Summary
Summary {data-width=650}
Manhattan plot
manhattan_plot
QQ plot
qq_plot
AF plot
af_plot
P-Z plot
pz_plot
beta_std plot
beta_std_plot
Metadata
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"Gwas2VCF_command": "--data /data/cromwell-executions/qc/ba72e90e-0a3c-4b94-9609-f07464ac591c/call-vcf/inputs/-261022184/upload.txt.gz --id ieu-b-5098 --json /data/cromwell-executions/qc/ba72e90e-0a3c-4b94-9609-f07464ac591c/call-vcf/inputs/-261022184/ieu-b-5098_data.json --ref /data/cromwell-executions/qc/ba72e90e-0a3c-4b94-9609-f07464ac591c/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/ba72e90e-0a3c-4b94-9609-f07464ac591c/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-5098/ieu-b-5098.vcf.gz --alias alias.txt --cohort_cases 5998 --cohort_controls 3826; 1.3.0",
"file_date": "2023-02-03T02:27:00.766976",
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}
LDSC
*********************************************************************
* 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 /data/cromwell-executions/qc/ba72e90e-0a3c-4b94-9609-f07464ac591c/call-ldsc/inputs/-261022184/ieu-b-5098.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-5098/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Fri Feb 3 02:39:31 2023
Reading summary statistics from /data/cromwell-executions/qc/ba72e90e-0a3c-4b94-9609-f07464ac591c/call-ldsc/inputs/-261022184/ieu-b-5098.vcf.gz ...
Read summary statistics for 6315314 SNPs.
Dropped 17947 SNPs with duplicated rs numbers.
Reading reference panel LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from /data/ref/eur_w_ld_chr/[1-22] ... (ldscore_fromlist)
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1189789 SNPs remain.
After merging with regression SNP LD, 1189789 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0951 (0.0378)
Lambda GC: 1.0764
Mean Chi^2: 1.0745
Intercept: 1.0561 (0.0071)
Ratio: 0.7526 (0.0959)
Analysis finished at Fri Feb 3 02:40:55 2023
Total time elapsed: 1.0m:23.88sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9088,
"inflation_factor": 1.0743,
"mean_EFFECT": 0.0004,
"n": "-Inf",
"n_snps": 6315331,
"n_clumped_hits": 0,
"n_p_sig": 0,
"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": 3,
"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": 1189789,
"ldsc_nsnp_merge_regression_ld": 1189789,
"ldsc_observed_scale_h2_beta": 0.0951,
"ldsc_observed_scale_h2_se": 0.0378,
"ldsc_intercept_beta": 1.0561,
"ldsc_intercept_se": 0.0071,
"ldsc_lambda_gc": 1.0764,
"ldsc_mean_chisq": 1.0745,
"ldsc_ratio": 0.753
}
Flags
| name | value |
|---|---|
| af_correlation | FALSE |
| inflation_factor | FALSE |
| n | TRUE |
| 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 | TRUE |
| ldsc_intercept_beta | FALSE |
| n_clumped_hits | FALSE |
| r2_sum1 | FALSE |
| r2_sum2 | FALSE |
| r2_sum3 | FALSE |
| r2_sum4 | FALSE |
Definitions
General metrics
af_correlation: Correlation coefficient betweenAFandAF_reference.inflation_factor(lambda): Genomic inflation factor.mean_EFFECT: Mean ofEFFECTsize.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 below5e-8.n_mono: Number of monomorphic (MAF == 1orMAF == 0) SNPs.n_ns: Number of SNPs with nonsense values:- alleles other than
A, C, G or T. - P-values
< 0or> 1. - negative or infinite standard errors (
<= 0or= Infinity). - infinite beta estimates or allele frequencies
< 0or> 1.
