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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_3119/ukb-d-22617_3119.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_3119/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 14:49:05 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-22617_3119/ukb-d-22617_3119.vcf.gz ...
Read summary statistics for 10465620 SNPs.
Dropped 8334 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, 1280588 SNPs remain.
After merging with regression SNP LD, 1280588 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: -0.0063 (0.0043)
Lambda GC: 0.9936
Mean Chi^2: 0.998
Intercept: 1.0093 (0.0058)
Ratio: NA (mean chi^2 < 1)
Analysis finished at Mon Nov 25 14:50:48 2019
Total time elapsed: 1.0m:43.4s
{
"af_correlation": 0.9438,
"inflation_factor": 0.9956,
"mean_EFFECT": 3.7223e-06,
"n": 91149,
"n_snps": 10465620,
"n_clumped_hits": 1,
"n_p_sig": 1,
"n_mono": 0,
"n_ns": 1109936,
"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": 205869,
"n_est": 91219.4772,
"ratio_se_n": 1.0004,
"mean_diff": 0,
"ratio_diff": 16.4281,
"sd_y_est1": 0.1474,
"sd_y_est2": 0.1474,
"r2_sum1": 7.9042e-06,
"r2_sum2": 0.0004,
"r2_sum3": 0.0004,
"r2_sum4": 0.0003,
"ldsc_nsnp_merge_refpanel_ld": 1280588,
"ldsc_nsnp_merge_regression_ld": 1280588,
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": 1.0093,
"ldsc_intercept_se": 0.0058,
"ldsc_lambda_gc": 0.9936,
"ldsc_mean_chisq": 0.998,
"ldsc_ratio": -4.65
}
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 | 10457852 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.000000 | 1 | 100 | 0 | 49615 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.000000 | 1 | 342 | 0 | 30710 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.000000 | NA | NA | NA | NA | NA | 9.076239e+00 | 6.178177e+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 | 7.878917e+07 | 5.605522e+07 | 3.02000e+02 | 3.255302e+07 | 6.973055e+07 | 1.147359e+08 | 2.492300e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.000000 | NA | NA | NA | NA | NA | 3.700000e-06 | 1.860400e-03 | -1.79154e-02 | -8.086000e-04 | -1.150000e-05 | 7.863000e-04 | 2.094640e-02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.000000 | NA | NA | NA | NA | NA | 1.549200e-03 | 1.026600e-03 | 5.70400e-04 | 7.675000e-04 | 1.078300e-03 | 2.034500e-03 | 5.693300e-03 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.000000 | NA | NA | NA | NA | NA | 5.001093e-01 | 2.887322e-01 | 0.00000e+00 | 2.497627e-01 | 5.009415e-01 | 7.499702e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.000000 | NA | NA | NA | NA | NA | 5.001075e-01 | 2.887332e-01 | 0.00000e+00 | 2.497593e-01 | 5.009391e-01 | 7.499688e-01 | 9.999999e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.000000 | NA | NA | NA | NA | NA | 2.441738e-01 | 2.626611e-01 | 6.19420e-03 | 3.125010e-02 | 1.343480e-01 | 3.906390e-01 | 9.938050e-01 | ▇▂▂▁▁ |
