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"FORMAT.2": "<ID=EZ,Number=A,Type=Float,Description=\"Z-score provided if it was used to derive the EFFECT and SE fields\">",
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"META.4": "<ID=TotalControls,Number=1,Type=Integer,Description=\"Total number of controls in the association study\">",
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"META.7": "<ID=VariantsNotRead,Number=1,Type=Integer,Description=\"Number of variants that could not be read\">",
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"file_date": "2019-10-26T21:46:54.959346",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006948/EBI-a-GCST006948_data.json --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/hg38/hg38.fa; 1.1.1",
"reference": "file:/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/b37/human_g1k_v37.fasta",
"bcftools_annotateVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
"bcftools_annotateCommand": "annotate -a /mnt/storage/home/gh13047/mr-eve/vcf-reference-datasets/dbsnp/dbsnp.v153.b37.vcf.gz -c ID -o /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006948/EBI-a-GCST006948.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006948/EBI-a-GCST006948_data.vcf.gz; Date=Sat Oct 26 22:06:22 2019",
"bcftools_viewVersion": "1.9-74-g6af271c+htslib-1.9-64-g226b4a8",
"bcftools_viewCommand": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ebi-a-GCST006948/ebi-a-GCST006948.vcf.gz; Date=Sat May 9 18:26:44 2020"
}
*********************************************************************
* 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/ebi_gwas_import/processed/EBI-a-GCST006948/EBI-a-GCST006948.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/ebi_gwas_import/processed/EBI-a-GCST006948/ldsc.txt \
--snplist /data/ref/snplist.gz \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Sat Oct 26 22:32:13 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST006948/EBI-a-GCST006948.vcf.gz ...
and extracting SNPs specified in /data/ref/snplist.gz ...
Traceback (most recent call last):
File "./ldsc/ldsc.py", line 647, in <module>
sumstats.estimate_h2(args, log)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
args, log, args.h2)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 246, in _read_ld_sumstats
sumstats = _read_sumstats(args, log, fh, alleles=alleles, dropna=dropna)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/sumstats.py", line 165, in _read_sumstats
sumstats = ps.sumstats(fh, alleles=alleles, dropna=dropna, slh=args.snplist)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 85, in sumstats
x = read_vcf(fh, alleles, slh)
File "/mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/igd-hpc-pipeline/resources/gwas_processing/ldsc/ldscore/parse.py", line 161, in read_vcf
with gzip.open(slh) as f:
File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 34, in open
return GzipFile(filename, mode, compresslevel)
File "/mnt/storage/home/gh13047/mr-eve/conda/ldsc/lib/python2.7/gzip.py", line 94, in __init__
fileobj = self.myfileobj = __builtin__.open(filename, mode or 'rb')
IOError: [Errno 2] No such file or directory: '/data/ref/snplist.gz'
Analysis finished at Sat Oct 26 22:33:26 2019
Total time elapsed: 1.0m:12.13s
{
"af_correlation": 0.9589,
"inflation_factor": 1.2144,
"mean_EFFECT": -0.0002,
"n": "-Inf",
"n_snps": 10824842,
"n_clumped_hits": 35,
"n_p_sig": 4409,
"n_mono": 0,
"n_ns": 0,
