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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-SLEEP/ukb-d-SLEEP.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-SLEEP/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 17:18:25 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-d-import/processed/ukb-d-SLEEP/ukb-d-SLEEP.vcf.gz ...
Read summary statistics for 11120382 SNPs.
Dropped 9232 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, 1282109 SNPs remain.
After merging with regression SNP LD, 1282109 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0068 (0.0013)
Lambda GC: 1.043
Mean Chi^2: 1.042
Intercept: 0.9937 (0.006)
Ratio < 0 (usually indicates GC correction).
Analysis finished at Mon Nov 25 17:20:16 2019
Total time elapsed: 1.0m:51.19s
{
"af_correlation": 0.9463,
"inflation_factor": 1.0394,
"mean_EFFECT": 1.9536e-06,
"n": 361194,
"n_snps": 11120382,
"n_clumped_hits": 0,
"n_p_sig": 0,
"n_mono": 0,
"n_ns": 1143948,
"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": 224805,
"n_est": 361696.8138,
"ratio_se_n": 1.0007,
"mean_diff": 0,
"ratio_diff": 162.0917,
"sd_y_est1": 0.0902,
"sd_y_est2": 0.0902,
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": 1282109,
"ldsc_nsnp_merge_regression_ld": 1282109,
"ldsc_observed_scale_h2_beta": 0.0068,
"ldsc_observed_scale_h2_se": 0.0013,
"ldsc_intercept_beta": 0.9937,
"ldsc_intercept_se": 0.006,
"ldsc_lambda_gc": 1.043,
"ldsc_mean_chisq": 1.042,
"ldsc_ratio": -0.15
}
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 | 11111744 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 100 | 0 | 51381 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 342 | 0 | 31424 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 9.074530e+00 | 6.181780e+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 | 7.882981e+07 | 5.601877e+07 | 3.02000e+02 | 3.260704e+07 | 6.981719e+07 | 1.147456e+08 | 2.492309e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.000000e-06 | 6.730000e-04 | -6.82020e-03 | -2.678000e-04 | -1.800000e-06 | 2.626000e-04 | 8.096400e-03 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 5.390000e-04 | 3.969000e-04 | 1.74600e-04 | 2.392000e-04 | 3.528000e-04 | 7.238000e-04 | 2.392100e-03 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.937302e-01 | 2.900789e-01 | 1.00000e-07 | 2.408951e-01 | 4.916635e-01 | 7.447646e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.937297e-01 | 2.900791e-01 | 1.00000e-07 | 2.408947e-01 | 4.916635e-01 | 7.447644e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.307024e-01 | 2.615674e-01 | 4.23580e-03 | 2.304950e-02 | 1.152220e-01 | 3.691100e-01 | 9.957640e-01 | ▇▂▂▁▁ |
numeric | AF_reference | 224805 | 0.9797844 | NA | NA | NA | NA | NA | 2.310109e-01 | 2.526940e-01 | 0.00000e+00 | 2.136580e-02 | 1.329870e-01 | 3.678120e-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 | 0.0002267 | 0.0003719 | 0.5421781 | 0.5421770 | 0.1106400 | 0.1894970 | 361194 |
