1 | 734349 | rs141242758 | T | C | -0.0015805 | 0.0014128 | 0.2632849 | 0.2632804 | 0.1215880 | 0.1525560 | 91149 |
1 | 740284 | rs61770167 | C | T | -0.0057426 | 0.0064872 | 0.3760356 | 0.3760341 | 0.0057444 | 0.0023962 | 91149 |
1 | 749963 | rs529266287 | T | TAA | 0.0010867 | 0.0013897 | 0.4342382 | 0.4342343 | 0.8689170 | 0.7641770 | 91149 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0021923 | 0.0016526 | 0.1846550 | 0.1846522 | 0.0552869 | 0.0309934 | 91149 |
23 | 154923374 | rs111332691 | T | A | 0.0018599 | 0.0017985 | 0.3010759 | 0.3010733 | 0.0448387 | 0.0116556 | 91149 |
23 | 154925045 | rs509981 | C | T | 0.0004338 | 0.0008667 | 0.6167086 | 0.6167063 | 0.2444670 | 0.3634440 | 91149 |
23 | 154925895 | rs538470 | C | T | 0.0008466 | 0.0008861 | 0.3393782 | 0.3393754 | 0.2409490 | 0.3634440 | 91149 |
23 | 154927581 | rs644138 | G | A | 0.0008803 | 0.0008152 | 0.2801999 | 0.2801975 | 0.3001640 | 0.4635760 | 91149 |
23 | 154929412 | rs557132 | C | T | 0.0004419 | 0.0008670 | 0.6102896 | 0.6102874 | 0.2443160 | 0.3568210 | 91149 |
23 | 154929637 | rs35185538 | CT | C | -0.0001308 | 0.0009053 | 0.8850889 | 0.8850890 | 0.2286640 | 0.3011920 | 91149 |
23 | 154929952 | rs4012982 | CAA | C | 0.0003450 | 0.0009125 | 0.7053489 | 0.7053478 | 0.2382530 | 0.3165560 | 91149 |
23 | 154930230 | rs781880 | A | G | 0.0004110 | 0.0008667 | 0.6353119 | 0.6353105 | 0.2447660 | 0.3618540 | 91149 |
23 | 154930487 | rs781879 | T | A | 0.0048099 | 0.0029394 | 0.1017640 | 0.1017603 | 0.0196632 | 0.1263580 | 91149 |
1 692794 rs530212009 CA C . PASS AF=0.111487 ES:SE:LP:AF:SS:ID -0.00175886:0.0015708:0.58032:0.111487:91149:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116459 ES:SE:LP:AF:SS:ID -0.00193297:0.0014877:0.712548:0.116459:91149:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0978765 ES:SE:LP:AF:SS:ID -0.00170679:0.00167184:0.512433:0.0978765:91149:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0157837 ES:SE:LP:AF:SS:ID -0.00217721:0.00398533:0.232951:0.0157837:91149:rs144155419
1 730087 rs148120343 T C . PASS AF=0.0569973 ES:SE:LP:AF:SS:ID -0.00110303:0.00206208:0.227158:0.0569973:91149:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122359 ES:SE:LP:AF:SS:ID -0.00162538:0.00141174:0.602757:0.122359:91149:rs58276399
1 732032 rs61770163 A C . PASS AF=0.122047 ES:SE:LP:AF:SS:ID -0.00153234:0.00150525:0.510487:0.122047:91149:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121588 ES:SE:LP:AF:SS:ID -0.00158047:0.00141281:0.579574:0.121588:91149:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00574438 ES:SE:LP:AF:SS:ID -0.00574261:0.00648716:0.424771:0.00574438:91149:rs61770167
1 749963 rs529266287 T TAA . PASS AF=0.868917 ES:SE:LP:AF:SS:ID 0.00108673:0.00138974:0.362272:0.868917:91149:rs529266287
1 751343 rs28544273 T A . PASS AF=0.123699 ES:SE:LP:AF:SS:ID -0.00112961:0.00137782:0.384784:0.123699:91149:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143202 ES:SE:LP:AF:SS:ID -0.0024548:0.00136404:1.14316:0.143202:91149:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123834 ES:SE:LP:AF:SS:ID -0.00116195:0.00137583:0.399717:0.123834:91149:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869892 ES:SE:LP:AF:SS:ID 0.00168559:0.00134061:0.680613:0.869892:91149:rs3115860
1 753425 rs3131970 T C . PASS AF=0.874553 ES:SE:LP:AF:SS:ID 0.00155125:0.00136235:0.593719:0.874553:91149:rs3131970
1 753541 rs2073813 G A . PASS AF=0.129529 ES:SE:LP:AF:SS:ID -0.00165701:0.00134481:0.661751:0.129529:91149:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0358205 ES:SE:LP:AF:SS:ID 0.000719703:0.00245686:0.113751:0.0358205:91149:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869539 ES:SE:LP:AF:SS:ID 0.00171294:0.00133949:0.696873:0.869539:91149:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869616 ES:SE:LP:AF:SS:ID 0.00173839:0.00134007:0.710964:0.869616:91149:rs3131968
