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"gwas_harmonisation_command": "--json /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-a-import/processed/ukb-a-207/ukb-a-207_data.json --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/QC/genomes/b37/human_g1k_v37.fasta; 1.1.1",
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"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/ukb-a-import/processed/ukb-a-207/ukb-a-207.vcf.gz -O z /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-a-import/processed/ukb-a-207/ukb-a-207_data.vcf.gz; Date=Sun Feb 16 01:24:44 2020",
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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-a-import/processed/ukb-a-207/ukb-a-207.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-a-import/processed/ukb-a-207/ldsc.txt \
--w-ld-chr /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/reference/eur_w_ld_chr/
Beginning analysis at Sun Feb 16 01:55:35 2020
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/dev/ukb-a-import/processed/ukb-a-207/ukb-a-207.vcf.gz ...
Read summary statistics for 10877936 SNPs.
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, 1281483 SNPs remain.
After merging with regression SNP LD, 1281483 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0193 (0.0018)
Lambda GC: 1.1038
Mean Chi^2: 1.1235
Intercept: 1.0114 (0.0065)
Ratio: 0.0926 (0.0527)
Analysis finished at Sun Feb 16 01:57:19 2020
Total time elapsed: 1.0m:44.39s
{
"af_correlation": 0.9533,
"inflation_factor": 1.0639,
"mean_EFFECT": -4.522e-06,
"n": 292053,
"n_snps": 10877936,
"n_clumped_hits": 6,
"n_p_sig": 110,
"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": 356865,
"n_est": 290867.1841,
"ratio_se_n": 0.998,
"mean_diff": -6.6019e-06,
"ratio_diff": 32.1294,
"sd_y_est1": 0.415,
"sd_y_est2": 0.4142,
"r2_sum1": 0.0001,
"r2_sum2": 0.0008,
"r2_sum3": 0.0008,
"r2_sum4": 0.0008,
"ldsc_nsnp_merge_refpanel_ld": 1281483,
"ldsc_nsnp_merge_regression_ld": 1281483,
"ldsc_observed_scale_h2_beta": 0.0193,
"ldsc_observed_scale_h2_se": 0.0018,
"ldsc_intercept_beta": 1.0114,
"ldsc_intercept_se": 0.0065,
"ldsc_lambda_gc": 1.1038,
"ldsc_mean_chisq": 1.1235,
"ldsc_ratio": 0.0923
}
name | value |
---|---|
af_correlation | FALSE |
inflation_factor | FALSE |
n | FALSE |
is_snpid_non_unique | FALSE |
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 | 58 | 0 | 10877936 | 0 | 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 |
character | ALT | 0 | 1.0000000 | 1 | 1 | 0 | 4 | 0 | NA | NA | NA | NA | NA | NA | NA | NA |
numeric | CHROM | 0 | 1.0000000 | NA | NA | NA | NA | NA | 8.598638e+00 | 5.745666e+00 | 1.00000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▃▂▂ |
numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | 7.911383e+07 | 5.624931e+07 | 8.28000e+02 | 3.287294e+07 | 6.988889e+07 | 1.148258e+08 | 2.492251e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | -4.500000e-06 | 6.496600e-03 | -7.45711e-02 | -1.805400e-03 | -7.300000e-06 | 1.786200e-03 | 8.628610e-02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.677400e-03 | 4.430300e-03 | 1.07310e-03 | 1.325300e-03 | 2.545300e-03 | 6.802500e-03 | 2.432880e-02 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.899438e-01 | 2.918199e-01 | 0.00000e+00 | 2.343597e-01 | 4.866088e-01 | 7.429798e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | 4.899433e-01 | 2.918202e-01 | 0.00000e+00 | 2.343587e-01 | 4.866085e-01 | 7.429792e-01 | 9.999998e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | 1.820865e-01 | 2.503832e-01 | 1.00090e-03 | 6.878700e-03 | 5.191440e-02 | 2.739880e-01 | 9.989990e-01 | ▇▂▁▁▁ |
numeric | AF_reference | 356865 | 0.9671937 | NA | NA | NA | NA | NA | 1.877709e-01 | 2.439191e-01 | 0.00000e+00 | 5.191700e-03 | 7.468050e-02 | 2.873400e-01 | 1.000000e+00 | ▇▂▁▁▁ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | 2.920530e+05 | 0.000000e+00 | 2.92053e+05 | 2.920530e+05 | 2.920530e+05 | 2.920530e+05 | 2.920530e+05 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 693731 | rs12238997 | A | G | 0.0002133 | 0.0017901 | 0.9051520 | 0.9051517 | 0.1169260 | 0.1417730 | 292053 |
1 | 717587 | rs144155419 | G | A | 0.0028251 | 0.0048062 | 0.5566574 | 0.5566580 | 0.0143862 | 0.0045926 | 292053 |
1 | 730087 | rs148120343 | T | C | -0.0004798 | 0.0024970 | 0.8476290 | 0.8476291 | 0.0554733 | 0.0127796 | 292053 |
1 | 731718 | rs142557973 | T | C | 0.0000713 | 0.0016979 | 0.9665130 | 0.9665130 | 0.1216580 | 0.1543530 | 292053 |
1 | 734349 | rs141242758 | T | C | 0.0001663 | 0.0016989 | 0.9220231 | 0.9220231 | 0.1215130 | 0.1525560 | 292053 |
1 | 740284 | rs61770167 | C | T | 0.0011715 | 0.0077062 | 0.8791670 | 0.8791666 | 0.0058556 | 0.0023962 | 292053 |
1 | 742813 | rs112573343 | C | T | 0.0231638 | 0.0146238 | 0.1131999 | 0.1131984 | 0.0015525 | 0.1030350 | 292053 |
1 | 753405 | rs3115860 | C | A | -0.0000990 | 0.0016144 | 0.9510860 | 0.9510857 | 0.8706760 | 0.7517970 | 292053 |
1 | 753541 | rs2073813 | G | A | 0.0000955 | 0.0016185 | 0.9529469 | 0.9529468 | 0.1288330 | 0.3019170 | 292053 |
1 | 754182 | rs3131969 | A | G | -0.0001044 | 0.0016127 | 0.9483610 | 0.9483607 | 0.8703180 | 0.6785140 | 292053 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51219387 | rs9616832 | T | C | 0.0026322 | 0.0020814 | 0.2060099 | 0.2060098 | 0.0729806 | 0.0654952 | 292053 |
22 | 51219704 | rs147475742 | G | A | 0.0039124 | 0.0027915 | 0.1610549 | 0.1610534 | 0.0418225 | 0.0473243 | 292053 |
22 | 51219766 | rs182321900 | C | T | 0.0138026 | 0.0142926 | 0.3341881 | 0.3341860 | 0.0014546 | NA | 292053 |
22 | 51220088 | rs566371895 | G | A | 0.0043512 | 0.0094009 | 0.6434770 | 0.6434769 | 0.0039843 | 0.0003994 | 292053 |
22 | 51220146 | rs868950473 | C | T | 0.0144812 | 0.0140789 | 0.3036813 | 0.3036796 | 0.0015139 | NA | 292053 |
22 | 51221731 | rs115055839 | T | C | 0.0026350 | 0.0020826 | 0.2057889 | 0.2057882 | 0.0728101 | 0.0625000 | 292053 |
22 | 51223637 | rs375798137 | G | A | -0.0027380 | 0.0024536 | 0.2644618 | 0.2644616 | 0.0540289 | 0.0788738 | 292053 |
