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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-22601_41223241/ukb-d-22601_41223241.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-22601_41223241/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 14:58:38 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22601_41223241/ukb-d-22601_41223241.vcf.gz ...
Read summary statistics for 10383546 SNPs.
Dropped 8236 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, 1280249 SNPs remain.
After merging with regression SNP LD, 1280249 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.002 (0.0047)
Lambda GC: 1.0022
Mean Chi^2: 0.9999
Intercept: 0.9963 (0.0063)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 15:00:43 2019
Total time elapsed: 2.0m:5.18s
{
"af_correlation": 0.9435,
"inflation_factor": 0.9912,
"mean_EFFECT": 2.9764e-07,
"n": 89866,
"n_snps": 10383546,
"n_clumped_hits": 2,
"n_p_sig": 2,
"n_mono": 0,
"n_ns": 1105395,
"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": 204242,
"n_est": 89949.525,
"ratio_se_n": 1.0005,
"mean_diff": 2.0926e-06,
"ratio_diff": 6.2891,
"sd_y_est1": 0.1446,
"sd_y_est2": 0.1447,
"r2_sum1": 0,
"r2_sum2": 0.0007,
"r2_sum3": 0.0007,
"r2_sum4": 0.0007,
"ldsc_nsnp_merge_refpanel_ld": 1280249,
"ldsc_nsnp_merge_regression_ld": 1280249,
"ldsc_observed_scale_h2_beta": 0.002,
"ldsc_observed_scale_h2_se": 0.0047,
"ldsc_intercept_beta": 0.9963,
"ldsc_intercept_se": 0.0063,
"ldsc_lambda_gc": 1.0022,
"ldsc_mean_chisq": 0.9999,
"ldsc_ratio": 37
}
name | value |
---|---|
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 | 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×N×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, ˆn.ratio_se_n
: ratio_se_n=√ˆn√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
: mean_diff=∑j^βstdj−βjn_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
: ratio_diff=|mean_diffmean_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
: r2=∑j2×β2j×MAFj×(1−MAFj)var1, var1=1.2
: r2=∑j2×β2j×MAFj×(1−MAFj)var2, var2=^sd1y2,3
: r2=∑j2×β2j×MAFj×(1−MAFj)var3, var3=^sd2y2,4
: r2=∑jFjFj+n−2, F=β2jse2j.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 χ2 statistics.ldsc_ratio
: ldsc_intercept_beta−1ldsc_mean_chisq−1, the proportion of the inflation in the mean χ2 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 h2 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 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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 | 10375875 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 49372 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 30615 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.077021e+00 | 6.178319e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.300000e+01 | ▇▅▅▂▂ |
numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.878319e+07 | 5.605805e+07 | 3.02000e+02 | 3.254588e+07 | 6.971102e+07 | 1.147296e+08 | 2.492297e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.000000e-07 | 1.790700e-03 | -1.93929e-02 | -7.861000e-04 | -7.700000e-06 | 7.708000e-04 | 1.936850e-02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.508000e-03 | 9.848000e-04 | 5.64100e-04 | 7.571000e-04 | 1.057600e-03 | 1.974700e-03 | 5.601300e-03 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.011278e-01 | 2.886251e-01 | 0.00000e+00 | 2.506709e-01 | 5.018905e-01 | 7.511644e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.011260e-01 | 2.886262e-01 | 0.00000e+00 | 2.506676e-01 | 5.018880e-01 | 7.511630e-01 | 9.999998e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.459513e-01 | 2.627429e-01 | 6.50360e-03 | 3.239230e-02 | 1.369280e-01 | 3.934328e-01 | 9.934960e-01 | ▇▂▂▁▁ |
numeric | AF_reference | 204242 | 0.9803302 | NA | NA | NA | NA | NA | 2.457891e-01 | 2.536552e-01 | 0.00000e+00 | 3.434500e-02 | 1.535540e-01 | 3.901760e-01 | 1.000000e+00 | ▇▃▂▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.986600e+04 | 0.000000e+00 | 8.98660e+04 | 8.986600e+04 | 8.986600e+04 | 8.986600e+04 | 8.986600e+04 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
1 | 692794 | rs530212009 | CA | C | -0.0010333 | 0.0011917 | 0.3859277 | 0.3859248 | 0.1114870 | 0.1894970 | 89866 |
1 | 693731 | rs12238997 | A | G | -0.0015737 | 0.0011289 | 0.1633180 | 0.1633135 | 0.1164980 | 0.1417730 | 89866 |
1 | 707522 | rs371890604 | G | C | -0.0015165 | 0.0012691 | 0.2321250 | 0.2321223 | 0.0978285 | 0.1293930 | 89866 |
1 | 717587 | rs144155419 | G | A | -0.0008184 | 0.0030229 | 0.7865965 | 0.7865948 | 0.0158090 | 0.0045926 | 89866 |
1 | 730087 | rs148120343 | T | C | -0.0015684 | 0.0015654 | 0.3163749 | 0.3163716 | 0.0569661 | 0.0127796 | 89866 |
1 | 731718 | rs142557973 | T | C | -0.0013896 | 0.0010712 | 0.1945822 | 0.1945760 | 0.1223780 | 0.1543530 | 89866 |
1 | 732032 | rs61770163 | A | C | -0.0016448 | 0.0011421 | 0.1498121 | 0.1498071 | 0.1220530 | 0.1555510 | 89866 |
1 | 734349 | rs141242758 | T | C | -0.0012980 | 0.0010720 | 0.2259868 | 0.2259850 | 0.1216170 | 0.1525560 | 89866 |
1 | 749963 | rs529266287 | T | TAA | 0.0010062 | 0.0010547 | 0.3400870 | 0.3400848 | 0.8689590 | 0.7641770 | 89866 |
1 | 751343 | rs28544273 | T | A | -0.0010749 | 0.0010456 | 0.3039338 | 0.3039305 | 0.1236780 | 0.2426120 | 89866 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
23 | 154923311 | rs141127553 | C | T | -0.0012406 | 0.0012539 | 0.3224698 | 0.3224670 | 0.0553576 | 0.0309934 | 89866 |
23 | 154923374 | rs111332691 | T | A | 0.0000159 | 0.0013650 | 0.9907060 | 0.9907059 | 0.0449113 | 0.0116556 | 89866 |
23 | 154925045 | rs509981 | C | T | 0.0000131 | 0.0006583 | 0.9840730 | 0.9840733 | 0.2444280 | 0.3634440 | 89866 |
23 | 154925895 | rs538470 | C | T | -0.0001110 | 0.0006732 | 0.8690131 | 0.8690125 | 0.2408760 | 0.3634440 | 89866 |
23 | 154927581 | rs644138 | G | A | -0.0002773 | 0.0006193 | 0.6543031 | 0.6543023 | 0.3001910 | 0.4635760 | 89866 |
23 | 154929412 | rs557132 | C | T | -0.0000270 | 0.0006585 | 0.9673060 | 0.9673061 | 0.2442750 | 0.3568210 | 89866 |
23 | 154929637 | rs35185538 | CT | C | -0.0000108 | 0.0006876 | 0.9875160 | 0.9875160 | 0.2286930 | 0.3011920 | 89866 |
23 | 154929952 | rs4012982 | CAA | C | -0.0002842 | 0.0006930 | 0.6817765 | 0.6817746 | 0.2381980 | 0.3165560 | 89866 |