"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": 429065,
"n_est": "NA",
"ratio_se_n": "NA",
"mean_diff": "NaN",
"ratio_diff": "NaN",
"sd_y_est1": "NaN",
"sd_y_est2": "NA",
"r2_sum1": 0,
"r2_sum2": 0,
"r2_sum3": 0,
"r2_sum4": 0,
"ldsc_nsnp_merge_refpanel_ld": "NA",
"ldsc_nsnp_merge_regression_ld": "NA",
"ldsc_observed_scale_h2_beta": "NA",
"ldsc_observed_scale_h2_se": "NA",
"ldsc_intercept_beta": "NA",
"ldsc_intercept_se": "NA",
"ldsc_lambda_gc": "NA",
"ldsc_mean_chisq": "NA",
"ldsc_ratio": "NA"
}
name | value |
---|---|
af_correlation | FALSE |
inflation_factor | TRUE |
n | TRUE |
is_snpid_non_unique | FALSE |
mean_EFFECT_nonfinite | FALSE |
mean_EFFECT_05 | FALSE |
mean_EFFECT_01 | FALSE |
mean_chisq | TRUE |
n_p_sig | TRUE |
miss_EFFECT | FALSE |
miss_SE | FALSE |
miss_PVAL | FALSE |
ldsc_ratio | TRUE |
ldsc_intercept_beta | TRUE |
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 | logical.mean | logical.count | numeric.mean | numeric.sd | numeric.p0 | numeric.p25 | numeric.p50 | numeric.p75 | numeric.p100 | numeric.hist |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
character | ID | 0 | 1.0000000 | 3 | 47 | 0 | 10809170 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
logical | N | 10809171 | 0.0000000 | NA | NA | NA | NA | NA | NaN | : | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 8.526279e+00 | 5.701029e+00 | 1.0000000 | 4.000000e+00 | 7.000000e+00 | 1.200000e+01 | 2.200000e+01 | ▇▅▃▂▂ |
numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.942146e+07 | 5.593369e+07 | 828.0000000 | 3.358304e+07 | 7.035975e+07 | 1.147892e+08 | 2.492251e+08 | ▇▇▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.930000e-04 | 2.006560e-02 | -0.3400590 | -4.549100e-03 | -7.520000e-05 | 4.277800e-03 | 4.932320e-01 | ▁▂▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.245330e-02 | 1.557080e-02 | 0.0023165 | 2.894000e-03 | 5.667100e-03 | 1.602390e-02 | 1.364240e-01 | ▇▁▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.682416e-01 | 2.975357e-01 | 0.0000000 | 2.029000e-01 | 4.572998e-01 | 7.260993e-01 | 9.996000e-01 | ▇▆▆▆▆ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.682415e-01 | 2.975357e-01 | 0.0000000 | 2.030177e-01 | 4.574811e-01 | 7.263383e-01 | 9.992021e-01 | ▇▆▆▆▆ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.801837e-01 | 2.533980e-01 | 0.0000894 | 5.471200e-03 | 4.879420e-02 | 2.651680e-01 | 9.998900e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 429065 | 0.9603055 | NA | NA | NA | NA | NA | NA | NA | 1.908462e-01 | 2.453527e-01 | 0.0000000 | 1.337860e-02 | 7.488020e-02 | 2.825480e-01 | 1.000000e+00 | ▇▂▁▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 715265 | rs12184267 | C | T | 0.0043705 | 0.0062081 | 0.4812004 | 0.4814331 | 0.0366377 | 0.0275559 | NA |
1 | 715367 | rs12184277 | A | G | 0.0039396 | 0.0061943 | 0.5244994 | 0.5247769 | 0.0367695 | 0.0281550 | NA |
1 | 717485 | rs12184279 | C | A | 0.0049441 | 0.0062191 | 0.4266001 | 0.4266138 | 0.0364631 | NA | NA |
1 | 720381 | rs116801199 | G | T | 0.0040412 | 0.0061604 | 0.5116005 | 0.5118240 | 0.0371104 | 0.0359425 | NA |
1 | 721290 | rs12565286 | G | C | 0.0049602 | 0.0061541 | 0.4201003 | 0.4202429 | 0.0372080 | 0.0371406 | NA |
1 | 723891 | rs2977670 | G | C | -0.0015848 | 0.0053722 | 0.7683994 | 0.7679935 | 0.9503520 | 0.7799520 | NA |
1 | 726794 | rs28454925 | C | G | 0.0033101 | 0.0061986 | 0.5935004 | 0.5933414 | 0.0366130 | 0.0279553 | NA |