numeric | AF_reference | 205869 | 0.980329 | NA | NA | NA | NA | NA | 2.440568e-01 | 2.535902e-01 | 0.00000e+00 | 3.274760e-02 | 1.511580e-01 | 3.875800e-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 | 0.0026574 | 0.0012065 | 0.0276261 | 0.0276234 | 0.1114870 | 0.1894970 | 91149 |
1 | 693731 | rs12238997 | A | G | 0.0017578 | 0.0011427 | 0.1239730 | 0.1239700 | 0.1164590 | 0.1417730 | 91149 |
1 | 707522 | rs371890604 | G | C | 0.0021403 | 0.0012841 | 0.0955741 | 0.0955724 | 0.0978765 | 0.1293930 | 91149 |
1 | 717587 | rs144155419 | G | A | 0.0027402 | 0.0030611 | 0.3707021 | 0.3707002 | 0.0157837 | 0.0045926 | 91149 |
1 | 730087 | rs148120343 | T | C | 0.0017502 | 0.0015839 | 0.2691690 | 0.2691668 | 0.0569973 | 0.0127796 | 91149 |
1 | 731718 | rs142557973 | T | C | 0.0015691 | 0.0010844 | 0.1478788 | 0.1478748 | 0.1223590 | 0.1543530 | 91149 |
1 | 732032 | rs61770163 | A | C | 0.0015624 | 0.0011562 | 0.1765961 | 0.1765927 | 0.1220470 | 0.1555510 | 91149 |
1 | 734349 | rs141242758 | T | C | 0.0016122 | 0.0010852 | 0.1373609 | 0.1373553 | 0.1215880 | 0.1525560 | 91149 |
1 | 749963 | rs529266287 | T | TAA | -0.0018039 | 0.0010674 | 0.0910458 | 0.0910442 | 0.8689170 | 0.7641770 | 91149 |
1 | 751343 | rs28544273 | T | A | 0.0018012 | 0.0010583 | 0.0887524 | 0.0887482 | 0.1236990 | 0.2426120 | 91149 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0015472 | 0.0012694 | 0.2228938 | 0.2228883 | 0.0552869 | 0.0309934 | 91149 |
23 | 154923374 | rs111332691 | T | A | -0.0007980 | 0.0013814 | 0.5634755 | 0.5634737 | 0.0448387 | 0.0116556 | 91149 |
23 | 154925045 | rs509981 | C | T | 0.0003453 | 0.0006657 | 0.6039556 | 0.6039533 | 0.2444670 | 0.3634440 | 91149 |
23 | 154925895 | rs538470 | C | T | 0.0001090 | 0.0006806 | 0.8727340 | 0.8727336 | 0.2409490 | 0.3634440 | 91149 |
23 | 154927581 | rs644138 | G | A | 0.0006519 | 0.0006262 | 0.2978503 | 0.2978470 | 0.3001640 | 0.4635760 | 91149 |
23 | 154929412 | rs557132 | C | T | 0.0003519 | 0.0006659 | 0.5972305 | 0.5972296 | 0.2443160 | 0.3568210 | 91149 |
23 | 154929637 | rs35185538 | CT | C | 0.0003163 | 0.0006953 | 0.6491454 | 0.6491450 | 0.2286640 | 0.3011920 | 91149 |
23 | 154929952 | rs4012982 | CAA | C | 0.0002381 | 0.0007009 | 0.7341081 | 0.7341079 | 0.2382530 | 0.3165560 | 91149 |
23 | 154930230 | rs781880 | A | G | 0.0002543 | 0.0006657 | 0.7024429 | 0.7024420 | 0.2447660 | 0.3618540 | 91149 |
23 | 154930487 | rs781879 | T | A | 0.0013505 | 0.0022577 | 0.5497383 | 0.5497361 | 0.0196632 | 0.1263580 | 91149 |
1 692794 rs530212009 CA C . PASS AF=0.111487 ES:SE:LP:AF:SS:ID 0.00265743:0.0012065:1.55868:0.111487:91149:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.116459 ES:SE:LP:AF:SS:ID 0.00175784:0.0011427:0.906673:0.116459:91149:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0978765 ES:SE:LP:AF:SS:ID 0.00214027:0.00128413:1.01966:0.0978765:91149:rs371890604
