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"FORMAT.1": "<ID=ES,Number=A,Type=Float,Description=\"Effect size estimate relative to the alternative allele\">",
"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.7": "<ID=VariantsNotRead,Number=1,Type=Integer,Description=\"Number of variants that could not be read\">",
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"file_date": "2019-10-27T20:50:42.235565",
"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004600/EBI-a-GCST004600_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-GCST004600/EBI-a-GCST004600.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004600/EBI-a-GCST004600_data.vcf.gz; Date=Sun Oct 27 21:40:21 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-GCST004600/ebi-a-GCST004600.vcf.gz; Date=Sun May 10 23:11:52 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-GCST004600/EBI-a-GCST004600.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-GCST004600/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 Sun Oct 27 22:08:48 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ebi_gwas_import/processed/EBI-a-GCST004600/EBI-a-GCST004600.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 Sun Oct 27 22:12:01 2019
Total time elapsed: 3.0m:13.36s
{
"af_correlation": 0.9629,
"inflation_factor": 1,
"mean_EFFECT": 0.0001,
"n": "-Inf",
"n_snps": 29167232,
"n_clumped_hits": 171,
"n_p_sig": 37728,
"n_mono": 0,
"n_ns": 2186718,
"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": 3828543,
"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 | FALSE |
n | TRUE |
is_snpid_non_unique | TRUE |
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 | 58 | 0 | 29141643 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
character | REF | 0 | 1.0000000 | 1 | 93 | 0 | 107706 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
character | ALT | 0 | 1.0000000 | 1 | 103 | 0 | 46326 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
logical | N | 29142110 | 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 | 8.646803e+00 | 5.784601e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▃▂▂ |
numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.917786e+07 | 5.638542e+07 | 56.0000000 | 3.277794e+07 | 6.999092e+07 | 1.150709e+08 | 2.492398e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.239000e-04 | 8.025910e-02 | -1.1332800 | -2.192810e-02 | 2.010000e-05 | 2.211510e-02 | 1.139190e+00 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 6.263370e-02 | 5.512050e-02 | 0.0031416 | 9.266600e-03 | 5.159600e-02 | 1.023260e-01 | 4.445850e-01 | ▇▃▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.987279e-01 | 2.905167e-01 | 0.0000000 | 2.474999e-01 | 5.000000e-01 | 7.504003e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.987278e-01 | 2.905167e-01 | 0.0000000 | 2.475388e-01 | 4.999679e-01 | 7.503827e-01 | 9.999999e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 9.255390e-02 | 2.049350e-01 | 0.0001000 | 5.000000e-04 | 1.800000e-03 | 4.660000e-02 | 9.999000e-01 | ▇▁▁▁▁ |
numeric | AF_reference | 3828543 | 0.8686251 | NA | NA | NA | NA | NA | NA | NA | 1.073484e-01 | 2.076407e-01 | 0.0000000 | 3.994000e-04 | 6.190100e-03 | 9.524760e-02 | 1.000000e+00 | ▇▁▁▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 10177 | rs367896724 | A | AC | -0.0010591 | 0.0049144 | 0.8293999 | 0.8293708 | 0.3923 | 0.4253190 | NA |
1 | 10352 | rs555500075 | T | TA | 0.0076623 | 0.0050521 | 0.1293999 | 0.1293567 | 0.3854 | 0.4375000 | NA |
1 | 10616 | rs376342519 | CCGCCGTTGCAAAGGCGCGCCG | C | 0.0608446 | 0.0323266 | 0.0598095 | 0.0598111 | 0.9942 | 0.9930110 | NA |