1 | 729632 | rs116720794 | C | T | 0.0039323 | 0.0061731 | 0.5242000 | 0.5241246 | 0.0368931 | 0.0099840 | NA |
1 | 729679 | rs4951859 | C | G | 0.0018049 | 0.0031555 | 0.5675995 | 0.5673220 | 0.8316140 | 0.6399760 | NA |
1 | 752478 | rs146277091 | G | A | 0.0049858 | 0.0061705 | 0.4193001 | 0.4190902 | 0.0367696 | 0.0277556 | NA |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51219704 | rs147475742 | G | A | 0.0028562 | 0.0057934 | 0.6219994 | 0.6220121 | 0.0427541 | 0.0473243 | NA |
22 | 51219766 | rs182321900 | C | T | -0.0018876 | 0.0202964 | 0.9255000 | 0.9259038 | 0.0032748 | NA | NA |
22 | 51220025 | rs148808236 | G | A | -0.0113404 | 0.0277950 | 0.6830005 | 0.6832726 | 0.0017399 | 0.0215655 | NA |
22 | 51220146 | rs868950473 | C | T | 0.0067443 | 0.0201926 | 0.7381999 | 0.7383799 | 0.0033097 | NA | NA |
22 | 51221731 | rs115055839 | T | C | 0.0024375 | 0.0044480 | 0.5837999 | 0.5836913 | 0.0732027 | 0.0625000 | NA |
22 | 51222100 | rs114553188 | G | T | 0.0137923 | 0.0050466 | 0.0062690 | 0.0062759 | 0.0568181 | 0.0880591 | NA |
22 | 51223637 | rs375798137 | G | A | 0.0142053 | 0.0050879 | 0.0052330 | 0.0052384 | 0.0558736 | 0.0788738 | NA |
22 | 51224208 | rs116656403 | G | A | -0.0031592 | 0.0277121 | 0.9089000 | 0.9092378 | 0.0017501 | 0.0209665 | NA |
22 | 51224267 | rs138354270 | G | A | 0.0184974 | 0.0278156 | 0.5063001 | 0.5060499 | 0.0017376 | 0.0209665 | NA |
22 | 51229805 | rs9616985 | T | C | 0.0012616 | 0.0044421 | 0.7763007 | 0.7764105 | 0.0735865 | 0.0730831 | NA |
1 715265 rs12184267 C T . PASS AF=0.0366377 ES:SE:LP:AF:ID 0.00437052:0.00620813:0.317674:0.0366377:rs12184267
1 715367 rs12184277 A G . PASS AF=0.0367695 ES:SE:LP:AF:ID 0.00393957:0.0061943:0.280255:0.0367695:rs12184277
1 717485 rs12184279 C A . PASS AF=0.0364631 ES:SE:LP:AF:ID 0.00494415:0.00621906:0.369979:0.0364631:rs12184279
1 720381 rs116801199 G T . PASS AF=0.0371104 ES:SE:LP:AF:ID 0.00404125:0.00616044:0.291069:0.0371104:rs116801199
1 721290 rs12565286 G C . PASS AF=0.037208 ES:SE:LP:AF:ID 0.00496018:0.00615407:0.376647:0.037208:rs12565286
1 723891 rs2977670 G C . PASS AF=0.950352 ES:SE:LP:AF:ID -0.00158479:0.00537216:0.114413:0.950352:rs2977670
1 726794 rs28454925 C G . PASS AF=0.036613 ES:SE:LP:AF:ID 0.00331008:0.00619865:0.226579:0.036613:rs28454925
1 729632 rs116720794 C T . PASS AF=0.0368931 ES:SE:LP:AF:ID 0.00393228:0.00617312:0.280503:0.0368931:rs116720794
1 729679 rs4951859 C G . PASS AF=0.831614 ES:SE:LP:AF:ID 0.00180494:0.00315549:0.245958:0.831614:rs4951859
1 752478 rs146277091 G A . PASS AF=0.0367696 ES:SE:LP:AF:ID 0.00498576:0.00617049:0.377475:0.0367696:rs146277091
1 752566 rs3094315 G A . PASS AF=0.829189 ES:SE:LP:AF:ID 0.00118959:0.00308184:0.155026:0.829189:rs3094315
1 752721 rs3131972 A G . PASS AF=0.826243 ES:SE:LP:AF:ID 0.00138787:0.00305698:0.187421:0.826243:rs3131972
1 753405 rs3115860 C A . PASS AF=0.860653 ES:SE:LP:AF:ID 0.00251336:0.00335562:0.342753:0.860653:rs3115860
1 753541 rs2073813 G A . PASS AF=0.140455 ES:SE:LP:AF:ID -0.00316295:0.00334704:0.462937:0.140455:rs2073813
1 754063 rs12184312 G T . PASS AF=0.0371833 ES:SE:LP:AF:ID 0.00404862:0.006125:0.293709:0.0371833:rs12184312
1 754105 rs12184325 C T . PASS AF=0.0374306 ES:SE:LP:AF:ID 0.00427766:0.00610222:0.315604:0.0374306:rs12184325
1 754182 rs3131969 A G . PASS AF=0.857265 ES:SE:LP:AF:ID 0.00273161:0.00332313:0.386264:0.857265:rs3131969
1 754192 rs3131968 A G . PASS AF=0.857357 ES:SE:LP:AF:ID 0.00291198:0.00332418:0.419075:0.857357:rs3131968