1 717587 rs144155419 G A . PASS AF=0.0157837 ES:SE:LP:AF:SS:ID 0.0027402:0.00306112:0.430975:0.0157837:91149:rs144155419
1 730087 rs148120343 T C . PASS AF=0.0569973 ES:SE:LP:AF:SS:ID 0.00175015:0.00158387:0.569975:0.0569973:91149:rs148120343
1 731718 rs58276399 T C . PASS AF=0.122359 ES:SE:LP:AF:SS:ID 0.00156914:0.00108435:0.830094:0.122359:91149:rs58276399
1 732032 rs61770163 A C . PASS AF=0.122047 ES:SE:LP:AF:SS:ID 0.00156237:0.00115618:0.753019:0.122047:91149:rs61770163
1 734349 rs141242758 T C . PASS AF=0.121588 ES:SE:LP:AF:SS:ID 0.00161225:0.00108517:0.862137:0.121588:91149:rs141242758
1 749963 rs529266287 T TAA . PASS AF=0.868917 ES:SE:LP:AF:SS:ID -0.0018039:0.00106745:1.04074:0.868917:91149:rs529266287
1 751343 rs28544273 T A . PASS AF=0.123699 ES:SE:LP:AF:SS:ID 0.00180125:0.00105829:1.05182:0.123699:91149:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.143202 ES:SE:LP:AF:SS:ID 0.00185209:0.00104772:1.1129:0.143202:91149:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123834 ES:SE:LP:AF:SS:ID 0.00179971:0.00105676:1.05274:0.123834:91149:rs28527770
1 753405 rs3115860 C A . PASS AF=0.869892 ES:SE:LP:AF:SS:ID -0.00148111:0.00102972:0.822949:0.869892:91149:rs3115860
1 753425 rs3131970 T C . PASS AF=0.874553 ES:SE:LP:AF:SS:ID -0.00157625:0.00104641:0.879479:0.874553:91149:rs3131970
1 753541 rs2073813 G A . PASS AF=0.129529 ES:SE:LP:AF:SS:ID 0.00141987:0.00103295:0.771433:0.129529:91149:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0358205 ES:SE:LP:AF:SS:ID 0.0010561:0.0018871:0.239784:0.0358205:91149:rs12184325
1 754182 rs3131969 A G . PASS AF=0.869539 ES:SE:LP:AF:SS:ID -0.00141126:0.00102886:0.769125:0.869539:91149:rs3131969
1 754192 rs3131968 A G . PASS AF=0.869616 ES:SE:LP:AF:SS:ID -0.00142748:0.0010293:0.781213:0.869616:91149:rs3131968
1 754334 rs3131967 T C . PASS AF=0.869535 ES:SE:LP:AF:SS:ID -0.00141085:0.00102881:0.768857:0.869535:91149:rs3131967
1 755890 rs3115858 A T . PASS AF=0.86952 ES:SE:LP:AF:SS:ID -0.00141709:0.00102669:0.775946:0.86952:91149:rs3115858
1 756434 rs61768170 G C . PASS AF=0.126911 ES:SE:LP:AF:SS:ID 0.00162933:0.00104807:0.920656:0.126911:91149:rs61768170
1 756604 rs3131962 A G . PASS AF=0.86905 ES:SE:LP:AF:SS:ID -0.00138727:0.00102404:0.755686:0.86905:91149:rs3131962
1 757640 rs3115853 G A . PASS AF=0.868436 ES:SE:LP:AF:SS:ID -0.00142331:0.00102339:0.784376:0.868436:91149:rs3115853
1 757734 rs4951929 C T . PASS AF=0.869199 ES:SE:LP:AF:SS:ID -0.00142055:0.00102496:0.780505:0.869199:91149:rs4951929
1 757936 rs4951862 C A . PASS AF=0.869205 ES:SE:LP:AF:SS:ID -0.00142277:0.00102503:0.782171:0.869205:91149:rs4951862
1 758144 rs3131956 A G . PASS AF=0.869207 ES:SE:LP:AF:SS:ID -0.00141834:0.00102504:0.778698:0.869207:91149:rs3131956