1 | 11012 | rs544419019 | C | G | 0.0123872 | 0.0085559 | 0.1476998 | 0.1476755 | 0.0845 | 0.0880591 | NA |
1 | 13110 | rs540538026 | G | A | 0.0091906 | 0.0108507 | 0.3969995 | 0.3969948 | 0.0591 | 0.0267572 | NA |
1 | 13116 | rs62635286 | T | G | 0.0094130 | 0.0065552 | 0.1510000 | 0.1510139 | 0.1870 | 0.0970447 | NA |
1 | 13118 | rs200579949 | A | G | 0.0058017 | 0.0065374 | 0.3748004 | 0.3748336 | 0.1883 | 0.0970447 | NA |
1 | 13273 | rs531730856 | G | C | -0.0024368 | 0.0074890 | 0.7449000 | 0.7448906 | 0.1345 | 0.0950479 | NA |
1 | 13445 | rs558318514 | C | G | -0.0222415 | 0.0977580 | 0.8200001 | 0.8200226 | 0.0006 | 0.0005990 | NA |
1 | 13453 | rs568927457 | T | C | 0.0116674 | 0.0300427 | 0.6977004 | 0.6977492 | 0.0063 | 0.0007987 | NA |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51238364 | rs564490465 | C | G | 0.0079836 | 0.0360782 | 0.8249000 | 0.8248704 | 0.0048 | 0.0005990 | NA |
22 | 51238394 | rs149712012 | C | T | -0.0035824 | 0.0366352 | 0.9221000 | 0.9221018 | 0.0035 | 0.0033946 | NA |
22 | 51239281 | rs8138215 | G | C | -0.0158497 | 0.0459119 | 0.7298994 | 0.7299291 | 0.0025 | 0.0111821 | NA |
22 | 51239296 | rs8137179 | T | C | -0.0158497 | 0.0459119 | 0.7298994 | 0.7299291 | 0.0025 | 0.0111821 | NA |
22 | 51239304 | rs8142977 | C | T | -0.0158497 | 0.0459119 | 0.7298994 | 0.7299291 | 0.0025 | 0.0111821 | NA |
22 | 51239586 | rs535432390 | T | G | -0.0561639 | 0.0506129 | 0.2671001 | 0.2671388 | 0.0018 | 0.0001997 | NA |
22 | 51239652 | rs564418969 | G | T | 0.0451497 | 0.1003780 | 0.6529005 | 0.6528570 | 0.0008 | 0.0011981 | NA |
22 | 51239794 | rs561893765 | C | A | -0.0740777 | 0.0507302 | 0.1441999 | 0.1442272 | 0.0020 | 0.0299521 | NA |
22 | 51240820 | rs202228854 | C | T | -0.0132614 | 0.0133292 | 0.3197997 | 0.3197784 | 0.0264 | 0.1267970 | NA |
22 | 51244237 | rs575160859 | C | T | -0.0064784 | 0.0206660 | 0.7539004 | 0.7539145 | 0.0123 | 0.0037939 | NA |
1 10177 rs367896724 A AC . PASS AF=0.3923 ES:SE:LP:AF:ID -0.0010591:0.00491442:0.081236:0.3923:rs367896724
1 10352 rs555500075 T TA . PASS AF=0.3854 ES:SE:LP:AF:ID 0.00766228:0.00505213:0.888066:0.3854:rs555500075
1 10616 rs376342519 CCGCCGTTGCAAAGGCGCGCCG C . PASS AF=0.9942 ES:SE:LP:AF:ID 0.0608446:0.0323266:1.22323:0.9942:rs376342519
1 11012 rs544419019 C G . PASS AF=0.0845 ES:SE:LP:AF:ID 0.0123872:0.00855593:0.83062:0.0845:rs544419019
1 13110 rs540538026 G A . PASS AF=0.0591 ES:SE:LP:AF:ID 0.00919055:0.0108507:0.40121:0.0591:rs540538026
1 13116 rs62635286 T G . PASS AF=0.187 ES:SE:LP:AF:ID 0.009413:0.0065552:0.821023:0.187:rs62635286
1 13118 rs62028691 A G . PASS AF=0.1883 ES:SE:LP:AF:ID 0.00580168:0.00653743:0.4262:0.1883:rs62028691
1 13273 rs531730856 G C . PASS AF=0.1345 ES:SE:LP:AF:ID -0.00243679:0.00748897:0.127902:0.1345:rs531730856
1 13445 rs558318514 C G . PASS AF=0.0006 ES:SE:LP:AF:ID -0.0222415:0.097758:0.0861861:0.0006:rs558318514
1 13453 rs568927457 T C . PASS AF=0.0063 ES:SE:LP:AF:ID 0.0116674:0.0300427:0.156331:0.0063:rs568927457
1 13483 rs554760071 G C . PASS AF=0.0049 ES:SE:LP:AF:ID 0.0107246:0.0340519:0.12332:0.0049:rs554760071
1 14464 rs546169444 A T . PASS AF=0.1535 ES:SE:LP:AF:ID 0.00561071:0.00695948:0.376647:0.1535:rs546169444
1 14599 rs707680 T A . PASS AF=0.1915 ES:SE:LP:AF:ID 0.00338886:0.00632622:0.227532:0.1915:rs707680
1 14604 rs541940975 A G . PASS AF=0.1911 ES:SE:LP:AF:ID 0.00523416:0.00633356:0.388702:0.1911:rs541940975
1 14930 rs6682385 A G . PASS AF=0.4634 ES:SE:LP:AF:ID -0.000927438:0.00495563:0.0698153:0.4634:rs6682385
