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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/ieu-a-import/processed/ieu-a-996/ieu-a-996.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-996/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 11:56:39 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-996/ieu-a-996.vcf.gz ...
Read summary statistics for 9965795 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, 1289604 SNPs remain.
After merging with regression SNP LD, 1289604 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0659 (0.0163)
Lambda GC: 1.0512
Mean Chi^2: 1.08
Intercept: 1.0284 (0.0066)
Ratio: 0.3555 (0.083)
Analysis finished at Tue Feb 4 11:58:04 2020
Total time elapsed: 1.0m:25.44s
{
"af_correlation": 0.946,
"inflation_factor": 1.0447,
"mean_EFFECT": 0.0057,
"n": 40835,
"n_snps": 9965795,
"n_clumped_hits": 12,
"n_p_sig": 721,
"n_mono": 0,
"n_ns": 0,
"n_mac": 3,
"is_snpid_unique": true,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 290038,
"n_est": 36370.2006,
"ratio_se_n": 0.9437,
"mean_diff": -0.0038,
"ratio_diff": 14.8661,
"sd_y_est1": 2.8298,
"sd_y_est2": 2.6706,
"r2_sum1": 0.088,
"r2_sum2": 0.011,
"r2_sum3": 0.0123,
"r2_sum4": 0.014,
"ldsc_nsnp_merge_refpanel_ld": 1289604,
"ldsc_nsnp_merge_regression_ld": 1289604,
"ldsc_observed_scale_h2_beta": 0.0659,
"ldsc_observed_scale_h2_se": 0.0163,
"ldsc_intercept_beta": 1.0284,
"ldsc_intercept_se": 0.0066,
"ldsc_lambda_gc": 1.0512,
"ldsc_mean_chisq": 1.08,
"ldsc_ratio": 0.355
}
name | value |
---|---|
af_correlation | FALSE |
inflation_factor | FALSE |
n | FALSE |
is_snpid_non_unique | FALSE |
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 | 1.0000000 | 3 | 59 | 0 | 9965793 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.680186e+00 | 5.777235e+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 | 7.866053e+07 | 5.642987e+07 | 828.0000000 | 3.236759e+07 | 6.916933e+07 | 1.144637e+08 | 2.492297e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.689100e-03 | 4.453580e-01 | -261.1540000 | -2.217400e-02 | 2.462000e-03 | 3.015670e-02 | 3.052700e+01 | ▁▁▁▁▇ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.575830e-02 | 6.248778e-01 | 0.0164146 | 2.041670e-02 | 3.455590e-02 | 8.772550e-02 | 3.368330e+02 | ▇▁▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.928946e-01 | 2.910629e-01 | 0.0000000 | 2.391509e-01 | 4.905745e-01 | 7.453684e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.928945e-01 | 2.910637e-01 | 0.0000000 | 2.391717e-01 | 4.905587e-01 | 7.453610e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.094925e-01 | 2.425788e-01 | 0.0003190 | 2.124400e-02 | 9.259300e-02 | 3.358830e-01 | 9.952650e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 290038 | 0.9708967 | NA | NA | NA | NA | NA | 2.195667e-01 | 2.526678e-01 | 0.0000000 | 1.837060e-02 | 1.140180e-01 | 3.428510e-01 | 1.000000e+00 | ▇▂▁▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.020600e+04 | 1.335767e+04 | 304.0000000 | 2.787800e+04 | 3.486700e+04 | 4.053000e+04 | 4.083500e+04 | ▂▁▁▁▇ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 55164 | rs3091274 | C | A | 0.0639668 | 0.349420 | 0.8547311 | 0.8547465 | 0.957143 | 0.9233230 | 856 |
1 | 55299 | rs10399749 | C | T | -0.0022154 | 0.190480 | 0.9907160 | 0.9907201 | 0.182289 | NA | 856 |
1 | 55326 | rs3107975 | T | C | 0.3412300 | 0.316440 | 0.2808640 | 0.2808819 | 0.035449 | 0.0459265 | 856 |
1 | 55394 | rs2949420 | T | A | -0.4503410 | 0.528760 | 0.3943846 | 0.3943847 | 0.014356 | NA | 856 |
1 | 55850 | rs191890754 | C | G | 0.0739417 | 0.294474 | 0.8017331 | 0.8017387 | 0.012673 | NA | 3470 |
1 | 66176 | rs28552463 | T | A | -1.1014000 | 0.634620 | 0.0826514 | 0.0826475 | 0.011975 | NA | 856 |
1 | 66219 | rs181028663 | A | T | 1.1094000 | 0.749560 | 0.1388430 | 0.1388550 | 0.010238 | 0.0203674 | 856 |
1 | 77961 | rs78385339 | G | A | 0.5305700 | 0.290820 | 0.0681020 | 0.0680927 | 0.067717 | NA | 856 |
1 | 84002 | rs28850140 | G | A | -0.0452317 | 0.104808 | 0.6660733 | 0.6660560 | 0.173270 | NA | 3470 |
1 | 85063 | rs187802690 | T | C | -0.3224700 | 0.427930 | 0.4511241 | 0.4511148 | 0.030280 | NA | 856 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51224635 | rs143053851 | G | A | 0.1886580 | 0.1567970 | 0.2288790 | 0.2288993 | 0.043084 | NA | 4945 |
22 | 51224718 | rs189454695 | T | G | 0.0444723 | 0.0765311 | 0.5611927 | 0.5611724 | 0.135809 | NA | 7883 |
22 | 51227891 | rs6010091 | G | A | -0.0040492 | 0.0354251 | 0.9089709 | 0.9089977 | 0.372510 | 0.4039540 | 15798 |
22 | 51229805 | rs9616985 | T | C | -0.0257292 | 0.0621591 | 0.6789488 | 0.6789291 | 0.079470 | 0.0730831 | 15798 |
22 | 51229855 | rs144549712 | G | A | -0.0438631 | 0.0815574 | 0.5907232 | 0.5907022 | 0.093923 | 0.1160140 | 9087 |
22 | 51234799 | rs191117135 | G | A | 0.1813100 | 0.6048700 | 0.7643706 | 0.7643676 | 0.010701 | 0.0059904 | 1307 |
22 | 51237063 | rs3896457 | T | C | 0.0115154 | 0.0450824 | 0.7983840 | 0.7983910 | 0.249514 | 0.2050720 | 12763 |
22 | 51238249 | rs149733995 | A | C | -0.0717990 | 0.0819438 | 0.3809211 | 0.3809224 | 0.072168 | NA | 10394 |
23 | 50040891 | rs192267219 | C | T | -0.1058840 | 0.1732570 | 0.5411292 | 0.5411080 | 0.977139 | 0.0222517 | 6754 |
23 | 100784211 | rs188350543 | C | A | 0.0084324 | 0.0283846 | 0.7664115 | 0.7664067 | 0.739636 | 0.6498010 | 20007 |
1 55164 rs3091274 C A . PASS AF=0.957143 ES:SE:LP:AF:SS:ID 0.0639668:0.34942:0.0681705:0.957143:856:rs3091274
1 55299 rs10399749 C T . PASS AF=0.182289 ES:SE:LP:AF:SS:ID -0.00221545:0.19048:0.00405082:0.182289:856:rs10399749
