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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-I9_ARTOTH/ukb-d-I9_ARTOTH.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-I9_ARTOTH/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 16:52:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-I9_ARTOTH/ukb-d-I9_ARTOTH.vcf.gz ...
Read summary statistics for 9426752 SNPs.
Dropped 6947 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, 1271973 SNPs remain.
After merging with regression SNP LD, 1271973 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.001 (0.0012)
Lambda GC: 1.0127
Mean Chi^2: 1.0081
Intercept: 1.0009 (0.0061)
Ratio: 0.1095 (0.7487)
Analysis finished at Mon Nov 25 16:53:48 2019
Total time elapsed: 1.0m:35.22s
{
"af_correlation": 0.9384,
"inflation_factor": 1.0157,
"mean_EFFECT": 1.02e-06,
"n": 361194,
"n_snps": 9426752,
"n_clumped_hits": 1,
"n_p_sig": 3,
"n_mono": 0,
"n_ns": 1045668,
"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": 189013,
"n_est": 361074.7926,
"ratio_se_n": 0.9998,
"mean_diff": 0,
"ratio_diff": 37.6007,
"sd_y_est1": 0.0548,
"sd_y_est2": 0.0548,
"r2_sum1": 2.7258e-07,
"r2_sum2": 0.0001,
"r2_sum3": 0.0001,
"r2_sum4": 0.0001,
"ldsc_nsnp_merge_refpanel_ld": 1271973,
"ldsc_nsnp_merge_regression_ld": 1271973,
"ldsc_observed_scale_h2_beta": 0.001,
"ldsc_observed_scale_h2_se": 0.0012,
"ldsc_intercept_beta": 1.0009,
"ldsc_intercept_se": 0.0061,
"ldsc_lambda_gc": 1.0127,
"ldsc_mean_chisq": 1.0081,
"ldsc_ratio": 0.1111
}
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 | 1.0000000 | 3 | 94 | 0 | 9420341 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 98 | 0 | 46134 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 29321 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.080832e+00 | 6.173824e+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 | 7.869785e+07 | 5.611352e+07 | 3.02000e+02 | 3.241312e+07 | 6.956491e+07 | 1.147155e+08 | 2.492297e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.000000e-06 | 2.762000e-04 | -2.22480e-03 | -1.374000e-04 | -7.000000e-07 | 1.359000e-04 | 3.315200e-03 | ▁▇▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.413000e-04 | 1.299000e-04 | 1.06100e-04 | 1.406000e-04 | 1.844000e-04 | 3.059000e-04 | 7.608000e-04 | ▇▂▂▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.975307e-01 | 2.888243e-01 | 0.00000e+00 | 2.471599e-01 | 4.966438e-01 | 7.475048e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.975303e-01 | 2.888246e-01 | 0.00000e+00 | 2.471596e-01 | 4.966437e-01 | 7.475049e-01 | 9.999999e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.683653e-01 | 2.626456e-01 | 1.15420e-02 | 4.966420e-02 | 1.690940e-01 | 4.262432e-01 | 9.884580e-01 | ▇▂▂▁▁ |