1 | 693731 | rs12238997 | A | G | 0.0004616 | 0.0003514 | 0.1889779 | 0.1889769 | 0.1158300 | 0.1417730 | 361194 |
1 | 707522 | rs371890604 | G | C | 0.0002672 | 0.0003950 | 0.4987604 | 0.4987616 | 0.0973034 | 0.1293930 | 361194 |
1 | 717587 | rs144155419 | G | A | 0.0012898 | 0.0009427 | 0.1712340 | 0.1712326 | 0.0156880 | 0.0045926 | 361194 |
1 | 730087 | rs148120343 | T | C | 0.0002441 | 0.0004895 | 0.6180207 | 0.6180204 | 0.0564602 | 0.0127796 | 361194 |
1 | 731718 | rs142557973 | T | C | 0.0004371 | 0.0003333 | 0.1896470 | 0.1896465 | 0.1217380 | 0.1543530 | 361194 |
1 | 732032 | rs61770163 | A | C | 0.0003034 | 0.0003555 | 0.3933163 | 0.3933155 | 0.1211710 | 0.1555510 | 361194 |
1 | 734349 | rs141242758 | T | C | 0.0004387 | 0.0003334 | 0.1882912 | 0.1882902 | 0.1209650 | 0.1525560 | 361194 |
1 | 740284 | rs61770167 | C | T | 0.0001033 | 0.0015255 | 0.9460200 | 0.9460196 | 0.0057851 | 0.0023962 | 361194 |
1 | 749963 | rs529266287 | T | TAA | -0.0002569 | 0.0003287 | 0.4344082 | 0.4344085 | 0.8697420 | 0.7641770 | 361194 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
23 | 154923311 | rs141127553 | C | T | 0.0006040 | 0.0003850 | 0.1166769 | 0.1166770 | 0.0561667 | 0.0309934 | 361194 |
23 | 154923374 | rs111332691 | T | A | -0.0001454 | 0.0004231 | 0.7310667 | 0.7310650 | 0.0447862 | 0.0116556 | 361194 |
23 | 154925045 | rs509981 | C | T | -0.0002849 | 0.0002036 | 0.1617160 | 0.1617143 | 0.2456060 | 0.3634440 | 361194 |
23 | 154925895 | rs538470 | C | T | -0.0002677 | 0.0002083 | 0.1986328 | 0.1986336 | 0.2419150 | 0.3634440 | 361194 |
23 | 154927581 | rs644138 | G | A | -0.0000928 | 0.0001915 | 0.6280294 | 0.6280298 | 0.3021620 | 0.4635760 | 361194 |
23 | 154929412 | rs557132 | C | T | -0.0002809 | 0.0002036 | 0.1678070 | 0.1678069 | 0.2454590 | 0.3568210 | 361194 |
23 | 154929637 | rs35185538 | CT | C | -0.0002771 | 0.0002125 | 0.1923021 | 0.1923012 | 0.2296970 | 0.3011920 | 361194 |
23 | 154929952 | rs4012982 | CAA | C | -0.0002952 | 0.0002142 | 0.1680870 | 0.1680863 | 0.2394250 | 0.3165560 | 361194 |
23 | 154930230 | rs781880 | A | G | -0.0002794 | 0.0002036 | 0.1700032 | 0.1700025 | 0.2458690 | 0.3618540 | 361194 |
23 | 154930487 | rs781879 | T | A | 0.0001619 | 0.0006985 | 0.8166790 | 0.8166792 | 0.0195623 | 0.1263580 | 361194 |
1 692794 rs530212009 CA C . PASS AF=0.11064 ES:SE:LP:AF:SS:ID 0.000226676:0.00037189:0.265858:0.11064:361194:1_692794_CA_C
1 693731 rs12238997 A G . PASS AF=0.11583 ES:SE:LP:AF:SS:ID 0.00046159:0.00035139:0.723589:0.11583:361194:rs12238997
1 707522 rs371890604 G C . PASS AF=0.0973034 ES:SE:LP:AF:SS:ID 0.000267218:0.000395036:0.302108:0.0973034:361194:rs371890604
1 717587 rs144155419 G A . PASS AF=0.015688 ES:SE:LP:AF:SS:ID 0.00128979:0.000942654:0.76641:0.015688:361194:rs144155419
