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/51f47113-cab2-4300-98e6-c77337b16c17/call-vcf/inputs/-261021507/upload.txt.gz --id ieu-b-5103 --json /data/cromwell-executions/qc/51f47113-cab2-4300-98e6-c77337b16c17/call-vcf/inputs/-261021507/ieu-b-5103_data.json --ref /data/cromwell-executions/qc/51f47113-cab2-4300-98e6-c77337b16c17/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/51f47113-cab2-4300-98e6-c77337b16c17/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-5103/ieu-b-5103.vcf.gz --alias alias.txt --cohort_cases 1234 --cohort_controls 3090; 1.3.0",
"file_date": "2023-02-03T13:19:43.127683",
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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/51f47113-cab2-4300-98e6-c77337b16c17/call-ldsc/inputs/-261021507/ieu-b-5103.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-5103/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Fri Feb 3 13:29:01 2023
Reading summary statistics from /data/cromwell-executions/qc/51f47113-cab2-4300-98e6-c77337b16c17/call-ldsc/inputs/-261021507/ieu-b-5103.vcf.gz ...
Read summary statistics for 6861083 SNPs.
Dropped 19109 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, 1199481 SNPs remain.
After merging with regression SNP LD, 1199481 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.3594 (0.1243)
Lambda GC: 1.0986
Mean Chi^2: 1.0901
Intercept: 1.0597 (0.0074)
Ratio: 0.6634 (0.0816)
Analysis finished at Fri Feb 3 13:30:40 2023
Total time elapsed: 1.0m:38.88sQC metrics
Metrics
Metrics
{
"af_correlation": 0.9573,
"inflation_factor": 1.0911,
"mean_EFFECT": -0.0014,
"n": "-Inf",
"n_snps": 6861099,
"n_clumped_hits": 1,
"n_p_sig": 8,
"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": 2,
"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": 1199481,
"ldsc_nsnp_merge_regression_ld": 1199481,
"ldsc_observed_scale_h2_beta": 0.3594,
"ldsc_observed_scale_h2_se": 0.1243,
"ldsc_intercept_beta": 1.0597,
"ldsc_intercept_se": 0.0074,
"ldsc_lambda_gc": 1.0986,
"ldsc_mean_chisq": 1.0901,
"ldsc_ratio": 0.6626
}
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 | 6861099 | 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 | 6861099 | 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 | 8.659214e+00 | 5.758258e+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 | 7.874019e+07 | 5.648021e+07 | 828.0000000 | 3.221169e+07 | 6.923668e+07 | 1.146645e+08 | 2.492223e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.395600e-03 | 1.117640e-01 | -1.8301100 | -5.467760e-02 | -2.000000e-04 | 5.382280e-02 | 1.194020e+00 | ▁▁▆▇▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 9.324170e-02 | 5.394470e-02 | 0.0453000 | 5.440000e-02 | 6.950000e-02 | 1.132000e-01 | 6.781000e-01 | ▇▁▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.865238e-01 | 2.919920e-01 | 0.0000000 | 2.301002e-01 | 4.810996e-01 | 7.392001e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.865238e-01 | 2.919921e-01 | 0.0000000 | 2.301305e-01 | 4.810562e-01 | 7.392381e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.790769e-01 | 2.645571e-01 | 0.0100000 | 5.540000e-02 | 1.862000e-01 | 4.422000e-01 | 9.900000e-01 | ▇▃▂▂▁ |
| numeric | AF_reference | 2 | 0.9999997 | NA | NA | NA | NA | NA | NA | NA | 2.784143e-01 | 2.509933e-01 | 0.0009984 | 7.368210e-02 | 1.946880e-01 | 4.293130e-01 | 9.978040e-01 | ▇▃▂▂▁ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 752478 | rs146277091 | G | A | 0.306525 | 0.1934 | 0.1131001 | 0.1129828 | 0.0240 | 0.0277556 | NA |
| 1 | 752566 | rs3094315 | G | A | -0.183488 | 0.0732 | 0.0121801 | 0.0121876 | 0.7655 | 0.7182510 | NA |
| 1 | 752721 | rs3131972 | A | G | -0.174289 | 0.0701 | 0.0129700 | 0.0129082 | 0.7062 | 0.6533550 | NA |
| 1 | 753405 | rs3115860 | C | A | -0.168814 | 0.0766 | 0.0274303 | 0.0275357 | 0.7907 | 0.7517970 | NA |
| 1 | 753541 | rs2073813 | G | A | 0.129881 | 0.0741 | 0.0797003 | 0.0796398 | 0.2584 | 0.3019170 | NA |
| 1 | 754063 | rs12184312 | G | T | 0.331286 | 0.1865 | 0.0756798 | 0.0756781 | 0.0222 | 0.0229633 | NA |
| 1 | 754105 | rs12184325 | C | T | 0.310337 | 0.1946 | 0.1108001 | 0.1107697 | 0.0229 | 0.0269569 | NA |
| 1 | 754182 | rs3131969 | A | G | -0.150831 | 0.0722 | 0.0367401 | 0.0367012 | 0.7293 | 0.6785140 | NA |
| 1 | 754192 | rs3131968 | A | G | -0.150573 | 0.0722 | 0.0369301 | 0.0370241 | 0.7293 | 0.6785140 | NA |
| 1 | 754211 | rs12184313 | G | A | 0.299215 | 0.1894 | 0.1142000 | 0.1141516 | 0.0240 | 0.0281550 | NA |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51218224 | rs9616975 | C | A | 0.0204068 | 0.1321 | 0.8771000 | 0.8772313 | 0.0444 | 0.0619010 | NA |
| 22 | 51218377 | rs2519461 | G | C | -0.0128175 | 0.1246 | 0.9183000 | 0.9180668 | 0.0522 | 0.0826677 | NA |
| 22 | 51219006 | rs28729663 | G | A | -0.0360426 | 0.0854 | 0.6731006 | 0.6729925 | 0.1931 | 0.2052720 | NA |
| 22 | 51219387 | rs9616832 | T | C | 0.0296348 | 0.1330 | 0.8238000 | 0.8236771 | 0.0463 | 0.0654952 | NA |
| 22 | 51219704 | rs147475742 | G | A | 0.1442170 | 0.1696 | 0.3952001 | 0.3951383 | 0.0292 | 0.0473243 | NA |
| 22 | 51221731 | rs115055839 | T | C | 0.0204068 | 0.1328 | 0.8780000 | 0.8778734 | 0.0446 | 0.0625000 | NA |
| 22 | 51222100 | rs114553188 | G | T | 0.0772051 | 0.1647 | 0.6394005 | 0.6392398 | 0.0415 | 0.0880591 | NA |
| 22 | 51223637 | rs375798137 | G | A | 0.0584769 | 0.1722 | 0.7343008 | 0.7341675 | 0.0396 | 0.0788738 | NA |
| 22 | 51229805 | rs9616985 | T | C | 0.0147076 | 0.1409 | 0.9168000 | 0.9168652 | 0.0485 | 0.0730831 | NA |
