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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-1091/ieu-a-1091.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-1091/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 16:49:45 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ieu-a-import/processed/ieu-a-1091/ieu-a-1091.vcf.gz ...
Read summary statistics for 8973300 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, 1258582 SNPs remain.
After merging with regression SNP LD, 1258582 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.001 (0.0064)
Lambda GC: 1.0314
Mean Chi^2: 1.0346
Intercept: 1.036 (0.0065)
Ratio: 1.0427 (0.1892)
Analysis finished at Tue Feb 4 16:51:15 2020
Total time elapsed: 1.0m:29.65s
{
"af_correlation": 0.9438,
"inflation_factor": 1.0475,
"mean_EFFECT": 0,
"n": 75244,
"n_snps": 8973300,
"n_clumped_hits": 1,
"n_p_sig": 1,
"n_mono": 0,
"n_ns": 615334,
"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": 166203,
"n_est": 74392.0791,
"ratio_se_n": 0.9943,
"mean_diff": 0.0001,
"ratio_diff": 47.8099,
"sd_y_est1": 0.1672,
"sd_y_est2": 0.1663,
"r2_sum1": 0,
"r2_sum2": 0.0005,
"r2_sum3": 0.0005,
"r2_sum4": 0.0004,
"ldsc_nsnp_merge_refpanel_ld": 1258582,
"ldsc_nsnp_merge_regression_ld": 1258582,
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": 1.036,
"ldsc_intercept_se": 0.0065,
"ldsc_lambda_gc": 1.0314,
"ldsc_mean_chisq": 1.0346,
"ldsc_ratio": 1.0405
}
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 | 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 | 58 | 0 | 8973299 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 45 | 0 | 34759 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 45 | 0 | 18428 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.670575e+00 | 5.777711e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.865655e+07 | 5.656167e+07 | 3.02000e+02 | 3.199260e+07 | 6.913289e+07 | 1.145153e+08 | 2.492393e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.200000e-05 | 2.013800e-03 | -1.92893e-02 | -9.627000e-04 | -8.200000e-06 | 9.500000e-04 | 2.410590e-02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.714500e-03 | 9.837000e-04 | 8.42100e-04 | 9.487000e-04 | 1.283400e-03 | 2.216200e-03 | 6.829900e-03 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.944585e-01 | 2.899777e-01 | 0.00000e+00 | 2.399999e-01 | 4.899999e-01 | 7.499995e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.944578e-01 | 2.899517e-01 | 0.00000e+00 | 2.422914e-01 | 4.923015e-01 | 7.451297e-01 | 9.999998e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.586996e-01 | 2.637445e-01 | 1.00010e-02 | 4.224200e-02 | 1.529370e-01 | 4.112290e-01 | 9.899990e-01 | ▇▂▂▁▁ |