1 14933 rs199856693 G A . PASS AF=0.0475 ES:SE:LP:AF:ID -0.00397287:0.0117142:0.134008:0.0475:rs199856693
1 15211 rs3982632 T G . PASS AF=0.7262 ES:SE:LP:AF:ID -0.00163257:0.00552755:0.114808:0.7262:rs3982632
1 15245 rs576044687 C T . PASS AF=0.0014 ES:SE:LP:AF:ID -0.0225877:0.0630297:0.142607:0.0014:rs576044687
1 15644 rs564003018 G A . PASS AF=0.004 ES:SE:LP:AF:ID 0.0243049:0.0421218:0.248798:0.004:rs564003018
1 15820 rs2691315 G T . PASS AF=0.2681 ES:SE:LP:AF:ID 0.00102223:0.00577666:0.0657541:0.2681:rs2691315
1 15903 rs557514207 G GC . PASS AF=0.4015 ES:SE:LP:AF:ID -0.00459899:0.00488811:0.459921:0.4015:rs557514207
1 16141 rs529651976 C T . PASS AF=0.0005 ES:SE:LP:AF:ID -0.00452071:0.104858:0.0152027:0.0005:rs529651976
1 16142 rs548165136 G A . PASS AF=0.003 ES:SE:LP:AF:ID -0.022117:0.0465686:0.197363:0.003:rs548165136
1 16542 rs539235482 C A . PASS AF=0.0001 ES:SE:LP:AF:ID -0.0445699:0.178764:0.0952304:0.0001:rs539235482
1 16949 rs199745162 A C . PASS AF=0.0208 ES:SE:LP:AF:ID 0.00145803:0.0172547:0.030258:0.0208:rs199745162
1 17571 rs557947346 C T . PASS AF=0.0006 ES:SE:LP:AF:ID -0.129725:0.110152:0.621784:0.0006:rs557947346
1 17641 rs578081284 G A . PASS AF=0.0007 ES:SE:LP:AF:ID -0.0292502:0.0705082:0.168578:0.0007:rs578081284
1 18643 rs564023708 G A . PASS AF=0.006 ES:SE:LP:AF:ID 0.0325321:0.0337221:0.475344:0.006:rs564023708
1 18849 rs533090414 C G . PASS AF=0.9728 ES:SE:LP:AF:ID -0.0159397:0.0142365:0.580209:0.9728:rs533090414
1 30524 rs534702355 G A . PASS AF=0.0007 ES:SE:LP:AF:ID 0.147259:0.0889799:1.00908:0.0007:rs534702355
1 30923 rs806731 G T . PASS AF=0.9008 ES:SE:LP:AF:ID -0.00845479:0.00838461:0.50404:0.9008:rs806731
1 46285 rs545414834 ATAT A . PASS AF=0.0018 ES:SE:LP:AF:ID 0.0322712:0.0554581:0.251347:0.0018:rs545414834
1 47159 rs540662756 T C . PASS AF=0.0646 ES:SE:LP:AF:ID 0.0155431:0.0103073:0.880744:0.0646:rs540662756
1 48327 rs565824523 C A . PASS AF=0.0004 ES:SE:LP:AF:ID 0.115405:0.132381:0.416461:0.0004:rs565824523
1 48328 rs528394432 A T . PASS AF=0.0004 ES:SE:LP:AF:ID 0.105835:0.132379:0.372634:0.0004:rs528394432
1 49298 rs10399793 T C . PASS AF=0.8332 ES:SE:LP:AF:ID -0.0219772:0.00672828:2.96297:0.8332:rs10399793
1 49318 rs536836601 A G . PASS AF=0.0016 ES:SE:LP:AF:ID 0.0277943:0.0588564:0.195997:0.0016:rs536836601
1 49343 rs553572247 T C . PASS AF=0.0021 ES:SE:LP:AF:ID -0.0587477:0.0535965:0.563837:0.0021:rs553572247
1 49482 rs202079915 G A . PASS AF=0.0002 ES:SE:LP:AF:ID -0.143231:0.192013:0.341321:0.0002:rs202079915
1 49554 rs539322794 A G . PASS AF=0.0935 ES:SE:LP:AF:ID 0.0226838:0.00871187:2.03527:0.0935:rs539322794
1 51047 rs559500163 A T . PASS AF=0.0018 ES:SE:LP:AF:ID 0.0369545:0.0621625:0.257904:0.0018:rs559500163
1 51049 rs528344458 A C . PASS AF=0.0018 ES:SE:LP:AF:ID 0.0331074:0.0621683:0.225994:0.0018:rs528344458
1 51050 rs551668143 A T . PASS AF=0.0018 ES:SE:LP:AF:ID 0.0331074:0.0621683:0.225994:0.0018:rs551668143
1 51053 rs565211799 G T . PASS AF=0.0018 ES:SE:LP:AF:ID 0.0331074:0.0621683:0.225994:0.0018:rs565211799
1 51479 rs116400033 T A . PASS AF=0.2085 ES:SE:LP:AF:ID 0.000398987:0.00614417:0.0231:0.2085:rs116400033
1 51762 rs559190862 A G . PASS AF=0.009 ES:SE:LP:AF:ID -0.000854113:0.0267196:0.0112182:0.009:rs559190862
1 51765 rs575564077 C G . PASS AF=0.0086 ES:SE:LP:AF:ID -0.00541025:0.0272478:0.0743785:0.0086:rs575564077
1 52144 rs190291950 T A . PASS AF=0.0006 ES:SE:LP:AF:ID -0.0789395:0.0873259:0.436519:0.0006:rs190291950
1 52238 rs2691277 T G . PASS AF=0.9778 ES:SE:LP:AF:ID -0.0134382:0.0175257:0.3534:0.9778:rs2691277
1 53254 rs547088867 T A . PASS AF=0.0002 ES:SE:LP:AF:ID 0.0149306:0.125682:0.0431595:0.0002:rs547088867