- alleles other than
n_mac: Number of cases whereMAC(\(2 \times N \times MAF\)) is less than6.is_snpid_unique:trueif the combination ofIDREFALTis unique and therefore no duplication in snpid.n_miss_<*>: Number ofNAobservations 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 expectratio_se_nto 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.- \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
- \({z}_j = \frac{\beta_j}{{se}_j}\),
- and \(\beta_j\) is the reported effect size.
ratio_diff: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean ofdiffand the mean ofdiff2(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.- \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
- \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
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.- \(\widehat{\texttt{sd1}}_{y} = \frac{\sqrt{n} \times median({se}_j)}{C}\),
- \(C = median(\frac{1}{\sqrt{2 \times {MAF}_j \times (1 - {MAF}_j)}})\),
- and \({se}_j\) is the reported standard error.
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.- \(\widehat{\texttt{sd2}}_{y} = median(\widehat{sd_j})\),
- \(\widehat{sd_j} = \frac{\beta_j}{\widehat{\beta_j^{std}}}\),
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>:r2statistics under various assumptions1: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).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: NOTis_snpid_unique.mean_EFFECT_nonfinite:mean(EFFECT)isNA,NaN, orInf.mean_EFFECT_05:abs(mean(EFFECT))> 0.5.mean_EFFECT_01:abs(mean(EFFECT))> 0.1.mean_chisq:ldsc_mean_chisq> 1.3 orldsc_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<*>> 0.5
Plots
- Manhattan plot
- Red line: \(-log_{10}^{5 \times 10^{-8}}\)
- Blue line: \(-log_{10}^{5 \times 10^{-5}}\)
- QQ plot
- AF plot
- P-Z plot
- beta_std plot: Scatter plot between \(\widehat{\beta_j^{std}}\) and \(\beta_j\)
Diagnostics
Details
Summary stats
| 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 | 12 | 0 | 6315331 | 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 | 6315331 | 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 | 8.666719e+00 | 5.762427e+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 | 7.864437e+07 | 5.652241e+07 | 828.0000000 | 3.201211e+07 | 6.915197e+07 | 1.145722e+08 | 2.492223e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.858000e-04 | 6.017200e-02 | -0.7581390 | -3.004410e-02 | 2.000000e-04 | 3.025300e-02 | 9.253310e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.085940e-02 | 2.875340e-02 | 0.0276000 | 3.200000e-02 | 3.900000e-02 | 5.660000e-02 | 4.796000e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.886104e-01 | 2.913422e-01 | 0.0000001 | 2.333001e-01 | 4.845002e-01 | 7.408000e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.886109e-01 | 2.913431e-01 | 0.0000001 | 2.333113e-01 | 4.844688e-01 | 7.408540e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.992196e-01 | 2.594497e-01 | 0.0100000 | 8.450000e-02 | 2.162000e-01 | 4.632000e-01 | 9.900000e-01 | ▇▃▂▂▁ |