numeric | AF_reference | 189013 | 0.9799493 | NA | NA | NA | NA | NA | 2.676773e-01 | 2.534427e-01 | 0.00000e+00 | 5.710860e-02 | 1.835060e-01 | 4.209270e-01 | 1.000000e+00 | ▇▃▂▂▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 3.611940e+05 | 0.000000e+00 | 3.61194e+05 | 3.611940e+05 | 3.611940e+05 | 3.611940e+05 | 3.611940e+05 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 692794 | rs530212009 | CA | C | -0.0002718 | 0.0002261 | 0.2292910 | 0.2292905 | 0.1106400 | 0.1894970 | 361194 |
1 | 693731 | rs12238997 | A | G | -0.0002664 | 0.0002136 | 0.2123851 | 0.2123857 | 0.1158300 | 0.1417730 | 361194 |
1 | 707522 | rs371890604 | G | C | -0.0004006 | 0.0002402 | 0.0952796 | 0.0952801 | 0.0973034 | 0.1293930 | 361194 |
1 | 717587 | rs144155419 | G | A | 0.0003225 | 0.0005731 | 0.5736064 | 0.5736064 | 0.0156880 | 0.0045926 | 361194 |
1 | 730087 | rs148120343 | T | C | -0.0002229 | 0.0002976 | 0.4539071 | 0.4539056 | 0.0564602 | 0.0127796 | 361194 |
1 | 731718 | rs142557973 | T | C | -0.0001990 | 0.0002026 | 0.3260821 | 0.3260808 | 0.1217380 | 0.1543530 | 361194 |
1 | 732032 | rs61770163 | A | C | -0.0002670 | 0.0002161 | 0.2166871 | 0.2166851 | 0.1211710 | 0.1555510 | 361194 |
1 | 734349 | rs141242758 | T | C | -0.0001944 | 0.0002027 | 0.3375173 | 0.3375162 | 0.1209650 | 0.1525560 | 361194 |
1 | 749963 | rs529266287 | T | TAA | 0.0002492 | 0.0001998 | 0.2123240 | 0.2123232 | 0.8697420 | 0.7641770 | 361194 |
1 | 751343 | rs28544273 | T | A | -0.0002495 | 0.0001979 | 0.2074541 | 0.2074524 | 0.1229160 | 0.2426120 | 361194 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0002468 | 0.0002341 | 0.2917259 | 0.2917251 | 0.0561667 | 0.0309934 | 361194 |
23 | 154923374 | rs111332691 | T | A | 0.0001136 | 0.0002572 | 0.6587536 | 0.6587545 | 0.0447862 | 0.0116556 | 361194 |
23 | 154925045 | rs509981 | C | T | 0.0000021 | 0.0001238 | 0.9867570 | 0.9867575 | 0.2456060 | 0.3634440 | 361194 |
23 | 154925895 | rs538470 | C | T | -0.0000131 | 0.0001266 | 0.9176480 | 0.9176479 | 0.2419150 | 0.3634440 | 361194 |
23 | 154927581 | rs644138 | G | A | 0.0000640 | 0.0001164 | 0.5824062 | 0.5824042 | 0.3021620 | 0.4635760 | 361194 |
23 | 154929412 | rs557132 | C | T | 0.0000038 | 0.0001238 | 0.9756110 | 0.9756110 | 0.2454590 | 0.3568210 | 361194 |
23 | 154929637 | rs35185538 | CT | C | 0.0001315 | 0.0001292 | 0.3089342 | 0.3089348 | 0.2296970 | 0.3011920 | 361194 |
23 | 154929952 | rs4012982 | CAA | C | 0.0000121 | 0.0001302 | 0.9262410 | 0.9262409 | 0.2394250 | 0.3165560 | 361194 |
23 | 154930230 | rs781880 | A | G | 0.0000015 | 0.0001238 | 0.9905400 | 0.9905402 | 0.2458690 | 0.3618540 | 361194 |
23 | 154930487 | rs781879 | T | A | 0.0005340 | 0.0004247 | 0.2085432 | 0.2085419 | 0.0195623 | 0.1263580 | 361194 |
1 692794 rs530212009 CA C . PASS AF=0.11064 ES:SE:LP:AF:SS:ID -0.000271798:0.000226086:0.639613:0.11064:361194:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.11583 ES:SE:LP:AF:SS:ID -0.000266396:0.000213624:0.672876:0.11583:361194:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0973034 ES:SE:LP:AF:SS:ID -0.000400625:0.000240157:1.021:0.0973034:361194:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015688 ES:SE:LP:AF:SS:ID 0.000322498:0.000573077:0.241386:0.015688:361194:rs144155419