1 55326 rs3107975 T C . PASS AF=0.035449 ES:SE:LP:AF:SS:ID 0.34123:0.31644:0.551504:0.035449:856:rs3107975
1 55394 rs2949420 T A . PASS AF=0.014356 ES:SE:LP:AF:SS:ID -0.450341:0.52876:0.40408:0.014356:856:rs2949420
1 55850 rs191890754 C G . PASS AF=0.012673 ES:SE:LP:AF:SS:ID 0.0739417:0.294474:0.0959702:0.012673:3470:rs191890754
1 66176 rs28552463 T A . PASS AF=0.011975 ES:SE:LP:AF:SS:ID -1.1014:0.63462:1.08275:0.011975:856:rs28552463
1 66219 rs181028663 A T . PASS AF=0.010238 ES:SE:LP:AF:SS:ID 1.1094:0.74956:0.857476:0.010238:856:rs181028663
1 77961 rs78385339 G A . PASS AF=0.067717 ES:SE:LP:AF:SS:ID 0.53057:0.29082:1.16684:0.067717:856:rs78385339
1 84002 rs28850140 G A . PASS AF=0.17327 ES:SE:LP:AF:SS:ID -0.0452317:0.104808:0.176478:0.17327:3470:rs28850140
1 85063 rs187802690 T C . PASS AF=0.03028 ES:SE:LP:AF:SS:ID -0.32247:0.42793:0.345704:0.03028:856:rs187802690
1 87021 rs188486692 T C . PASS AF=0.027216 ES:SE:LP:AF:SS:ID -0.0527343:0.223121:0.0898256:0.027216:3470:rs188486692
1 99687 rs139153227 C T . PASS AF=0.056542 ES:SE:LP:AF:SS:ID -0.0736552:0.180382:0.165548:0.056542:3470:rs139153227
1 115746 rs147538909 C T . PASS AF=0.040325 ES:SE:LP:AF:SS:ID -0.948019:0.383749:1.86915:0.040325:856:rs147538909
1 120705 rs4117992 T C . PASS AF=0.957408 ES:SE:LP:AF:SS:ID -0.10109:0.34124:0.115177:0.957408:856:rs4117992
1 126113 rs79114531 C A . PASS AF=0.986805 ES:SE:LP:AF:SS:ID -0.20747:0.53256:0.156848:0.986805:856:rs79114531
1 135203 rs147502335 G A . PASS AF=0.034675 ES:SE:LP:AF:SS:ID -0.311631:0.40406:0.355987:0.034675:856:rs147502335
1 168373 rs183198872 C T . PASS AF=0.044838 ES:SE:LP:AF:SS:ID -0.0400327:0.165975:0.0918384:0.044838:4326:rs183198872
1 168964 rs187450123 A G . PASS AF=0.02437 ES:SE:LP:AF:SS:ID -0.264559:0.49346:0.227759:0.02437:856:rs187450123
1 230433 rs190807317 T C . PASS AF=0.010111 ES:SE:LP:AF:SS:ID -1.5508:0.737781:1.44886:0.010111:856:rs190807317
1 249276 rs115018998 T C . PASS AF=0.010143 ES:SE:LP:AF:SS:ID 0.0425047:0.49841:0.0305762:0.010143:2511:rs115018998
1 526057 rs141459107 T C . PASS AF=0.012903 ES:SE:LP:AF:SS:ID -0.398191:0.59215:0.299889:0.012903:1307:rs141459107
1 526970 rs60791385 T C . PASS AF=0.012306 ES:SE:LP:AF:SS:ID 1.389:0.68542:1.36925:0.012306:856:rs60791385
1 527186 rs111227194 A G . PASS AF=0.017086 ES:SE:LP:AF:SS:ID -1.0201:0.797502:0.697161:0.017086:1631:rs111227194
1 527207 rs112901516 A G . PASS AF=0.015506 ES:SE:LP:AF:SS:ID -1.5205:0.985749:0.910275:0.015506:1631:rs112901516
1 533198 rs78497331 C T . PASS AF=0.041151 ES:SE:LP:AF:SS:ID -0.305001:0.38631:0.36672:0.041151:856:rs78497331
1 540975 rs80246094 G A . PASS AF=0.087192 ES:SE:LP:AF:SS:ID -0.3509:0.26254:0.741487:0.087192:856:rs80246094