1 754211 rs12184313 G A . PASS AF=0.0374202 ES:SE:LP:AF:ID 0.00468577:0.00610922:0.3534:0.0374202:rs12184313
1 754334 rs3131967 T C . PASS AF=0.857369 ES:SE:LP:AF:ID 0.00258296:0.00332428:0.359419:0.857369:rs3131967
1 754503 rs3115859 G A . PASS AF=0.826634 ES:SE:LP:AF:ID 0.00149505:0.00306991:0.203079:0.826634:rs3115859
1 754629 rs10454459 A G . PASS AF=0.0374193 ES:SE:LP:AF:ID 0.00492589:0.00611152:0.376647:0.0374193:rs10454459
1 754964 rs3131966 C T . PASS AF=0.827271 ES:SE:LP:AF:ID 0.00137866:0.00307736:0.184223:0.827271:rs3131966
1 755775 rs3131965 A G . PASS AF=0.831031 ES:SE:LP:AF:ID 0.00190159:0.00315878:0.262092:0.831031:rs3131965
1 755890 rs3115858 A T . PASS AF=0.860232 ES:SE:LP:AF:ID 0.00301593:0.0033436:0.435334:0.860232:rs3115858
1 756604 rs3131962 A G . PASS AF=0.85979 ES:SE:LP:AF:ID 0.00286232:0.00333604:0.407934:0.85979:rs3131962
1 757640 rs3115853 G A . PASS AF=0.854521 ES:SE:LP:AF:ID 0.00289367:0.00328826:0.421705:0.854521:rs3115853
1 757734 rs4951929 C T . PASS AF=0.859889 ES:SE:LP:AF:ID 0.00287078:0.00333812:0.40927:0.859889:rs4951929
1 757936 rs4951862 C A . PASS AF=0.859935 ES:SE:LP:AF:ID 0.00287456:0.00333862:0.409493:0.859935:rs4951862
1 758144 rs3131956 A G . PASS AF=0.859942 ES:SE:LP:AF:ID 0.00290801:0.0033387:0.415895:0.859942:rs3131956
1 758626 rs3131954 C T . PASS AF=0.860464 ES:SE:LP:AF:ID 0.00302228:0.00334693:0.435571:0.860464:rs3131954
1 759036 rs114525117 G A . PASS AF=0.0374737 ES:SE:LP:AF:ID 0.00392766:0.00609885:0.284164:0.0374737:rs114525117
1 760912 rs1048488 C T . PASS AF=0.82959 ES:SE:LP:AF:ID 0.00151856:0.0030928:0.204955:0.82959:rs1048488
1 760998 rs148828841 C A . PASS AF=0.0369479 ES:SE:LP:AF:ID 0.00334097:0.00615281:0.231214:0.0369479:rs148828841
1 761147 rs3115850 T C . PASS AF=0.829712 ES:SE:LP:AF:ID 0.00142642:0.00309418:0.19044:0.829712:rs3115850
1 761606 rs377377186 G A . PASS AF=0.0358125 ES:SE:LP:AF:ID 0.00767679:0.00627189:0.655804:0.0358125:rs377377186
1 761732 rs2286139 C T . PASS AF=0.848492 ES:SE:LP:AF:ID 0.00311024:0.00330525:0.460297:0.848492:rs2286139
1 761881 rs374493323 A C . PASS AF=0.0342849 ES:SE:LP:AF:ID 0.00757388:0.00642398:0.622694:0.0342849:rs374493323
1 766007 rs61768174 A C . PASS AF=0.105478 ES:SE:LP:AF:ID -0.00305933:0.00381939:0.373352:0.105478:rs61768174
1 767096 rs115991721 A G . PASS AF=0.00259125 ES:SE:LP:AF:ID -0.00836166:0.0227838:0.146363:0.00259125:rs115991721
1 768253 rs2977608 A C . PASS AF=0.744125 ES:SE:LP:AF:ID 0.000303336:0.00266085:0.0414361:0.744125:rs2977608
1 768448 rs12562034 G A . PASS AF=0.111263 ES:SE:LP:AF:ID 0.00336668:0.00368345:0.443095:0.111263:rs12562034
1 768680 rs140605359 C T . PASS AF=0.00057169 ES:SE:LP:AF:ID -0.0626664:0.0484659:0.707522:0.00057169:rs140605359
1 768819 rs12562811 C T . PASS AF=0.0121867 ES:SE:LP:AF:ID 0.0120171:0.0105971:0.590236:0.0121867:rs12562811
1 769223 rs60320384 C G . PASS AF=0.135131 ES:SE:LP:AF:ID -0.00345445:0.00339337:0.510463:0.135131:rs60320384
1 770504 rs150664068 C G . PASS AF=0.000562164 ES:SE:LP:AF:ID -0.0524432:0.0488753:0.5476:0.000562164:rs150664068
1 771823 rs2977605 T C . PASS AF=0.859693 ES:SE:LP:AF:ID 0.00324281:0.00333966:0.479255:0.859693:rs2977605
1 771967 rs59066358 G A . PASS AF=0.136281 ES:SE:LP:AF:ID -0.00354017:0.00338125:0.530178:0.136281:rs59066358
1 772755 rs2905039 A C . PASS AF=0.859685 ES:SE:LP:AF:ID 0.00329622:0.00333963:0.489723:0.859685:rs2905039
1 776556 rs151160018 C T . PASS AF=0.00833475 ES:SE:LP:AF:ID -0.00392878:0.0127558:0.120216:0.00833475:rs151160018