1 730087 rs148120343 T C . PASS AF=0.0564602 ES:SE:LP:AF:SS:ID -0.000222883:0.000297606:0.343033:0.0564602:361194:rs148120343
1 731718 rs58276399 T C . PASS AF=0.121738 ES:SE:LP:AF:SS:ID -0.000198962:0.000202601:0.486673:0.121738:361194:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121171 ES:SE:LP:AF:SS:ID -0.000266984:0.000216113:0.664167:0.121171:361194:rs61770163
1 734349 rs141242758 T C . PASS AF=0.120965 ES:SE:LP:AF:SS:ID -0.000194416:0.00020271:0.471704:0.120965:361194:rs141242758
1 749963 rs529266287 T TAA . PASS AF=0.869742 ES:SE:LP:AF:SS:ID 0.000249241:0.00019984:0.673001:0.869742:361194:rs529266287
1 751343 rs28544273 T A . PASS AF=0.122916 ES:SE:LP:AF:SS:ID -0.000249492:0.000197915:0.683078:0.122916:361194:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.142712 ES:SE:LP:AF:SS:ID -0.000244735:0.000195629:0.675864:0.142712:361194:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123031 ES:SE:LP:AF:SS:ID -0.000251072:0.00019764:0.690453:0.123031:361194:rs28527770
1 753405 rs3115860 C A . PASS AF=0.87089 ES:SE:LP:AF:SS:ID 0.000186755:0.000192594:0.478594:0.87089:361194:rs3115860
1 753425 rs3131970 T C . PASS AF=0.875472 ES:SE:LP:AF:SS:ID 0.000268355:0.000195785:0.768324:0.875472:361194:rs3131970
1 753541 rs2073813 G A . PASS AF=0.128631 ES:SE:LP:AF:SS:ID -0.000157362:0.000193077:0.381888:0.128631:361194:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0363613 ES:SE:LP:AF:SS:ID 1.62517e-05:0.000350286:0.016376:0.0363613:361194:rs12184325
1 754182 rs3131969 A G . PASS AF=0.870484 ES:SE:LP:AF:SS:ID 0.000176343:0.000192393:0.444464:0.870484:361194:rs3131969
1 754192 rs3131968 A G . PASS AF=0.870589 ES:SE:LP:AF:SS:ID 0.000174349:0.000192481:0.437656:0.870589:361194:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870481 ES:SE:LP:AF:SS:ID 0.000164394:0.000192386:0.405796:0.870481:361194:rs3131967
1 755890 rs3115858 A T . PASS AF=0.870563 ES:SE:LP:AF:SS:ID 0.000194609:0.000192048:0.507378:0.870563:361194:rs3115858
1 756434 rs61768170 G C . PASS AF=0.125985 ES:SE:LP:AF:SS:ID -0.000190968:0.000195959:0.481757:0.125985:361194:rs61768170
1 756604 rs3131962 A G . PASS AF=0.870127 ES:SE:LP:AF:SS:ID 0.000181917:0.000191585:0.46553:0.870127:361194:rs3131962
1 757640 rs3115853 G A . PASS AF=0.869414 ES:SE:LP:AF:SS:ID 0.000192624:0.000191411:0.502721:0.869414:361194:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870281 ES:SE:LP:AF:SS:ID 0.000198366:0.00019175:0.521575:0.870281:361194:rs4951929
1 757936 rs4951862 C A . PASS AF=0.870287 ES:SE:LP:AF:SS:ID 0.000198814:0.000191764:0.523099:0.870287:361194:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870295 ES:SE:LP:AF:SS:ID 0.000198345:0.00019177:0.521429:0.870295:361194:rs3131956