| numeric | AF_reference | 3 | 0.9999995 | NA | NA | NA | NA | NA | NA | NA | 2.998917e-01 | 2.477603e-01 | 0.0009984 | 9.664540e-02 | 2.204470e-01 | 4.548720e-01 | 9.980030e-01 | ▇▅▂▂▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 752478 | rs146277091 | G | A | 0.1780510 | 0.1244 | 0.1524000 | 0.1523505 | 0.0290 | 0.0277556 | NA |
| 1 | 752566 | rs3094315 | G | A | 0.0484552 | 0.0390 | 0.2144999 | 0.2140739 | 0.4915 | 0.7182510 | NA |
| 1 | 752721 | rs3131972 | A | G | 0.0509776 | 0.0390 | 0.1919999 | 0.1911727 | 0.4151 | 0.6533550 | NA |
| 1 | 753405 | rs3115860 | C | A | 0.0641119 | 0.0387 | 0.0979693 | 0.0975926 | 0.5469 | 0.7517970 | NA |
| 1 | 753541 | rs2073813 | G | A | -0.0399896 | 0.0385 | 0.2993002 | 0.2989485 | 0.4806 | 0.3019170 | NA |
| 1 | 754063 | rs12184312 | G | T | 0.2323100 | 0.1698 | 0.1712999 | 0.1712686 | 0.0234 | 0.0229633 | NA |
| 1 | 754105 | rs12184325 | C | T | 0.1978410 | 0.1301 | 0.1284000 | 0.1283391 | 0.0261 | 0.0269569 | NA |
| 1 | 754182 | rs3131969 | A | G | 0.0593255 | 0.0383 | 0.1212001 | 0.1213893 | 0.4606 | 0.6785140 | NA |
| 1 | 754192 | rs3131968 | A | G | 0.0594316 | 0.0383 | 0.1206999 | 0.1207247 | 0.4605 | 0.6785140 | NA |
| 1 | 754211 | rs12184313 | G | A | 0.1912820 | 0.1264 | 0.1299999 | 0.1302017 | 0.0269 | 0.0281550 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51217954 | rs9616974 | G | A | -0.0012992 | 0.0617 | 0.9827000 | 0.9832009 | 0.0855 | 0.0621006 | NA |
| 22 | 51218224 | rs9616975 | C | A | -0.0005998 | 0.0618 | 0.9928000 | 0.9922560 | 0.0854 | 0.0619010 | NA |
| 22 | 51218377 | rs2519461 | G | C | -0.0222506 | 0.0472 | 0.6374997 | 0.6373473 | 0.1495 | 0.0826677 | NA |
| 22 | 51219006 | rs28729663 | G | A | -0.0012992 | 0.0411 | 0.9751001 | 0.9747833 | 0.3016 | 0.2052720 | NA |
| 22 | 51219387 | rs9616832 | T | C | 0.0059175 | 0.0623 | 0.9246000 | 0.9243280 | 0.0892 | 0.0654952 | NA |
| 22 | 51219704 | rs147475742 | G | A | -0.0048880 | 0.0658 | 0.9408000 | 0.9407827 | 0.0766 | 0.0473243 | NA |
| 22 | 51221731 | rs115055839 | T | C | -0.0034939 | 0.0626 | 0.9559001 | 0.9554908 | 0.0852 | 0.0625000 | NA |
| 22 | 51222100 | rs114553188 | G | T | -0.0533512 | 0.0515 | 0.3004000 | 0.3002275 | 0.1586 | 0.0880591 | NA |
| 22 | 51223637 | rs375798137 | G | A | -0.0489806 | 0.0559 | 0.3804004 | 0.3809114 | 0.1383 | 0.0788738 | NA |
| 22 | 51229805 | rs9616985 | T | C | -0.0214679 | 0.0625 | 0.7314001 | 0.7312326 | 0.1057 | 0.0730831 | NA |