22 | 51226692 | rs150189434 | G | A | 0.0127330 | 0.0146384 | 0.3843899 | 0.3843903 | 0.0013983 | 0.0155751 | 292053 |
22 | 51229805 | rs9616985 | T | C | 0.0026612 | 0.0020902 | 0.2029612 | 0.2029594 | 0.0727671 | 0.0730831 | 292053 |
22 | 51237063 | rs3896457 | T | C | 0.0003770 | 0.0012719 | 0.7669322 | 0.7669318 | 0.2968410 | 0.2050720 | 292053 |
1 693731 rs12238997 A G . PASS AF=0.116926 ES:SE:LP:AF:SS:ID 0.0002133:0.00179009:0.0432785:0.116926:292053:rs12238997
1 717587 rs144155419 G A . PASS AF=0.0143862 ES:SE:LP:AF:SS:ID 0.00282514:0.00480619:0.254412:0.0143862:292053:rs144155419
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1 731718 rs58276399 T C . PASS AF=0.121658 ES:SE:LP:AF:SS:ID 7.12818e-05:0.00169791:0.0147923:0.121658:292053:rs58276399
1 734349 rs141242758 T C . PASS AF=0.121513 ES:SE:LP:AF:SS:ID 0.000166297:0.00169889:0.0352582:0.121513:292053:rs141242758
1 740284 rs61770167 C T . PASS AF=0.00585559 ES:SE:LP:AF:SS:ID 0.00117154:0.00770619:0.0559286:0.00585559:292053:rs61770167
1 742813 rs112573343 C T . PASS AF=0.0015525 ES:SE:LP:AF:SS:ID 0.0231638:0.0146238:0.946154:0.0015525:292053:rs112573343
1 753405 rs3115860 C A . PASS AF=0.870676 ES:SE:LP:AF:SS:ID -9.9034e-05:0.00161442:0.0217802:0.870676:292053:rs3115860
1 753541 rs2073813 G A . PASS AF=0.128833 ES:SE:LP:AF:SS:ID 9.55017e-05:0.00161849:0.0209313:0.128833:292053:rs2073813
1 754182 rs3131969 A G . PASS AF=0.870318 ES:SE:LP:AF:SS:ID -0.000104448:0.00161271:0.0230263:0.870318:292053:rs3131969
1 754192 rs3131968 A G . PASS AF=0.870409 ES:SE:LP:AF:SS:ID -0.000235032:0.00161346:0.0534583:0.870409:292053:rs3131968
1 754334 rs3131967 T C . PASS AF=0.870037 ES:SE:LP:AF:SS:ID -9.59444e-05:0.00161264:0.0211086:0.870037:292053:rs3131967
1 754433 rs150578204 G A . PASS AF=0.00465304 ES:SE:LP:AF:SS:ID 0.000514607:0.00822847:0.0222156:0.00465304:292053:rs150578204
1 754458 rs142682604 G T . PASS AF=0.00464711 ES:SE:LP:AF:SS:ID 0.000498901:0.00824878:0.0214671:0.00464711:292053:rs142682604
1 755435 rs184270342 T G . PASS AF=0.00590897 ES:SE:LP:AF:SS:ID -0.00478317:0.00801367:0.259172:0.00590897:292053:rs184270342
1 755890 rs3115858 A T . PASS AF=0.870329 ES:SE:LP:AF:SS:ID -8.08118e-05:0.00160986:0.0177446:0.870329:292053:rs3115858
1 756604 rs3131962 A G . PASS AF=0.87002 ES:SE:LP:AF:SS:ID -9.81205e-05:0.00160598:0.0216907:0.87002:292053:rs3131962
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1 757734 rs4951929 C T . PASS AF=0.870219 ES:SE:LP:AF:SS:ID -0.000104856:0.00160726:0.023199:0.870219:292053:rs4951929
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1 758144 rs3131956 A G . PASS AF=0.870222 ES:SE:LP:AF:SS:ID -0.000103954:0.00160743:0.022992:0.870222:292053:rs3131956
1 758626 rs3131954 C T . PASS AF=0.870396 ES:SE:LP:AF:SS:ID -5.04712e-05:0.0016116:0.0109883:0.870396:292053:rs3131954
1 761732 rs2286139 C T . PASS AF=0.867743 ES:SE:LP:AF:SS:ID -0.000112969:0.00160394:0.025097:0.867743:292053:rs2286139
1 766007 rs61768174 A C . PASS AF=0.106958 ES:SE:LP:AF:SS:ID -0.000597516:0.0017865:0.131925:0.106958:292053:rs61768174