1 730087 rs148120343 T C . PASS AF=0.0564602 ES:SE:LP:AF:SS:ID 0.00024411:0.000489534:0.208997:0.0564602:361194:rs148120343
1 731718 rs58276399 T C . PASS AF=0.121738 ES:SE:LP:AF:SS:ID 0.000437111:0.000333259:0.722054:0.121738:361194:rs58276399
1 732032 rs61770163 A C . PASS AF=0.121171 ES:SE:LP:AF:SS:ID 0.00030345:0.000355486:0.405258:0.121171:361194:rs61770163
1 734349 rs141242758 T C . PASS AF=0.120965 ES:SE:LP:AF:SS:ID 0.000438689:0.000333438:0.72517:0.120965:361194:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00578512 ES:SE:LP:AF:SS:ID 0.000103285:0.00152549:0.0240997:0.00578512:361194:rs61770167
1 749963 rs529266287 T TAA . PASS AF=0.869742 ES:SE:LP:AF:SS:ID -0.000256949:0.000328718:0.362102:0.869742:361194:rs529266287
1 751343 rs28544273 T A . PASS AF=0.122916 ES:SE:LP:AF:SS:ID 0.000266808:0.000325552:0.384609:0.122916:361194:rs28544273
1 751488 rs200141114 G GA . PASS AF=0.142712 ES:SE:LP:AF:SS:ID 0.000264389:0.00032179:0.385848:0.142712:361194:rs200141114
1 751756 rs28527770 T C . PASS AF=0.123031 ES:SE:LP:AF:SS:ID 0.000264495:0.000325099:0.381029:0.123031:361194:rs28527770
1 753405 rs3115860 C A . PASS AF=0.87089 ES:SE:LP:AF:SS:ID -0.000278473:0.000316798:0.420915:0.87089:361194:rs3115860
1 753425 rs3131970 T C . PASS AF=0.875472 ES:SE:LP:AF:SS:ID -0.000251649:0.000322048:0.361944:0.875472:361194:rs3131970
1 753541 rs2073813 G A . PASS AF=0.128631 ES:SE:LP:AF:SS:ID 0.000305798:0.000317592:0.474157:0.128631:361194:rs2073813
1 754105 rs12184325 C T . PASS AF=0.0363613 ES:SE:LP:AF:SS:ID 0.00129293:0.000576182:1.60493:0.0363613:361194:rs12184325
1 754182 rs3131969 A G . PASS AF=0.870484 ES:SE:LP:AF:SS:ID -0.00028229:0.000316469:0.428999:0.870484:361194:rs3131969
1 754192 rs3131968 A G . PASS AF=0.870589 ES:SE:LP:AF:SS:ID -0.000253992:0.000316613:0.374246:0.870589:361194:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870481 ES:SE:LP:AF:SS:ID -0.00028273:0.000316457:0.429887:0.870481:361194:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00504367 ES:SE:LP:AF:SS:ID 0.000482003:0.00162464:0.11537:0.00504367:361194:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00501064 ES:SE:LP:AF:SS:ID 0.000493377:0.00162899:0.118053:0.00501064:361194:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00558665 ES:SE:LP:AF:SS:ID -0.000167672:0.0015735:0.0385134:0.00558665:361194:rs184270342
1 755890 rs3115858 A T . PASS AF=0.870563 ES:SE:LP:AF:SS:ID -0.000305192:0.0003159:0.476263:0.870563:361194:rs3115858
1 756434 rs61768170 G C . PASS AF=0.125985 ES:SE:LP:AF:SS:ID 0.000332385:0.000322334:0.519338:0.125985:361194:rs61768170
1 756604 rs3131962 A G . PASS AF=0.870127 ES:SE:LP:AF:SS:ID -0.000317381:0.00031514:0.503235:0.870127:361194:rs3131962
1 757640 rs3115853 G A . PASS AF=0.869414 ES:SE:LP:AF:SS:ID -0.000344279:0.000314852:0.561945:0.869414:361194:rs3115853