1 758626 rs3131954 C T . PASS AF=0.869687 ES:SE:LP:AF:SS:ID -0.00143906:0.00102778:0.791911:0.869687:91149:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0991787 ES:SE:LP:AF:SS:ID 0.00205207:0.00119608:1.06436:0.0991787:91149:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00649624 ES:SE:LP:AF:SS:ID 0.00119024:0.00461445:0.0988388:0.00649624:91149:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.873682 ES:SE:LP:AF:SS:ID -0.00156316:0.001043:0.873054:0.873682:91149:rs3115851
1 761732 rs2286139 C T . PASS AF=0.863058 ES:SE:LP:AF:SS:ID -0.00175319:0.0010231:1.06247:0.863058:91149:rs2286139
1 761752 rs1057213 C T . PASS AF=0.868472 ES:SE:LP:AF:SS:ID -0.00157738:0.00103325:0.896679:0.868472:91149:rs1057213
1 762273 rs3115849 G A . PASS AF=0.865369 ES:SE:LP:AF:SS:ID -0.00150532:0.00103345:0.837944:0.865369:91149:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0995228 ES:SE:LP:AF:SS:ID 0.001254:0.00123685:0.507731:0.0995228:91149:rs12095200
1 762589 rs3115848 G C . PASS AF=0.870657 ES:SE:LP:AF:SS:ID -0.00152774:0.00104522:0.842111:0.870657:91149:rs3115848
1 762592 rs3131950 C G . PASS AF=0.870657 ES:SE:LP:AF:SS:ID -0.00152773:0.00104522:0.842105:0.870657:91149:rs3131950
1 762601 rs3131949 T C . PASS AF=0.870654 ES:SE:LP:AF:SS:ID -0.00152716:0.00104522:0.841656:0.870654:91149:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871019 ES:SE:LP:AF:SS:ID -0.00157385:0.00104571:0.878397:0.871019:91149:rs3131948
1 764191 rs7515915 T G . PASS AF=0.126515 ES:SE:LP:AF:SS:ID 0.00166103:0.00104687:0.948489:0.126515:91149:rs7515915
1 766007 rs61768174 A C . PASS AF=0.106037 ES:SE:LP:AF:SS:ID 0.00155717:0.00113796:0.766511:0.106037:91149:rs61768174
1 766105 rs2519015 T A . PASS AF=0.85438 ES:SE:LP:AF:SS:ID -0.00194884:0.0010227:1.24636:0.85438:91149:rs2519015
1 768116 rs376645387 A AGTTTT . PASS AF=0.839153 ES:SE:LP:AF:SS:ID -0.000247521:0.00101049:0.0933978:0.839153:91149:rs376645387
1 768253 rs2977608 A C . PASS AF=0.763195 ES:SE:LP:AF:SS:ID -0.00096619:0.000812484:0.630094:0.763195:91149:rs2977608
1 768448 rs12562034 G A . PASS AF=0.105092 ES:SE:LP:AF:SS:ID -0.000211361:0.00111962:0.0704447:0.105092:91149:rs12562034
1 768819 rs12562811 C T . PASS AF=0.00772317 ES:SE:LP:AF:SS:ID 0.00191456:0.00414857:0.190817:0.00772317:91149:rs12562811
1 769138 rs59306077 CAT C . PASS AF=0.129904 ES:SE:LP:AF:SS:ID 0.00162256:0.00103225:0.935598:0.129904:91149:rs762168062
1 769223 rs60320384 C G . PASS AF=0.129636 ES:SE:LP:AF:SS:ID 0.0015635:0.00103089:0.888203:0.129636:91149:rs60320384
1 769963 rs7518545 G A . PASS AF=0.104365 ES:SE:LP:AF:SS:ID -0.000121106:0.00112831:0.0388049:0.104365:91149:rs7518545
1 770181 rs146076599 A G . PASS AF=0.00906976 ES:SE:LP:AF:SS:ID 0.000407566:0.0039669:0.0370778:0.00906976:91149:rs146076599
1 770377 rs112563271 A T . PASS AF=0.00773917 ES:SE:LP:AF:SS:ID 0.00190971:0.00416588:0.189327:0.00773917:91149:rs112563271