numeric | AF_reference | 166203 | 0.9814781 | NA | NA | NA | NA | NA | 2.549491e-01 | 2.527002e-01 | 0.00000e+00 | 4.612620e-02 | 1.661340e-01 | 4.007590e-01 | 1.000000e+00 | ▇▃▂▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.524400e+04 | 0.000000e+00 | 7.52440e+04 | 7.524400e+04 | 7.524400e+04 | 7.524400e+04 | 7.524400e+04 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 10177 | rs367896724 | A | AC | -0.0008106 | 0.0012415 | 0.5099998 | 0.5138092 | 0.402314 | 0.4253190 | 75244 |
1 | 10352 | rs555500075 | T | TA | 0.0021928 | 0.0012920 | 0.0899995 | 0.0896553 | 0.390095 | 0.4375000 | 75244 |
1 | 11008 | rs575272151 | C | G | 0.0026090 | 0.0021351 | 0.2200002 | 0.2217147 | 0.086367 | 0.0880591 | 75244 |
1 | 11012 | rs544419019 | C | G | 0.0026090 | 0.0021351 | 0.2200002 | 0.2217147 | 0.086367 | 0.0880591 | 75244 |
1 | 13110 | rs540538026 | G | A | -0.0027612 | 0.0027909 | 0.3200000 | 0.3224862 | 0.059597 | 0.0267572 | 75244 |
1 | 13116 | rs62635286 | T | G | 0.0033615 | 0.0016967 | 0.0479999 | 0.0475664 | 0.188535 | 0.0970447 | 75244 |
1 | 13273 | rs531730856 | G | C | 0.0010660 | 0.0019509 | 0.5800000 | 0.5847955 | 0.133959 | 0.0950479 | 75244 |
1 | 14464 | rs546169444 | A | T | -0.0022996 | 0.0017740 | 0.1900002 | 0.1948786 | 0.155098 | 0.0958466 | 75244 |
1 | 14604 | rs541940975 | A | G | 0.0015363 | 0.0016139 | 0.3400001 | 0.3411444 | 0.193476 | 0.1475640 | 75244 |
1 | 14933 | rs199856693 | G | A | 0.0041727 | 0.0030182 | 0.1700000 | 0.1668195 | 0.047152 | 0.0283546 | 75244 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51233347 | rs62240044 | T | C | 0.0018023 | 0.0010888 | 0.0980009 | 0.0978483 | 0.275895 | 0.2134580 | 75244 |
22 | 51233666 | rs11091014 | C | T | -0.0020163 | 0.0037051 | 0.5900000 | 0.5863104 | 0.020872 | 0.0970447 | 75244 |
22 | 51234343 | rs374867791 | G | T | -0.0019097 | 0.0036878 | 0.5999997 | 0.6045700 | 0.021048 | 0.1002400 | 75244 |
22 | 51234799 | rs191117135 | G | A | 0.0019404 | 0.0039422 | 0.6200004 | 0.6225637 | 0.015260 | 0.0059904 | 75244 |
22 | 51235959 | rs200189535 | T | C | 0.0007679 | 0.0012721 | 0.5500004 | 0.5460534 | 0.192540 | 0.1996810 | 75244 |
22 | 51236013 | rs200507571 | A | AT | 0.0003315 | 0.0010864 | 0.7600007 | 0.7602386 | 0.252329 | 0.1487620 | 75244 |
22 | 51237063 | rs3896457 | T | C | 0.0013040 | 0.0010483 | 0.2099999 | 0.2135417 | 0.294328 | 0.2050720 | 75244 |
22 | 51237364 | rs200607599 | A | G | 0.0078878 | 0.0043530 | 0.0700003 | 0.0699772 | 0.015952 | 0.0187700 | 75244 |
22 | 51237712 | rs370652263 | G | A | -0.0038427 | 0.0020037 | 0.0549997 | 0.0551410 | 0.055591 | 0.0690895 | 75244 |
22 | 51244237 | rs575160859 | C | T | 0.0005318 | 0.0051900 | 0.9199999 | 0.9183870 | 0.013418 | 0.0037939 | 75244 |
1 10177 rs367896724 A AC . PASS AF=0.402314 ES:SE:LP:AF:SS:ID -0.000810578:0.00124147:0.29243:0.402314:75244:rs367896724
1 10352 rs555500075 T TA . PASS AF=0.390095 ES:SE:LP:AF:SS:ID 0.00219279:0.00129199:1.04576:0.390095:75244:rs555500075