1 757734 rs4951929 C T . PASS AF=0.870281 ES:SE:LP:AF:SS:ID -0.000315952:0.000315411:0.499652:0.870281:361194:rs4951929
1 757936 rs4951862 C A . PASS AF=0.870287 ES:SE:LP:AF:SS:ID -0.000316065:0.000315433:0.499843:0.870287:361194:rs4951862
1 758144 rs3131956 A G . PASS AF=0.870295 ES:SE:LP:AF:SS:ID -0.000316583:0.000315443:0.500911:0.870295:361194:rs3131956
1 758626 rs3131954 C T . PASS AF=0.870739 ES:SE:LP:AF:SS:ID -0.000297465:0.000316246:0.459789:0.870739:361194:rs3131954
1 759293 rs10157329 T A . PASS AF=0.0988442 ES:SE:LP:AF:SS:ID 0.00016026:0.000367498:0.178634:0.0988442:361194:rs10157329
1 759600 rs545998451 AGT A . PASS AF=0.00647588 ES:SE:LP:AF:SS:ID -0.000425848:0.0014215:0.116622:0.00647588:361194:1_759600_AGT_A
1 759837 rs3115851 T A . PASS AF=0.874635 ES:SE:LP:AF:SS:ID -0.00026985:0.00032096:0.397416:0.874635:361194:rs3115851
1 761732 rs2286139 C T . PASS AF=0.864027 ES:SE:LP:AF:SS:ID -0.000387747:0.000314748:0.661589:0.864027:361194:rs2286139
1 761752 rs1057213 C T . PASS AF=0.869425 ES:SE:LP:AF:SS:ID -0.000281368:0.000317804:0.424848:0.869425:361194:rs1057213
1 762273 rs3115849 G A . PASS AF=0.866371 ES:SE:LP:AF:SS:ID -0.000233157:0.000317869:0.334181:0.866371:361194:rs3115849
1 762485 rs12095200 C A . PASS AF=0.0987831 ES:SE:LP:AF:SS:ID 4.47173e-05:0.000380549:0.0426523:0.0987831:361194:rs12095200
1 762589 rs3115848 G C . PASS AF=0.871556 ES:SE:LP:AF:SS:ID -0.000239268:0.00032149:0.340343:0.871556:361194:rs3115848
1 762592 rs3131950 C G . PASS AF=0.871556 ES:SE:LP:AF:SS:ID -0.000239264:0.00032149:0.340336:0.871556:361194:rs3131950
1 762601 rs3131949 T C . PASS AF=0.871555 ES:SE:LP:AF:SS:ID -0.000239559:0.000321496:0.340855:0.871555:361194:rs3131949
1 762632 rs3131948 T A . PASS AF=0.871929 ES:SE:LP:AF:SS:ID -0.000238444:0.00032168:0.338619:0.871929:361194:rs3131948
1 764191 rs7515915 T G . PASS AF=0.125562 ES:SE:LP:AF:SS:ID 0.000301675:0.000321933:0.457521:0.125562:361194:rs7515915
1 766007 rs61768174 A C . PASS AF=0.105428 ES:SE:LP:AF:SS:ID 0.000174348:0.000350469:0.20841:0.105428:361194:rs61768174
1 766105 rs2519015 T A . PASS AF=0.855376 ES:SE:LP:AF:SS:ID -0.000255285:0.000314631:0.379709:0.855376:361194:rs2519015
1 768116 rs376645387 A AGTTTT . PASS AF=0.838358 ES:SE:LP:AF:SS:ID -0.000123108:0.000309968:0.160367:0.838358:361194:rs376645387
1 768253 rs2977608 A C . PASS AF=0.763351 ES:SE:LP:AF:SS:ID -0.000235493:0.000249466:0.461961:0.763351:361194:rs2977608
1 768448 rs12562034 G A . PASS AF=0.105921 ES:SE:LP:AF:SS:ID 0.000102398:0.000343703:0.115907:0.105921:361194:rs12562034
1 768819 rs12562811 C T . PASS AF=0.00768395 ES:SE:LP:AF:SS:ID -0.000460152:0.00127701:0.143515:0.00768395:361194:rs12562811
1 769138 rs59306077 CAT C . PASS AF=0.128938 ES:SE:LP:AF:SS:ID 0.000299485:0.00031743:0.461625:0.128938:361194:rs762168062