1 758626 rs3131954 C T . PASS AF=0.870739 ES:SE:LP:AF:SS:ID 0.000198194:0.000192258:0.51913:0.870739:361194:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0988442 ES:SE:LP:AF:SS:ID -0.000350599:0.000223415:0.933354:0.0988442:361194:rs10157329
1 759837 rs3115851 T A . PASS AF=0.874635 ES:SE:LP:AF:SS:ID 0.000267713:0.000195123:0.7694:0.874635:361194:rs3115851
1 761732 rs2286139 C T . PASS AF=0.864027 ES:SE:LP:AF:SS:ID 0.000219853:0.000191348:0.601073:0.864027:361194:rs2286139
1 761752 rs1057213 C T . PASS AF=0.869425 ES:SE:LP:AF:SS:ID 0.000222757:0.000193205:0.603921:0.869425:361194:rs1057213
1 762273 rs3115849 G A . PASS AF=0.866371 ES:SE:LP:AF:SS:ID 0.000216769:0.000193245:0.581738:0.866371:361194:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0987831 ES:SE:LP:AF:SS:ID -0.000419617:0.000231349:1.15669:0.0987831:361194:rs12095200
1 762589 rs3115848 G C . PASS AF=0.871556 ES:SE:LP:AF:SS:ID 0.000252846:0.000195446:0.708243:0.871556:361194:rs3115848
1 762592 rs3131950 C G . PASS AF=0.871556 ES:SE:LP:AF:SS:ID 0.000252847:0.000195446:0.708247:0.871556:361194:rs3131950
1 762601 rs3131949 T C . PASS AF=0.871555 ES:SE:LP:AF:SS:ID 0.00025286:0.00019545:0.708278:0.871555:361194:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871929 ES:SE:LP:AF:SS:ID 0.000270592:0.000195561:0.77869:0.871929:361194:rs3131948
1 764191 rs7515915 T G . PASS AF=0.125562 ES:SE:LP:AF:SS:ID -0.00025882:0.000195715:0.730426:0.125562:361194:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105428 ES:SE:LP:AF:SS:ID -0.000291336:0.000213063:0.765711:0.105428:361194:rs61768174
1 766105 rs2519015 T A . PASS AF=0.855376 ES:SE:LP:AF:SS:ID 0.000217608:0.000191276:0.593016:0.855376:361194:rs2519015
1 768116 rs376645387 A AGTTTT . PASS AF=0.838358 ES:SE:LP:AF:SS:ID -5.62554e-07:0.000188441:0.00103572:0.838358:361194:rs376645387
1 768253 rs2977608 A C . PASS AF=0.763351 ES:SE:LP:AF:SS:ID 0.000180906:0.00015166:0.632773:0.763351:361194:rs2977608
1 768448 rs12562034 G A . PASS AF=0.105921 ES:SE:LP:AF:SS:ID -5.51743e-05:0.00020895:0.101419:0.105921:361194:rs12562034
1 769138 rs59306077 CAT C . PASS AF=0.128938 ES:SE:LP:AF:SS:ID -0.000206594:0.000192978:0.546119:0.128938:361194:rs762168062
1 769223 rs60320384 C G . PASS AF=0.128608 ES:SE:LP:AF:SS:ID -0.000213884:0.000192799:0.573042:0.128608:361194:rs60320384
1 769963 rs7518545 G A . PASS AF=0.105213 ES:SE:LP:AF:SS:ID -5.65279e-05:0.000210529:0.103302:0.105213:361194:rs7518545
1 770886 rs371458725 G A . PASS AF=0.104268 ES:SE:LP:AF:SS:ID -3.91419e-05:0.000212211:0.0687141:0.104268:361194:rs371458725
1 771410 rs2519006 C T . PASS AF=0.830106 ES:SE:LP:AF:SS:ID 0.000227988:0.00018786:0.648011:0.830106:361194:rs2519006
1 771823 rs2977605 T C . PASS AF=0.87012 ES:SE:LP:AF:SS:ID 0.000218178:0.000191936:0.592344:0.87012:361194:rs2977605
1 771967 rs59066358 G A . PASS AF=0.128668 ES:SE:LP:AF:SS:ID -0.000214063:0.000192709:0.574055:0.128668:361194:rs59066358