1 11008 rs575272151 C G . PASS AF=0.086367 ES:SE:LP:AF:SS:ID 0.00260904:0.00213509:0.657577:0.086367:75244:rs575272151
1 11012 rs544419019 C G . PASS AF=0.086367 ES:SE:LP:AF:SS:ID 0.00260904:0.00213509:0.657577:0.086367:75244:rs544419019
1 13110 rs540538026 G A . PASS AF=0.059597 ES:SE:LP:AF:SS:ID -0.00276119:0.00279088:0.49485:0.059597:75244:rs540538026
1 13116 rs62635286 T G . PASS AF=0.188535 ES:SE:LP:AF:SS:ID 0.00336146:0.00169666:1.31876:0.188535:75244:rs62635286
1 13273 rs531730856 G C . PASS AF=0.133959 ES:SE:LP:AF:SS:ID 0.00106597:0.00195092:0.236572:0.133959:75244:rs531730856
1 14464 rs546169444 A T . PASS AF=0.155098 ES:SE:LP:AF:SS:ID -0.00229959:0.00177399:0.721246:0.155098:75244:rs546169444
1 14604 rs541940975 A G . PASS AF=0.193476 ES:SE:LP:AF:SS:ID 0.00153632:0.00161394:0.468521:0.193476:75244:rs541940975
1 14933 rs199856693 G A . PASS AF=0.047152 ES:SE:LP:AF:SS:ID 0.00417269:0.00301823:0.769551:0.047152:75244:rs199856693
1 15820 rs2691315 G T . PASS AF=0.27174 ES:SE:LP:AF:SS:ID 0.000715229:0.00148082:0.200659:0.27174:75244:rs2691315
1 15903 rs557514207 G GC . PASS AF=0.408683 ES:SE:LP:AF:SS:ID -0.000837884:0.00123056:0.30103:0.408683:75244:rs557514207
1 16949 rs199745162 A C . PASS AF=0.020279 ES:SE:LP:AF:SS:ID -0.000841718:0.00449154:0.0705811:0.020279:75244:rs199745162
1 18849 rs533090414 C G . PASS AF=0.974295 ES:SE:LP:AF:SS:ID 0.00380333:0.00365088:0.522879:0.974295:75244:rs533090414
1 30923 rs806731 G T . PASS AF=0.903876 ES:SE:LP:AF:SS:ID -0.00165064:0.00219911:0.346787:0.903876:75244:rs806731
1 47159 rs540662756 T C . PASS AF=0.065472 ES:SE:LP:AF:SS:ID 0.00269439:0.0026477:0.508638:0.065472:75244:rs540662756
1 49554 rs539322794 A G . PASS AF=0.097473 ES:SE:LP:AF:SS:ID 0.00447809:0.00220334:1.37675:0.097473:75244:rs539322794
1 51479 rs116400033 T A . PASS AF=0.209986 ES:SE:LP:AF:SS:ID -0.00242042:0.00156818:0.920819:0.209986:75244:rs116400033
1 52238 rs2691277 T G . PASS AF=0.976797 ES:SE:LP:AF:SS:ID 0.000411182:0.0043677:0.0362122:0.976797:75244:rs2691277
1 54490 rs141149254 G A . PASS AF=0.151422 ES:SE:LP:AF:SS:ID -0.00140838:0.00176195:0.376751:0.151422:75244:rs141149254
1 54716 rs569128616 C T . PASS AF=0.42454 ES:SE:LP:AF:SS:ID 0.00121441:0.00131991:0.443698:0.42454:75244:rs569128616
1 55164 rs3091274 C A . PASS AF=0.981509 ES:SE:LP:AF:SS:ID -5.05541e-05:0.00475658:0.00436481:0.981509:75244:rs3091274
1 55326 rs3107975 T C . PASS AF=0.01603 ES:SE:LP:AF:SS:ID -0.00200276:0.00531609:0.148742:0.01603:75244:rs3107975
1 55545 rs28396308 C T . PASS AF=0.261517 ES:SE:LP:AF:SS:ID 0.00262902:0.00147475:1.12494:0.261517:75244:rs28396308
1 57292 rs201418760 C T . PASS AF=0.02082 ES:SE:LP:AF:SS:ID 0.00617961:0.00467584:0.721246:0.02082:75244:rs201418760
1 58814 rs114420996 G A . PASS AF=0.094084 ES:SE:LP:AF:SS:ID 0.00328455:0.00224466:0.853872:0.094084:75244:rs114420996