23 | 154930230 | rs781880 | A | G | -0.0000225 | 0.0006583 | 0.9727819 | 0.9727819 | 0.2447120 | 0.3618540 | 89866 |
23 | 154930487 | rs781879 | T | A | -0.0006473 | 0.0022332 | 0.7719355 | 0.7719353 | 0.0196791 | 0.1263580 | 89866 |
1 692794 rs530212009 CA C . PASS AF=0.111487 ES:SE:LP:AF:SS:ID -0.00103325:0.00119171:0.413494:0.111487:89866:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116498 ES:SE:LP:AF:SS:ID -0.00157366:0.00112887:0.786966:0.116498:89866:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0978285 ES:SE:LP:AF:SS:ID -0.00151646:0.0012691:0.634278:0.0978285:89866:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015809 ES:SE:LP:AF:SS:ID -0.000818416:0.00302294:0.104248:0.015809:89866:rs144155419
1 730087 rs148120343 T C . PASS AF=0.0569661 ES:SE:LP:AF:SS:ID -0.00156839:0.00156535:0.499798:0.0569661:89866:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122378 ES:SE:LP:AF:SS:ID -0.00138957:0.00107124:0.710897:0.122378:89866:rs58276399
1 732032 rs61770163 A C . PASS AF=0.122053 ES:SE:LP:AF:SS:ID -0.00164481:0.00114206:0.824453:0.122053:89866:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121617 ES:SE:LP:AF:SS:ID -0.00129799:0.00107204:0.645917:0.121617:89866:rs141242758
1 749963 rs529266287 T TAA . PASS AF=0.868959 ES:SE:LP:AF:SS:ID 0.00100621:0.00105473:0.46841:0.868959:89866:rs529266287
1 751343 rs28544273 T A . PASS AF=0.123678 ES:SE:LP:AF:SS:ID -0.00107493:0.00104561:0.517221:0.123678:89866:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143191 ES:SE:LP:AF:SS:ID -0.000533502:0.00103522:0.217306:0.143191:89866:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123813 ES:SE:LP:AF:SS:ID -0.00107701:0.0010441:0.519562:0.123813:89866:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869927 ES:SE:LP:AF:SS:ID 0.00111096:0.00101733:0.560948:0.869927:89866:rs3115860
1 753425 rs3131970 T C . PASS AF=0.87461 ES:SE:LP:AF:SS:ID 0.00118818:0.00103392:0.601232:0.87461:89866:rs3131970
1 753541 rs2073813 G A . PASS AF=0.12951 ES:SE:LP:AF:SS:ID -0.00103809:0.00102044:0.51002:0.12951:89866:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0357365 ES:SE:LP:AF:SS:ID 0.000251996:0.00186692:0.0493295:0.0357365:89866:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869574 ES:SE:LP:AF:SS:ID 0.00116496:0.00101643:0.599034:0.869574:89866:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869652 ES:SE:LP:AF:SS:ID 0.00115557:0.00101689:0.592096:0.869652:89866:rs3131968
1 754334 rs3131967 T C . PASS AF=0.86957 ES:SE:LP:AF:SS:ID 0.00116749:0.00101639:0.600851:0.86957:89866:rs3131967
1 755890 rs3115858 A T . PASS AF=0.869566 ES:SE:LP:AF:SS:ID 0.00120325:0.00101438:0.627921:0.869566:89866:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126879 ES:SE:LP:AF:SS:ID -0.00105058:0.00103552:0.508179:0.126879:89866:rs61768170
1 756604 rs3131962 A G . PASS AF=0.869094 ES:SE:LP:AF:SS:ID 0.00118858:0.00101175:0.61963:0.869094:89866:rs3131962
