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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-1043/ieu-a-1043.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-1043/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Wed Feb 5 08:58:59 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1043/ieu-a-1043.vcf.gz ...
Read summary statistics for 6507245 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, 1170948 SNPs remain.
After merging with regression SNP LD, 1170948 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0178 (0.0313)
Lambda GC: 0.9943
Mean Chi^2: 0.9964
Intercept: 1.0011 (0.0058)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Wed Feb 5 09:00:08 2020
Total time elapsed: 1.0m:8.2s
{
"af_correlation": 0.9427,
"inflation_factor": 0.9967,
"mean_EFFECT": -0.0713,
"n": 13160,
"n_snps": 6507245,
"n_clumped_hits": 1,
"n_p_sig": 3,
"n_mono": 0,
"n_ns": 0,
"n_mac": 0,
"is_snpid_unique": true,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 0,
"n_miss_AF_reference": 89193,
"n_est": 12832.1503,
"ratio_se_n": 0.9875,
"mean_diff": 0.071,
"ratio_diff": 62949.7349,
"sd_y_est1": 193.806,
"sd_y_est2": 191.3767,
"r2_sum1": 245.3973,
"r2_sum2": 0.0065,
"r2_sum3": 0.0067,
"r2_sum4": 0.0038,
"ldsc_nsnp_merge_refpanel_ld": 1170948,
"ldsc_nsnp_merge_regression_ld": 1170948,
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": 1.0011,
"ldsc_intercept_se": 0.0058,
"ldsc_lambda_gc": 0.9943,
"ldsc_mean_chisq": 0.9964,
"ldsc_ratio": -0.3056
}
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 | TRUE |
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 | 58 | 0 | 6507245 | 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 | 8.614409e+00 | 5.742120e+00 | 1.000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.937395e+07 | 5.625300e+07 | 828.000000 | 3.318054e+07 | 7.028398e+07 | 1.150832e+08 | 2.492178e+08 | ▇▇▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -7.134970e-02 | 6.673993e+00 | -130.708000 | -2.643900e+00 | -3.990000e-02 | 2.550600e+00 | 1.127640e+02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.232039e+00 | 4.107934e+00 | 2.254000 | 2.594300e+00 | 3.472100e+00 | 6.065300e+00 | 3.464120e+01 | ▇▁▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.999929e-01 | 2.884708e-01 | 0.000000 | 2.497998e-01 | 5.007005e-01 | 7.494005e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.999929e-01 | 2.884708e-01 | 0.000000 | 2.497963e-01 | 5.006673e-01 | 7.493985e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.603523e-01 | 2.612737e-01 | 0.002639 | 4.485000e-02 | 1.596000e-01 | 4.129000e-01 | 9.986810e-01 | ▇▂▂▁▁ |