bcf preview
1 752478 rs146277091 G A . PASS AF=0.029 ES:SE:LP:AF:SI:ID 0.178051:0.1244:0.817015:0.029:0.5029:rs146277091
1 752566 rs3094315 G A . PASS AF=0.4915 ES:SE:LP:AF:SI:ID 0.0484552:0.039:0.668573:0.4915:0.5919:rs3094315
1 752721 rs3131972 A G . PASS AF=0.4151 ES:SE:LP:AF:SI:ID 0.0509776:0.039:0.716699:0.4151:0.6149:rs3131972
1 753405 rs3115860 C A . PASS AF=0.5469 ES:SE:LP:AF:SI:ID 0.0641119:0.0387:1.00891:0.5469:0.5992:rs3115860
1 753541 rs1388595942 G A . PASS AF=0.4806 ES:SE:LP:AF:SI:ID -0.0399896:0.0385:0.523893:0.4806:0.6005:rs1388595942
1 754063 rs12184312 G T . PASS AF=0.0234 ES:SE:LP:AF:SI:ID 0.23231:0.1698:0.766243:0.0234:0.3302:rs12184312
1 754105 rs12184325 C T . PASS AF=0.0261 ES:SE:LP:AF:SI:ID 0.197841:0.1301:0.891435:0.0261:0.5107:rs12184325
1 754182 rs3131969 A G . PASS AF=0.4606 ES:SE:LP:AF:SI:ID 0.0593255:0.0383:0.916497:0.4606:0.6163:rs3131969
1 754192 rs3131968 A G . PASS AF=0.4605 ES:SE:LP:AF:SI:ID 0.0594316:0.0383:0.918293:0.4605:0.6166:rs3131968
1 754211 rs12184313 G A . PASS AF=0.0269 ES:SE:LP:AF:SI:ID 0.191282:0.1264:0.886057:0.0269:0.5261:rs12184313
1 754334 rs3131967 T C . PASS AF=0.4628 ES:SE:LP:AF:SI:ID 0.0598562:0.0381:0.935917:0.4628:0.6236:rs3131967
1 754503 rs3115859 G A . PASS AF=0.4418 ES:SE:LP:AF:SI:ID 0.0509776:0.0387:0.72723:0.4418:0.6105:rs3115859
1 754629 rs10454459 A G . PASS AF=0.0265 ES:SE:LP:AF:SI:ID 0.196502:0.1285:0.899285:0.0265:0.5164:rs10454459
1 754964 rs3131966 C T . PASS AF=0.4407 ES:SE:LP:AF:SI:ID 0.0502412:0.0386:0.714218:0.4407:0.612:rs3131966
1 755890 rs1280367067 A T . PASS AF=0.5418 ES:SE:LP:AF:SI:ID 0.0566762:0.0382:0.862329:0.5418:0.6156:rs1280367067
1 756604 rs3131962 A G . PASS AF=0.5368 ES:SE:LP:AF:SI:ID 0.0565704:0.0381:0.862013:0.5368:0.6187:rs3131962
1 757640 rs3115853 G A . PASS AF=0.3722 ES:SE:LP:AF:SI:ID 0.0681718:0.04:1.05217:0.3722:0.6158:rs3115853
1 757734 rs1557551770 C T . PASS AF=0.5335 ES:SE:LP:AF:SI:ID 0.0523465:0.0378:0.77963:0.5335:0.6269:rs1557551770
1 757936 rs1360886751 C A . PASS AF=0.5343 ES:SE:LP:AF:SI:ID 0.0522411:0.0377:0.778586:0.5343:0.6282:rs1360886751
1 758144 rs3131956 A G . PASS AF=0.5262 ES:SE:LP:AF:SI:ID 0.0494004:0.038:0.713993:0.5262:0.6195:rs3131956
1 758626 rs3131954 C T . PASS AF=0.5369 ES:SE:LP:AF:SI:ID 0.057841:0.0375:0.912929:0.5369:0.6381:rs3131954
1 759036 rs114525117 G A . PASS AF=0.0251 ES:SE:LP:AF:SI:ID 0.220397:0.1195:1.18582:0.0251:0.637:rs114525117
1 760912 rs1048488 C T . PASS AF=0.5214 ES:SE:LP:AF:SI:ID 0.0338671:0.0374:0.438422:0.5214:0.6379:rs1048488
1 760998 rs148828841 C A . PASS AF=0.0246 ES:SE:LP:AF:SI:ID 0.222394:0.1237:1.142:0.0246:0.6041:rs148828841
1 761147 rs3115850 T C . PASS AF=0.5207 ES:SE:LP:AF:SI:ID 0.0338671:0.0373:0.438899:0.5207:0.6398:rs3115850