1 768253 rs2977608 A C . PASS AF=0.763932 ES:SE:LP:AF:SS:ID -0.000462671:0.00127296:0.144929:0.763932:292053:rs2977608
1 768448 rs12562034 G A . PASS AF=0.105257 ES:SE:LP:AF:SS:ID 0.000608449:0.00175812:0.137103:0.105257:292053:rs12562034
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1 769223 rs60320384 C G . PASS AF=0.128651 ES:SE:LP:AF:SS:ID 8.02577e-06:0.00161586:0.00172453:0.128651:292053:rs60320384
1 769224 rs141644775 G A . PASS AF=0.00143239 ES:SE:LP:AF:SS:ID -0.0368016:0.015256:1.79986:0.00143239:292053:rs141644775
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1 770377 rs112563271 A T . PASS AF=0.00692321 ES:SE:LP:AF:SS:ID 0.00537647:0.00653943:0.386173:0.00692321:292053:rs112563271
1 771823 rs2977605 T C . PASS AF=0.869934 ES:SE:LP:AF:SS:ID -6.29613e-05:0.00160883:0.0137735:0.869934:292053:rs2977605
1 771967 rs59066358 G A . PASS AF=0.128709 ES:SE:LP:AF:SS:ID -2.03971e-05:0.00161529:0.00439771:0.128709:292053:rs59066358
1 772755 rs2905039 A C . PASS AF=0.870112 ES:SE:LP:AF:SS:ID -9.81923e-05:0.00160891:0.0216665:0.870112:292053:rs2905039
1 774736 rs28830877 A C . PASS AF=0.998797 ES:SE:LP:AF:SS:ID -0.0130504:0.0168321:0.35838:0.998797:292053:rs28830877
1 776556 rs151160018 C T . PASS AF=0.00851871 ES:SE:LP:AF:SS:ID 0.00398915:0.00602636:0.294134:0.00851871:292053:rs151160018
1 777122 rs2980319 A T . PASS AF=0.871122 ES:SE:LP:AF:SS:ID -0.00041727:0.00161149:0.0992583:0.871122:292053:rs2980319
1 777232 rs112618790 C T . PASS AF=0.0961319 ES:SE:LP:AF:SS:ID 5.56685e-05:0.00186206:0.0104834:0.0961319:292053:rs112618790
1 778745 rs1055606 A G . PASS AF=0.127871 ES:SE:LP:AF:SS:ID 0.000324364:0.00161679:0.0752071:0.127871:292053:rs1055606
1 779322 rs4040617 A G . PASS AF=0.127984 ES:SE:LP:AF:SS:ID 0.00031102:0.0016146:0.0719889:0.127984:292053:rs4040617
1 780785 rs2977612 T A . PASS AF=0.870455 ES:SE:LP:AF:SS:ID -0.000342155:0.00160888:0.0800923:0.870455:292053:rs2977612
1 781367 rs149821290 A C . PASS AF=0.00989772 ES:SE:LP:AF:SS:ID -0.00606871:0.00570757:0.541124:0.00989772:292053:rs149821290
1 781845 rs61768199 A G . PASS AF=0.1044 ES:SE:LP:AF:SS:ID -0.000645973:0.00180967:0.141989:0.1044:292053:rs61768199
1 782721 rs185280546 G A . PASS AF=0.0143713 ES:SE:LP:AF:SS:ID 0.00235298:0.00490354:0.199742:0.0143713:292053:rs185280546
1 782981 rs6594026 C T . PASS AF=0.128338 ES:SE:LP:AF:SS:ID 0.000208071:0.00161566:0.0469515:0.128338:292053:rs6594026
1 783193 rs145767270 G C . PASS AF=0.0143639 ES:SE:LP:AF:SS:ID 0.00244414:0.00492195:0.207969:0.0143639:292053:rs145767270
1 783194 rs138555831 G T . PASS AF=0.0143713 ES:SE:LP:AF:SS:ID 0.0024326:0.0049214:0.206838:0.0143713:292053:rs138555831
1 783711 rs184266993 G A . PASS AF=0.00541372 ES:SE:LP:AF:SS:ID 0.00321926:0.00787733:0.165719:0.00541372:292053:rs184266993
1 785050 rs2905062 G A . PASS AF=0.87014 ES:SE:LP:AF:SS:ID -0.000404415:0.00160913:0.0960623:0.87014:292053:rs2905062
1 785989 rs2980300 T C . PASS AF=0.87009 ES:SE:LP:AF:SS:ID -0.000440654:0.0016102:0.105494:0.87009:292053:rs2980300