numeric | AF_reference | 89193 | 0.9862933 | NA | NA | NA | NA | NA | 2.623903e-01 | 2.530068e-01 | 0.000000 | 5.511180e-02 | 1.747200e-01 | 4.103430e-01 | 1.000000e+00 | ▇▃▂▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.228399e+04 | 1.708630e+03 | 5589.000000 | 1.256300e+04 | 1.316000e+04 | 1.316000e+04 | 1.316000e+04 | ▁▁▁▁▇ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 752566 | rs3094315 | G | A | -3.5251 | 3.2260 | 0.2744998 | 0.2745188 | 0.8364 | 0.718251 | 11685 |
1 | 752721 | rs3131972 | A | G | -3.6723 | 3.3011 | 0.2658998 | 0.2659458 | 0.8325 | 0.653355 | 11685 |
1 | 752894 | rs3131971 | T | C | -4.2266 | 3.4933 | 0.2263002 | 0.2263111 | 0.7955 | 0.753195 | 11685 |
1 | 753541 | rs2073813 | G | A | 2.7817 | 3.8608 | 0.4711997 | 0.4712182 | 0.1332 | 0.301917 | 11685 |
1 | 754182 | rs3131969 | A | G | -2.8768 | 3.8952 | 0.4602004 | 0.4601803 | 0.8668 | 0.678514 | 11685 |
1 | 754192 | rs3131968 | A | G | -2.8431 | 3.9194 | 0.4681996 | 0.4682118 | 0.8654 | 0.678514 | 11685 |
1 | 754334 | rs3131967 | T | C | -0.2901 | 4.6297 | 0.9500000 | 0.9500367 | 0.8377 | 0.684305 | 7246 |
1 | 754503 | rs3115859 | G | A | -3.6026 | 3.5476 | 0.3099003 | 0.3098659 | 0.8311 | 0.663938 | 11685 |
1 | 754964 | rs3131966 | C | T | -3.5320 | 3.8213 | 0.3552998 | 0.3553339 | 0.8074 | 0.663339 | 11135 |
1 | 755775 | rs3131965 | A | G | -2.5082 | 4.2451 | 0.5546002 | 0.5546237 | 0.7942 | NA | 8159 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51164115 | rs5770996 | C | T | 0.0974 | 2.5442 | 0.9695000 | 0.9694619 | 0.40770 | 0.5147760 | 11774 |
22 | 51164287 | rs6009957 | T | C | 3.1542 | 2.7670 | 0.2542998 | 0.2543134 | 0.28630 | 0.4155350 | 11774 |
22 | 51165390 | rs76268556 | C | T | 0.2409 | 13.3052 | 0.9856000 | 0.9855545 | 0.02507 | 0.0515176 | 6612 |
22 | 51165664 | rs8137951 | G | A | 3.2874 | 2.7567 | 0.2330999 | 0.2330602 | 0.28100 | 0.4063500 | 11774 |
22 | 51169045 | rs8140772 | C | T | 7.1788 | 11.8861 | 0.5458999 | 0.5458663 | 0.02770 | 0.0632987 | 7154 |
22 | 51171667 | rs41281537 | G | A | 6.7459 | 11.5388 | 0.5587995 | 0.5587982 | 0.02770 | 0.0577077 | 7426 |
22 | 51171693 | rs756638 | G | A | 3.8269 | 3.0445 | 0.2088002 | 0.2087580 | 0.25990 | 0.3049120 | 11028 |
22 | 51172460 | rs5770824 | T | C | 6.7378 | 11.5673 | 0.5601999 | 0.5602388 | 0.02770 | 0.0684904 | 7426 |
22 | 51175626 | rs3810648 | A | G | 9.1582 | 5.3579 | 0.0873997 | 0.0873974 | 0.05277 | 0.1084270 | 12034 |
22 | 51178090 | rs2285395 | G | A | 8.9808 | 5.5906 | 0.1081999 | 0.1081837 | 0.05145 | 0.0666933 | 12034 |
1 752566 rs3094315 G A . PASS AF=0.8364 ES:SE:LP:AF:SS:ID -3.5251:3.226:0.561458:0.8364:11685:rs3094315