| 22 | 51237063 | rs3896457 | T | C | 0.1537340 | 0.0915 | 0.0929202 | 0.0929276 | 0.2551 | 0.2050720 | NA |
bcf preview
1 752478 rs146277091 G A . PASS AF=0.024 ES:SE:LP:AF:SI:ID 0.306525:0.1934:0.946537:0.024:0.6554:rs146277091
1 752566 rs3094315 G A . PASS AF=0.7655 ES:SE:LP:AF:SI:ID -0.183488:0.0732:1.91435:0.7655:0.6486:rs3094315
1 752721 rs3131972 A G . PASS AF=0.7062 ES:SE:LP:AF:SI:ID -0.174289:0.0701:1.88706:0.7062:0.6096:rs3131972
1 753405 rs3115860 C A . PASS AF=0.7907 ES:SE:LP:AF:SI:ID -0.168814:0.0766:1.56177:0.7907:0.6458:rs3115860
1 753541 rs1388595942 G A . PASS AF=0.2584 ES:SE:LP:AF:SI:ID 0.129881:0.0741:1.09854:0.2584:0.5989:rs1388595942
1 754063 rs12184312 G T . PASS AF=0.0222 ES:SE:LP:AF:SI:ID 0.331286:0.1865:1.12102:0.0222:0.7555:rs12184312
1 754105 rs12184325 C T . PASS AF=0.0229 ES:SE:LP:AF:SI:ID 0.310337:0.1946:0.95546:0.0229:0.6765:rs12184325
1 754182 rs3131969 A G . PASS AF=0.7293 ES:SE:LP:AF:SI:ID -0.150831:0.0722:1.43486:0.7293:0.6087:rs3131969
1 754192 rs3131968 A G . PASS AF=0.7293 ES:SE:LP:AF:SI:ID -0.150573:0.0722:1.43262:0.7293:0.6093:rs3131968
1 754211 rs12184313 G A . PASS AF=0.024 ES:SE:LP:AF:SI:ID 0.299215:0.1894:0.942334:0.024:0.6839:rs12184313
1 754334 rs3131967 T C . PASS AF=0.73 ES:SE:LP:AF:SI:ID -0.148765:0.0718:1.41556:0.73:0.6158:rs3131967
1 754503 rs3115859 G A . PASS AF=0.7098 ES:SE:LP:AF:SI:ID -0.178732:0.0696:1.9897:0.7098:0.6251:rs3115859
1 754629 rs10454459 A G . PASS AF=0.0236 ES:SE:LP:AF:SI:ID 0.287549:0.191:0.878112:0.0236:0.687:rs10454459
1 754964 rs3131966 C T . PASS AF=0.7096 ES:SE:LP:AF:SI:ID -0.175213:0.0694:1.93817:0.7096:0.6296:rs3131966
1 755890 rs1280367067 A T . PASS AF=0.7909 ES:SE:LP:AF:SI:ID -0.161183:0.0747:1.51004:0.7909:0.6804:rs1280367067
1 756604 rs3131962 A G . PASS AF=0.7878 ES:SE:LP:AF:SI:ID -0.158882:0.0742:1.48999:0.7878:0.6815:rs3131962
1 757640 rs3115853 G A . PASS AF=0.7161 ES:SE:LP:AF:SI:ID -0.126633:0.0688:1.18237:0.7161:0.6517:rs3115853
1 757734 rs1557551770 C T . PASS AF=0.7891 ES:SE:LP:AF:SI:ID -0.154265:0.0736:1.44129:0.7891:0.6961:rs1557551770
1 757936 rs1360886751 C A . PASS AF=0.7898 ES:SE:LP:AF:SI:ID -0.155122:0.0735:1.4593:0.7898:0.7009:rs1360886751
1 758144 rs3131956 A G . PASS AF=0.7804 ES:SE:LP:AF:SI:ID -0.176555:0.0727:1.81873:0.7804:0.6914:rs3131956
1 758626 rs3131954 C T . PASS AF=0.7921 ES:SE:LP:AF:SI:ID -0.154436:0.0729:1.46737:0.7921:0.7189:rs3131954
1 759036 rs114525117 G A . PASS AF=0.0232 ES:SE:LP:AF:SI:ID 0.275622:0.1835:0.875496:0.0232:0.7546:rs114525117
1 760912 rs1048488 C T . PASS AF=0.7745 ES:SE:LP:AF:SI:ID -0.177811:0.0699:1.96257:0.7745:0.7344:rs1048488
1 760998 rs148828841 C A . PASS AF=0.0233 ES:SE:LP:AF:SI:ID 0.282894:0.1866:0.88773:0.0233:0.7258:rs148828841