1 754334 rs3131967 T C . PASS AF=0.869535 ES:SE:LP:AF:SS:ID 0.00171643:0.00133943:0.698894:0.869535:91149:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00531588 ES:SE:LP:AF:SS:ID 0.00272624:0.00669117:0.165143:0.00531588:91149:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00528125 ES:SE:LP:AF:SS:ID 0.00278626:0.00670779:0.168856:0.00528125:91149:rs142682604
1 755435 rs184270342 T G . PASS AF=0.0056599 ES:SE:LP:AF:SS:ID -0.00651025:0.0065941:0.490118:0.0056599:91149:rs184270342
1 755890 rs3115858 A T . PASS AF=0.86952 ES:SE:LP:AF:SS:ID 0.00160968:0.00133667:0.641118:0.86952:91149:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126911 ES:SE:LP:AF:SS:ID -0.00150839:0.00136451:0.570298:0.126911:91149:rs61768170
1 756604 rs3131962 A G . PASS AF=0.86905 ES:SE:LP:AF:SS:ID 0.00165347:0.00133321:0.667764:0.86905:91149:rs3131962
1 757640 rs3115853 G A . PASS AF=0.868436 ES:SE:LP:AF:SS:ID 0.00166887:0.00133237:0.677018:0.868436:91149:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869199 ES:SE:LP:AF:SS:ID 0.00161234:0.00133442:0.644076:0.869199:91149:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869205 ES:SE:LP:AF:SS:ID 0.00161059:0.00133451:0.643053:0.869205:91149:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869207 ES:SE:LP:AF:SS:ID 0.00161081:0.00133452:0.643166:0.869207:91149:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869687 ES:SE:LP:AF:SS:ID 0.00156839:0.00133809:0.617704:0.869687:91149:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0991787 ES:SE:LP:AF:SS:ID -0.00134805:0.00155722:0.412664:0.0991787:91149:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00649624 ES:SE:LP:AF:SS:ID -0.00518532:0.00600761:0.41109:0.00649624:91149:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.873682 ES:SE:LP:AF:SS:ID 0.00140342:0.00135791:0.520904:0.873682:91149:rs3115851
1 761732 rs2286139 C T . PASS AF=0.863058 ES:SE:LP:AF:SS:ID 0.00177701:0.001332:0.739509:0.863058:91149:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868472 ES:SE:LP:AF:SS:ID 0.00158424:0.00134521:0.621737:0.868472:91149:rs1057213
1 762273 rs3115849 G A . PASS AF=0.865369 ES:SE:LP:AF:SS:ID 0.00170266:0.00134547:0.686759:0.865369:91149:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0995228 ES:SE:LP:AF:SS:ID -0.00110012:0.00161028:0.30584:0.0995228:91149:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870657 ES:SE:LP:AF:SS:ID 0.00139485:0.0013608:0.515196:0.870657:91149:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870657 ES:SE:LP:AF:SS:ID 0.00139484:0.0013608:0.515194:0.870657:91149:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870654 ES:SE:LP:AF:SS:ID 0.00139492:0.0013608:0.515231:0.870654:91149:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871019 ES:SE:LP:AF:SS:ID 0.00140519:0.00136143:0.519982:0.871019:91149:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126515 ES:SE:LP:AF:SS:ID -0.00137278:0.00136295:0.503297:0.126515:91149:rs7515915
1 766007 rs61768174 A C . PASS AF=0.106037 ES:SE:LP:AF:SS:ID -0.00164003:0.00148153:0.571371:0.106037:91149:rs61768174
1 766105 rs2519015 T A . PASS AF=0.85438 ES:SE:LP:AF:SS:ID 0.00170763:0.00133149:0.699687:0.85438:91149:rs2519015
1 768116 rs376645387 A AGTTTT . PASS AF=0.839153 ES:SE:LP:AF:SS:ID 0.00124712:0.00131557:0.464517:0.839153:91149:rs376645387
1 768253 rs2977608 A C . PASS AF=0.763195 ES:SE:LP:AF:SS:ID 0.0015076:0.00105778:0.812226:0.763195:91149:rs2977608
1 768448 rs12562034 G A . PASS AF=0.105092 ES:SE:LP:AF:SS:ID -0.000739106:0.00145765:0.213164:0.105092:91149:rs12562034
1 768819 rs12562811 C T . PASS AF=0.00772317 ES:SE:LP:AF:SS:ID -0.000850785:0.0054011:0.0580738:0.00772317:91149:rs12562811
1 769138 rs59306077 CAT C . PASS AF=0.129904 ES:SE:LP:AF:SS:ID -0.00142895:0.00134391:0.541122:0.129904:91149:rs762168062