1 752721 rs3131972 A G . PASS AF=0.8325 ES:SE:LP:AF:SS:ID -3.6723:3.3011:0.575282:0.8325:11685:rs3131972
1 752894 rs3131971 T C . PASS AF=0.7955 ES:SE:LP:AF:SS:ID -4.2266:3.4933:0.645315:0.7955:11685:rs3131971
1 753541 rs2073813 G A . PASS AF=0.1332 ES:SE:LP:AF:SS:ID 2.7817:3.8608:0.326795:0.1332:11685:rs2073813
1 754182 rs3131969 A G . PASS AF=0.8668 ES:SE:LP:AF:SS:ID -2.8768:3.8952:0.337053:0.8668:11685:rs3131969
1 754192 rs3131968 A G . PASS AF=0.8654 ES:SE:LP:AF:SS:ID -2.8431:3.9194:0.329569:0.8654:11685:rs3131968
1 754334 rs3131967 T C . PASS AF=0.8377 ES:SE:LP:AF:SS:ID -0.2901:4.6297:0.0222764:0.8377:7246:rs3131967
1 754503 rs3115859 G A . PASS AF=0.8311 ES:SE:LP:AF:SS:ID -3.6026:3.5476:0.508778:0.8311:11685:rs3115859
1 754964 rs3131966 C T . PASS AF=0.8074 ES:SE:LP:AF:SS:ID -3.532:3.8213:0.449405:0.8074:11135:rs3131966
1 755775 rs3131965 A G . PASS AF=0.7942 ES:SE:LP:AF:SS:ID -2.5082:4.2451:0.25602:0.7942:8159:rs3131965
1 756604 rs3131962 A G . PASS AF=0.8351 ES:SE:LP:AF:SS:ID -1.9739:4.5467:0.177701:0.8351:7532:rs3131962
1 757640 rs3115853 G A . PASS AF=0.8668 ES:SE:LP:AF:SS:ID -0.1127:4.56:0.008641:0.8668:7727:rs3115853
1 757734 rs4951929 C T . PASS AF=0.8681 ES:SE:LP:AF:SS:ID -0.1052:4.5657:0.00806545:0.8681:7727:rs4951929
1 757936 rs4951862 C A . PASS AF=0.8668 ES:SE:LP:AF:SS:ID -0.2473:4.5669:0.0191788:0.8668:7727:rs4951862
1 758144 rs3131956 A G . PASS AF=0.8391 ES:SE:LP:AF:SS:ID -0.089:4.1962:0.0074023:0.8391:9063:rs3131956
1 758626 rs3131954 C T . PASS AF=0.8641 ES:SE:LP:AF:SS:ID 0.9036:4.7078:0.0717066:0.8641:6860:rs3131954
1 768448 rs12562034 G A . PASS AF=0.09763 ES:SE:LP:AF:SS:ID -9.6035:4.704:1.3851:0.09763:8790:rs12562034
1 769963 rs7518545 G A . PASS AF=0.09499 ES:SE:LP:AF:SS:ID -9.7268:4.9598:1.30225:0.09499:8790:rs7518545
1 798400 rs10900604 A G . PASS AF=0.2203 ES:SE:LP:AF:SS:ID -4.6428:3.8629:0.639407:0.2203:7675:rs10900604
1 798959 rs11240777 G A . PASS AF=0.2269 ES:SE:LP:AF:SS:ID -4.3922:3.6566:0.638839:0.2269:7675:rs11240777
1 876499 rs4372192 A G . PASS AF=0.94987 ES:SE:LP:AF:SS:ID -11.2257:7.136:0.936667:0.94987:8487:rs4372192
1 879676 rs6605067 G A . PASS AF=0.94987 ES:SE:LP:AF:SS:ID -10.2731:7.0266:0.842543:0.94987:8487:rs6605067
1 879687 rs2839 T C . PASS AF=0.95119 ES:SE:LP:AF:SS:ID -8.7777:6.9321:0.6874:0.95119:9037:rs2839
1 880238 rs3748592 A G . PASS AF=0.95251 ES:SE:LP:AF:SS:ID -8.967:6.9233:0.709298:0.95251:9037:rs3748592
1 882803 rs2340582 A G . PASS AF=0.95119 ES:SE:LP:AF:SS:ID -8.5355:6.7285:0.689094:0.95119:9037:rs2340582