1 59040 rs62637815 T C . PASS AF=0.091395 ES:SE:LP:AF:SS:ID 0.0045573:0.00226783:1.35655:0.091395:75244:rs62637815
1 60249 rs547227933 C T . PASS AF=0.01879 ES:SE:LP:AF:SS:ID 0.0100237:0.00457692:1.5376:0.01879:75244:rs547227933
1 60351 rs62637817 A G . PASS AF=0.084746 ES:SE:LP:AF:SS:ID 0.00399881:0.00234214:1.05552:0.084746:75244:rs62637817
1 61920 rs62637820 G A . PASS AF=0.030102 ES:SE:LP:AF:SS:ID 0.00350221:0.00376609:0.455932:0.030102:75244:rs62637820
1 63671 rs80011619 G A . PASS AF=0.160843 ES:SE:LP:AF:SS:ID 0.00109631:0.001711:0.283997:0.160843:75244:rs80011619
1 64649 rs181431124 A C . PASS AF=0.027235 ES:SE:LP:AF:SS:ID 0.00268808:0.00393489:0.309804:0.027235:75244:rs181431124
1 64931 rs62639104 G A . PASS AF=0.083092 ES:SE:LP:AF:SS:ID 0.00434445:0.00237241:1.17393:0.083092:75244:rs62639104
1 66219 rs181028663 A T . PASS AF=0.018879 ES:SE:LP:AF:SS:ID -0.0024816:0.00438593:0.244125:0.018879:75244:rs181028663
1 68082 rs367789441 T C . PASS AF=0.072252 ES:SE:LP:AF:SS:ID 0.00149635:0.00249855:0.259637:0.072252:75244:rs367789441
1 69428 rs140739101 T G . PASS AF=0.036251 ES:SE:LP:AF:SS:ID 0.00325961:0.00354548:0.443698:0.036251:75244:rs140739101
1 69761 rs200505207 A T . PASS AF=0.075779 ES:SE:LP:AF:SS:ID 0.0017356:0.002446:0.318759:0.075779:75244:rs200505207
1 69897 rs200676709 T C . PASS AF=0.742291 ES:SE:LP:AF:SS:ID -0.00203319:0.00148539:0.769551:0.742291:75244:rs200676709
1 72526 rs547237130 A G . PASS AF=0.041676 ES:SE:LP:AF:SS:ID 0.00766014:0.00333694:1.65758:0.041676:75244:rs547237130
1 73490 rs558384541 T C . PASS AF=0.017948 ES:SE:LP:AF:SS:ID 0.00143248:0.00490095:0.113509:0.017948:75244:rs558384541
1 74790 rs13328700 C G . PASS AF=0.035774 ES:SE:LP:AF:SS:ID 0.00199323:0.00338787:0.251812:0.035774:75244:rs13328700
1 74792 rs13328684 G A . PASS AF=0.035774 ES:SE:LP:AF:SS:ID 0.00199323:0.00338787:0.251812:0.035774:75244:rs13328684
1 76838 rs563953605 T G . PASS AF=0.078788 ES:SE:LP:AF:SS:ID 0.00633547:0.00240602:2.07058:0.078788:75244:rs563953605
1 76854 rs367666799 A G . PASS AF=0.081423 ES:SE:LP:AF:SS:ID 7.28907e-05:0.00234232:0.00877392:0.081423:75244:rs367666799
1 77866 rs563593912 C T . PASS AF=0.078671 ES:SE:LP:AF:SS:ID 0.00632923:0.00240671:2.07058:0.078671:75244:rs563593912
1 77874 rs62641297 G A . PASS AF=0.078671 ES:SE:LP:AF:SS:ID 0.00632923:0.00240671:2.07058:0.078671:75244:rs62641297
1 78061 rs550898066 C G . PASS AF=0.010458 ES:SE:LP:AF:SS:ID 0.00946009:0.00630422:0.886057:0.010458:75244:rs550898066
1 81587 rs536406113 C T . PASS AF=0.062285 ES:SE:LP:AF:SS:ID 0.00012552:0.0026495:0.0177288:0.062285:75244:rs536406113
1 82163 rs139113303 G A . PASS AF=0.079566 ES:SE:LP:AF:SS:ID 0.000528737:0.00236672:0.0861861:0.079566:75244:rs139113303
1 82609 rs149189449 C G . PASS AF=0.079597 ES:SE:LP:AF:SS:ID 0.000512845:0.00236646:0.0809219:0.079597:75244:rs149189449