1 757640 rs3115853 G A . PASS AF=0.868498 ES:SE:LP:AF:SS:ID 0.00131726:0.00101113:0.715211:0.868498:89866:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869245 ES:SE:LP:AF:SS:ID 0.00124483:0.00101267:0.659594:0.869245:89866:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869251 ES:SE:LP:AF:SS:ID 0.00124524:0.00101274:0.659832:0.869251:89866:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869252 ES:SE:LP:AF:SS:ID 0.00124369:0.00101275:0.658694:0.869252:89866:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869724 ES:SE:LP:AF:SS:ID 0.00120721:0.00101544:0.629855:0.869724:89866:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0991203 ES:SE:LP:AF:SS:ID -0.00176599:0.00118214:0.869007:0.0991203:89866:rs10157329
1 759837 rs3115851 T A . PASS AF=0.873732 ES:SE:LP:AF:SS:ID 0.00122422:0.00103052:0.6292:0.873732:89866:rs3115851
1 761732 rs2286139 C T . PASS AF=0.863116 ES:SE:LP:AF:SS:ID 0.00109907:0.00101079:0.557696:0.863116:89866:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868511 ES:SE:LP:AF:SS:ID 0.00116189:0.00102089:0.593334:0.868511:89866:rs1057213
1 762273 rs3115849 G A . PASS AF=0.86539 ES:SE:LP:AF:SS:ID 0.00108142:0.00102104:0.538291:0.86539:89866:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0994301 ES:SE:LP:AF:SS:ID -0.00173038:0.00122269:0.804081:0.0994301:89866:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870696 ES:SE:LP:AF:SS:ID 0.00105113:0.00103278:0.510333:0.870696:89866:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870695 ES:SE:LP:AF:SS:ID 0.00105096:0.00103278:0.510221:0.870695:89866:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870693 ES:SE:LP:AF:SS:ID 0.00105091:0.00103279:0.510191:0.870693:89866:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871061 ES:SE:LP:AF:SS:ID 0.00103536:0.00103327:0.499847:0.871061:89866:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126484 ES:SE:LP:AF:SS:ID -0.00105085:0.00103432:0.509144:0.126484:89866:rs7515915
1 766007 rs61768174 A C . PASS AF=0.106022 ES:SE:LP:AF:SS:ID -0.0017482:0.00112438:0.92084:0.106022:89866:rs61768174
1 766105 rs2519015 T A . PASS AF=0.854451 ES:SE:LP:AF:SS:ID 0.00131077:0.00101054:0.710853:0.854451:89866:rs2519015
1 768116 rs376645387 A AGTTTT . PASS AF=0.839008 ES:SE:LP:AF:SS:ID -0.00231964:0.000998292:1.69576:0.839008:89866:rs376645387
1 768253 rs2977608 A C . PASS AF=0.76317 ES:SE:LP:AF:SS:ID -0.000239038:0.000802644:0.115859:0.76317:89866:rs2977608
1 768448 rs12562034 G A . PASS AF=0.10519 ES:SE:LP:AF:SS:ID 0.00199201:0.00110615:1.1443:0.10519:89866:rs12562034
1 768819 rs12562811 C T . PASS AF=0.00773441 ES:SE:LP:AF:SS:ID 0.00282076:0.00409813:0.308685:0.00773441:89866:rs12562811
1 769138 rs59306077 CAT C . PASS AF=0.129876 ES:SE:LP:AF:SS:ID -0.00105368:0.00101983:0.520688:0.129876:89866:rs762168062
1 769223 rs60320384 C G . PASS AF=0.129602 ES:SE:LP:AF:SS:ID -0.00112184:0.00101849:0.567517:0.129602:89866:rs60320384
1 769963 rs7518545 G A . PASS AF=0.104469 ES:SE:LP:AF:SS:ID 0.00203935:0.00111468:1.17185:0.104469:89866:rs7518545
1 770181 rs146076599 A G . PASS AF=0.00900456 ES:SE:LP:AF:SS:ID 0.00234945:0.00393357:0.259384:0.00900456:89866:rs146076599
1 770377 rs112563271 A T . PASS AF=0.00774975 ES:SE:LP:AF:SS:ID 0.00274241:0.0041155:0.296551:0.00774975:89866:rs112563271
1 770886 rs371458725 G A . PASS AF=0.103468 ES:SE:LP:AF:SS:ID 0.0020306:0.00112435:1.14925:0.103468:89866:rs371458725