1 884815 rs4246503 A G . PASS AF=0.95119 ES:SE:LP:AF:SS:ID -8.1052:6.5287:0.668775:0.95119:9037:rs4246503
1 885676 rs4970377 C A . PASS AF=0.94327 ES:SE:LP:AF:SS:ID -4.8959:6.3638:0.354873:0.94327:9037:rs4970377
1 885689 rs4970452 G A . PASS AF=0.94987 ES:SE:LP:AF:SS:ID -8.2109:6.5956:0.671213:0.94987:9037:rs4970452
1 885699 rs4970376 A G . PASS AF=0.95119 ES:SE:LP:AF:SS:ID -8.0955:6.5025:0.671417:0.95119:9037:rs4970376
1 886006 rs4970375 T C . PASS AF=0.95119 ES:SE:LP:AF:SS:ID -8.2221:6.4254:0.697453:0.95119:9037:rs4970375
1 887801 rs3828047 A G . PASS AF=0.95119 ES:SE:LP:AF:SS:ID -8.2728:6.337:0.717378:0.95119:9037:rs3828047
1 888639 rs3748596 T C . PASS AF=0.95119 ES:SE:LP:AF:SS:ID -8.2829:6.3253:0.720333:0.95119:9037:rs3748596
1 888659 rs3748597 T C . PASS AF=0.95119 ES:SE:LP:AF:SS:ID -8.2246:6.3154:0.714893:0.95119:9037:rs3748597
1 889238 rs3828049 G A . PASS AF=0.04749 ES:SE:LP:AF:SS:ID 8.4078:6.4226:0.720105:0.04749:9037:rs3828049
1 889713 rs13303051 C A . PASS AF=0.94063 ES:SE:LP:AF:SS:ID -5.2364:6.0912:0.408935:0.94063:9037:rs13303051
1 891021 rs13302957 G A . PASS AF=0.94591 ES:SE:LP:AF:SS:ID -8.1022:6.3198:0.699405:0.94591:9037:rs13302957
1 892745 rs13303227 G A . PASS AF=0.95119 ES:SE:LP:AF:SS:ID -8.4946:6.4457:0.726999:0.95119:9037:rs13303227
1 893280 rs4970371 G A . PASS AF=0.95251 ES:SE:LP:AF:SS:ID -8.5466:6.5563:0.715795:0.95251:9037:rs4970371
1 893631 rs6605069 A G . PASS AF=0.93931 ES:SE:LP:AF:SS:ID -5.6926:6.2571:0.440213:0.93931:9037:rs6605069
1 893719 rs4970445 G A . PASS AF=0.92744 ES:SE:LP:AF:SS:ID -7.1093:6.2715:0.590067:0.92744:8487:rs4970445
1 896476 rs28393498 A G . PASS AF=0.93536 ES:SE:LP:AF:SS:ID -8.7769:6.5798:0.739452:0.93536:8487:rs28393498
1 897564 rs13303229 T C . PASS AF=0.94459 ES:SE:LP:AF:SS:ID -7.1739:6.6894:0.547447:0.94459:8487:rs13303229
1 897738 rs6696971 C T . PASS AF=0.05541 ES:SE:LP:AF:SS:ID 7.525:6.6891:0.584026:0.05541:8487:rs6696971
1 898323 rs6605071 T C . PASS AF=0.94723 ES:SE:LP:AF:SS:ID -8.1153:6.9184:0.618344:0.94723:9037:rs6605071
1 898467 rs41285808 C T . PASS AF=0.04617 ES:SE:LP:AF:SS:ID 8.4611:6.941:0.652085:0.04617:9037:rs41285808
1 913889 rs2340596 G A . PASS AF=0.6003 ES:SE:LP:AF:SS:ID -0.0893:2.8569:0.0109508:0.6003:10039:rs2340596
1 914940 rs13303033 T C . PASS AF=0.5858 ES:SE:LP:AF:SS:ID -0.3993:2.7732:0.0528114:0.5858:10039:rs13303033
1 916834 rs6694632 G A . PASS AF=0.5989 ES:SE:LP:AF:SS:ID -0.2455:2.7213:0.0324052:0.5989:10039:rs6694632
1 918384 rs13303118 G T . PASS AF=0.5871 ES:SE:LP:AF:SS:ID -0.4134:2.678:0.0568519:0.5871:10039:rs13303118
1 918573 rs2341354 A G . PASS AF=0.5963 ES:SE:LP:AF:SS:ID -0.2917:2.6797:0.0393865:0.5963:10039:rs2341354