1 761147 rs3115850 T C . PASS AF=0.7742 ES:SE:LP:AF:SI:ID -0.177309:0.0697:1.96019:0.7742:0.7377:rs3115850
1 761732 rs2286139 C T . PASS AF=0.7079 ES:SE:LP:AF:SI:ID -0.122837:0.0671:1.17231:0.7079:0.675:rs2286139
1 761881 rs374493323 A C . PASS AF=0.0231 ES:SE:LP:AF:SI:ID 0.287016:0.1921:0.869023:0.0231:0.6932:rs374493323
1 763394 rs3115847 G A . PASS AF=0.6831 ES:SE:LP:AF:SI:ID -0.14773:0.0699:1.4613:0.6831:0.5953:rs3115847
1 766007 rs61768174 A C . PASS AF=0.127 ES:SE:LP:AF:SI:ID 0.141794:0.0915:0.916139:0.127:0.687:rs61768174
1 768253 rs2977608 A C . PASS AF=0.6578 ES:SE:LP:AF:SI:ID -0.112257:0.0656:1.05943:0.6578:0.6708:rs2977608
1 768448 rs12562034 G A . PASS AF=0.1077 ES:SE:LP:AF:SI:ID 0.00230265:0.1166:0.0070049:0.1077:0.486:rs12562034
1 768819 rs12562811 C T . PASS AF=0.0449 ES:SE:LP:AF:SI:ID -0.182072:0.1914:0.466609:0.0449:0.3846:rs12562811
1 769223 rs60320384 C G . PASS AF=0.1811 ES:SE:LP:AF:SI:ID 0.112945:0.0723:0.92775:0.1811:0.8222:rs60320384
1 770377 rs112563271 A T . PASS AF=0.0393 ES:SE:LP:AF:SI:ID -0.209045:0.1926:0.556581:0.0393:0.4264:rs112563271
1 771823 rs2977605 T C . PASS AF=0.7942 ES:SE:LP:AF:SI:ID -0.124604:0.0675:1.18735:0.7942:0.8505:rs2977605
1 771967 rs59066358 G A . PASS AF=0.186 ES:SE:LP:AF:SI:ID 0.0951902:0.0701:0.758454:0.186:0.8616:rs59066358
1 772755 rs2905039 A C . PASS AF=0.7964 ES:SE:LP:AF:SI:ID -0.124516:0.0678:1.17849:0.7964:0.8505:rs2905039
1 773106 rs115616822 G A . PASS AF=0.0357 ES:SE:LP:AF:SI:ID -0.217367:0.2345:0.451242:0.0357:0.402:rs115616822
1 777122 rs2980319 A T . PASS AF=0.7952 ES:SE:LP:AF:SI:ID -0.132431:0.066:1.34795:0.7952:0.8874:rs2980319
1 777232 rs112618790 C T . PASS AF=0.0489 ES:SE:LP:AF:SI:ID 0.124317:0.14:0.426316:0.0489:0.6504:rs112618790
1 778745 rs1055606 A G . PASS AF=0.1858 ES:SE:LP:AF:SI:ID 0.11015:0.0687:0.963371:0.1858:0.8889:rs1055606
1 779322 rs4040617 A G . PASS AF=0.1916 ES:SE:LP:AF:SI:ID 0.112609:0.0674:1.02292:0.1916:0.8998:rs4040617
1 780785 rs2977612 T A . PASS AF=0.7315 ES:SE:LP:AF:SI:ID -0.116716:0.0623:1.21446:0.7315:0.8276:rs2977612
1 781845 rs1391043716 A G . PASS AF=0.1257 ES:SE:LP:AF:SI:ID 0.144795:0.0884:0.993106:0.1257:0.7384:rs1391043716
1 782981 rs6594026 C T . PASS AF=0.2538 ES:SE:LP:AF:SI:ID 0.0953002:0.0638:0.869345:0.2538:0.8233:rs6594026
1 783071 rs142849724 C T . PASS AF=0.0111 ES:SE:LP:AF:SI:ID 0.123411:0.3738:0.129947:0.0111:0.4018:rs142849724
1 785050 rs2905062 G A . PASS AF=0.7179 ES:SE:LP:AF:SI:ID -0.102827:0.0608:1.04191:0.7179:0.841:rs2905062
1 785989 rs2980300 T C . PASS AF=0.7178 ES:SE:LP:AF:SI:ID -0.102557:0.0607:1.03891:0.7178:0.8423:rs2980300
1 787399 rs2905055 G T . PASS AF=0.7202 ES:SE:LP:AF:SI:ID -0.10472:0.0613:1.05854:0.7202:0.832:rs2905055
1 787606 rs3863622 G T . PASS AF=0.19 ES:SE:LP:AF:SI:ID 0.111938:0.069:0.979639:0.19:0.8631:rs3863622