1 600478 rs114979547 G A . PASS AF=0.089717 ES:SE:LP:AF:SS:ID -0.14461:0.25903:0.239066:0.089717:856:rs114979547
1 601141 rs140845213 C T . PASS AF=0.098554 ES:SE:LP:AF:SS:ID 0.0239499:0.25132:0.0343008:0.098554:856:rs140845213
1 603331 rs186375515 T C . PASS AF=0.012097 ES:SE:LP:AF:SS:ID -0.6185:0.63673:0.479709:0.012097:612:rs186375515
1 645605 rs185127847 T A . PASS AF=0.04293 ES:SE:LP:AF:SS:ID 0.384977:0.193064:1.33568:0.04293:3367:rs185127847
1 662622 rs61769339 G A . PASS AF=0.113796 ES:SE:LP:AF:SS:ID -0.0156072:0.0613263:0.0973934:0.113796:11006:rs61769339
1 676127 rs150820983 C T . PASS AF=0.022678 ES:SE:LP:AF:SS:ID -0.221676:0.309322:0.324586:0.022678:3130:rs150820983
1 693625 rs190214723 T C . PASS AF=0.040483 ES:SE:LP:AF:SS:ID -0.0839241:0.192287:0.178795:0.040483:3986:rs190214723
1 701835 rs189800799 T C . PASS AF=0.025763 ES:SE:LP:AF:SS:ID 0.0267917:0.220697:0.0441401:0.025763:5713:rs189800799
1 704637 rs142559957 G A . PASS AF=0.074505 ES:SE:LP:AF:SS:ID 0.0560353:0.1253:0.183926:0.074505:3470:rs142559957
1 705882 rs72631875 G A . PASS AF=0.069887 ES:SE:LP:AF:SS:ID 0.0605512:0.161448:0.150191:0.069887:3718:rs72631875
1 712871 rs4311830 T C . PASS AF=0.019615 ES:SE:LP:AF:SS:ID -0.366245:0.418651:0.418313:0.019615:1475:rs4311830
1 712930 rs28457007 T C . PASS AF=0.02637 ES:SE:LP:AF:SS:ID -0.0505144:0.21307:0.090128:0.02637:5713:rs28457007
1 714019 rs114983708 A G . PASS AF=0.043374 ES:SE:LP:AF:SS:ID 0.0443144:0.2953:0.0551745:0.043374:856:rs114983708
1 714310 rs141232927 C G . PASS AF=0.018196 ES:SE:LP:AF:SS:ID -0.155718:0.286041:0.231959:0.018196:5025:rs141232927
1 714427 rs12028261 G A . PASS AF=0.981626 ES:SE:LP:AF:SS:ID 0.40101:0.54061:0.338912:0.981626:856:rs12028261
1 714596 rs149887893 T C . PASS AF=0.027038 ES:SE:LP:AF:SS:ID 0.0747731:0.248051:0.117429:0.027038:4406:rs149887893
1 715265 rs12184267 C T . PASS AF=0.039114 ES:SE:LP:AF:SS:ID -0.0342613:0.138819:0.0941734:0.039114:6332:rs12184267
1 715367 rs12184277 A G . PASS AF=0.035262 ES:SE:LP:AF:SS:ID 0.0450748:0.159398:0.109387:0.035262:5713:rs12184277
1 716041 rs149301622 G A . PASS AF=0.034258 ES:SE:LP:AF:SS:ID 0.0376271:0.162721:0.087712:0.034258:5713:rs149301622
1 717485 rs12184279 C A . PASS AF=0.033217 ES:SE:LP:AF:SS:ID 0.0347581:0.165261:0.0791434:0.033217:5713:rs12184279
1 718505 rs181440659 G A . PASS AF=0.013199 ES:SE:LP:AF:SS:ID -0.126922:0.321661:0.159162:0.013199:3986:rs181440659
1 719914 rs187772768 C G . PASS AF=0.039751 ES:SE:LP:AF:SS:ID 0.0239311:0.139263:0.0637145:0.039751:5713:rs187772768
1 720381 rs116801199 G T . PASS AF=0.040785 ES:SE:LP:AF:SS:ID 0.00487888:0.135256:0.0126855:0.040785:5713:rs116801199
1 721290 rs12565286 G C . PASS AF=0.042801 ES:SE:LP:AF:SS:ID 0.0069944:0.127792:0.0193909:0.042801:5713:rs12565286