1 761732 rs2286139 C T . PASS AF=0.3465 ES:SE:LP:AF:SI:ID 0.0661398:0.0403:0.996971:0.3465:0.631:rs2286139
1 761881 rs374493323 A C . PASS AF=0.024 ES:SE:LP:AF:SI:ID 0.255538:0.1295:1.31498:0.024:0.5696:rs374493323
1 763394 rs3115847 G A . PASS AF=0.3813 ES:SE:LP:AF:SI:ID 0.0455205:0.0393:0.608888:0.3813:0.6228:rs3115847
1 768253 rs2977608 A C . PASS AF=0.2696 ES:SE:LP:AF:SI:ID 0.0669949:0.0464:0.828859:0.2696:0.5542:rs2977608
1 768448 rs12562034 G A . PASS AF=0.1049 ES:SE:LP:AF:SI:ID 0.0717108:0.0716:0.499489:0.1049:0.4545:rs12562034
1 769223 rs60320384 C G . PASS AF=0.313 ES:SE:LP:AF:SI:ID -0.0641009:0.039:0.998699:0.313:0.6654:rs60320384
1 771823 rs2977605 T C . PASS AF=0.5219 ES:SE:LP:AF:SI:ID 0.0406137:0.0358:0.590913:0.5219:0.6996:rs2977605
1 771967 rs59066358 G A . PASS AF=0.3676 ES:SE:LP:AF:SI:ID -0.0350775:0.0369:0.467373:0.3676:0.6956:rs59066358
1 772755 rs2905039 A C . PASS AF=0.5317 ES:SE:LP:AF:SI:ID 0.0426988:0.0363:0.620332:0.5317:0.6809:rs2905039
1 777122 rs2980319 A T . PASS AF=0.5123 ES:SE:LP:AF:SI:ID 0.0364565:0.0352:0.522589:0.5123:0.7215:rs2980319
1 777232 rs112618790 C T . PASS AF=0.0299 ES:SE:LP:AF:SI:ID 0.132618:0.1292:0.51627:0.0299:0.4589:rs112618790
1 778745 rs1055606 A G . PASS AF=0.3718 ES:SE:LP:AF:SI:ID -0.0306262:0.0363:0.399027:0.3718:0.7111:rs1055606
1 779322 rs4040617 A G . PASS AF=0.4136 ES:SE:LP:AF:SI:ID -0.0268367:0.0354:0.34727:0.4136:0.7227:rs4040617
1 780785 rs2977612 T A . PASS AF=0.4253 ES:SE:LP:AF:SI:ID 0.0357308:0.0355:0.501552:0.4253:0.7281:rs2977612
1 781845 rs1391043716 A G . PASS AF=0.0638 ES:SE:LP:AF:SI:ID -0.0962189:0.1064:0.436638:0.0638:0.3142:rs1391043716
1 782981 rs6594026 C T . PASS AF=0.4966 ES:SE:LP:AF:SI:ID -0.0236189:0.0351:0.300422:0.4966:0.7195:rs6594026
1 785050 rs2905062 G A . PASS AF=0.3169 ES:SE:LP:AF:SI:ID 0.0521358:0.0383:0.760701:0.3169:0.7362:rs2905062
1 785989 rs2980300 T C . PASS AF=0.3167 ES:SE:LP:AF:SI:ID 0.0528735:0.0383:0.776245:0.3167:0.7383:rs2980300
1 787399 rs2905055 G T . PASS AF=0.3453 ES:SE:LP:AF:SI:ID 0.0509776:0.0374:0.761703:0.3453:0.7293:rs2905055
1 787606 rs3863622 G T . PASS AF=0.4159 ES:SE:LP:AF:SI:ID -0.026155:0.0356:0.334888:0.4159:0.7144:rs3863622
1 787685 rs2905054 G T . PASS AF=0.3119 ES:SE:LP:AF:SI:ID 0.0503464:0.0383:0.723079:0.3119:0.7427:rs2905054
1 787844 rs2905053 C T . PASS AF=0.3461 ES:SE:LP:AF:SI:ID 0.056782:0.0371:0.899974:0.3461:0.7418:rs2905053
1 790465 rs61768207 G A . PASS AF=0.2621 ES:SE:LP:AF:SI:ID -0.0808424:0.0411:1.30583:0.2621:0.6581:rs61768207
1 791191 rs111818025 G A . PASS AF=0.4019 ES:SE:LP:AF:SI:ID -0.024595:0.0363:0.301551:0.4019:0.6909:rs111818025
1 791853 rs6684487 G A . PASS AF=0.05 ES:SE:LP:AF:SI:ID 0.125903:0.0798:0.940815:0.05:0.731:rs6684487