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/23349aae-87a5-40a3-b7ba-adabdac704ac/call-vcf/inputs/-261044512/upload.txt.gz --id ieu-b-4820 --json /data/cromwell-executions/qc/23349aae-87a5-40a3-b7ba-adabdac704ac/call-vcf/inputs/-261044512/ieu-b-4820_data.json --ref /data/cromwell-executions/qc/23349aae-87a5-40a3-b7ba-adabdac704ac/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/23349aae-87a5-40a3-b7ba-adabdac704ac/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4820/ieu-b-4820.vcf.gz --alias alias.txt; 1.3.0",
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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/23349aae-87a5-40a3-b7ba-adabdac704ac/call-ldsc/inputs/-261044512/ieu-b-4820.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4820/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Wed Jan 5 04:43:58 2022
Reading summary statistics from /data/cromwell-executions/qc/23349aae-87a5-40a3-b7ba-adabdac704ac/call-ldsc/inputs/-261044512/ieu-b-4820.vcf.gz ...
Read summary statistics for 6046988 SNPs.
Dropped 16724 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, 1152796 SNPs remain.
After merging with regression SNP LD, 1152796 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0654 (0.0156)
Lambda GC: 1.0953
Mean Chi^2: 1.0978
Intercept: 1.057 (0.0066)
Ratio: 0.5826 (0.067)
Analysis finished at Wed Jan 5 04:45:22 2022
Total time elapsed: 1.0m:24.47sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.0986,
"mean_EFFECT": -0.0011,
"n": 32696,
"n_snps": 6047010,
"n_clumped_hits": 1,
"n_p_sig": 22,
"n_mono": 0,
"n_ns": 0,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 6047010,
"n_miss_AF_reference": 39453,
"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": 1152796,
"ldsc_nsnp_merge_regression_ld": 1152796,
"ldsc_observed_scale_h2_beta": 0.0654,
"ldsc_observed_scale_h2_se": 0.0156,
"ldsc_intercept_beta": 1.057,
"ldsc_intercept_se": 0.0066,
"ldsc_lambda_gc": 1.0953,
"ldsc_mean_chisq": 1.0978,
"ldsc_ratio": 0.5828
}
Flags
| name | value |
|---|---|
| af_correlation | NA |
| inflation_factor | FALSE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| 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 | 6 | 0.9999990 | 3 | 58 | 0 | 6046991 | 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 | AF | 6047010 | 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 | 8.630937e+00 | 5.740717e+00 | 1.0000e+00 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
| numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.888937e+07 | 5.640061e+07 | 8.2800e+02 | 3.241012e+07 | 6.951510e+07 | 1.147393e+08 | 2.492223e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -1.068900e-03 | 5.663860e-02 | -4.8590e-01 | -3.320000e-02 | -8.000000e-04 | 3.130000e-02 | 4.606000e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.022720e-02 | 1.993270e-02 | 3.1000e-02 | 3.490000e-02 | 4.210000e-02 | 5.940000e-02 | 1.331000e-01 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.849753e-01 | 2.928522e-01 | 0.0000e+00 | 2.272998e-01 | 4.795998e-01 | 7.388002e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.849754e-01 | 2.928529e-01 | 0.0000e+00 | 2.272665e-01 | 4.796308e-01 | 7.388827e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF_reference | 39453 | 0.9934756 | NA | NA | NA | NA | NA | NA | NA | 3.043527e-01 | 2.467845e-01 | 1.9970e-04 | 1.018370e-01 | 2.318290e-01 | 4.628590e-01 | 1.000000e+00 | ▇▅▂▂▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.044013e+04 | 2.847591e+03 | 1.9631e+04 | 3.001500e+04 | 3.104600e+04 | 3.269600e+04 | 3.269600e+04 | ▁▁▁▁▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 797440 | rs58013264 | T | C | -0.0349 | 0.0579 | 0.5471999 | 0.5466661 | NA | 0.189497 | 24754 |
| 1 | 798400 | rs10900604 | A | G | 0.0377 | 0.0478 | 0.4294000 | 0.4302857 | NA | 0.410543 | 25258 |
| 1 | 798959 | rs11240777 | G | A | 0.0403 | 0.0416 | 0.3324000 | 0.3326699 | NA | 0.409944 | 30390 |
| 1 | 801467 | rs61768212 | G | C | -0.0323 | 0.0583 | 0.5796996 | 0.5795577 | NA | 0.193091 | 24227 |
| 1 | 804759 | rs7526310 | C | T | -0.0382 | 0.0583 | 0.5126005 | 0.5123187 | NA | 0.193890 | 24227 |
| 1 | 808631 | rs11240779 | G | A | -0.0345 | 0.0458 | 0.4508998 | 0.4512846 | NA | 0.453474 | 25258 |
| 1 | 808928 | rs11240780 | C | T | -0.0338 | 0.0458 | 0.4610001 | 0.4605198 | NA | 0.452276 | 25258 |
| 1 | 845635 | rs117086422 | C | T | -0.0145 | 0.0416 | 0.7272002 | 0.7274214 | NA | 0.158546 | 30390 |
| 1 | 845938 | rs57760052 | G | A | -0.0066 | 0.0413 | 0.8721000 | 0.8730337 | NA | 0.363419 | 30390 |
| 1 | 846078 | rs28612348 | C | T | -0.0111 | 0.0431 | 0.7975000 | 0.7967615 | NA | 0.161741 | 30390 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51213613 | rs34726907 | C | T | -0.0914 | 0.0621 | 0.1405999 | 0.1410696 | NA | 0.1727240 | 21261 |
| 22 | 51216564 | rs9616970 | T | C | -0.0913 | 0.0621 | 0.1412001 | 0.1415051 | NA | 0.1563500 | 21261 |
| 22 | 51217954 | rs9616974 | G | A | -0.0455 | 0.0799 | 0.5686002 | 0.5690428 | NA | 0.0621006 | 20734 |
| 22 | 51218224 | rs9616975 | C | A | -0.0455 | 0.0799 | 0.5686002 | 0.5690428 | NA | 0.0619010 | 20734 |
| 22 | 51218377 | rs2519461 | G | C | -0.0437 | 0.0798 | 0.5843002 | 0.5839535 | NA | 0.0826677 | 20734 |
| 22 | 51219387 | rs9616832 | T | C | -0.0446 | 0.0795 | 0.5743002 | 0.5747932 | NA | 0.0654952 | 20734 |
| 22 | 51221731 | rs115055839 | T | C | -0.0468 | 0.0800 | 0.5590002 | 0.5585477 | NA | 0.0625000 | 20734 |
| 22 | 51222100 | rs114553188 | G | T | -0.1080 | 0.0933 | 0.2470000 | 0.2470452 | NA | 0.0880591 | 20782 |
| 22 | 51223637 | rs375798137 | G | A | -0.1099 | 0.0938 | 0.2412998 | 0.2413409 | NA | 0.0788738 | 20782 |
| 22 | 51229805 | rs9616985 | T | C | -0.0402 | 0.0800 | 0.6153993 | 0.6153159 | NA | 0.0730831 | 20734 |
bcf preview
1 797440 rs58013264 T C . PASS . ES:SE:LP:SS:ID -0.0349:0.0579:0.261854:24754:rs58013264
1 798400 rs10900604 A G . PASS . ES:SE:LP:SS:ID 0.0377:0.0478:0.367138:25258:rs10900604
1 798959 rs11240777 G A . PASS . ES:SE:LP:SS:ID 0.0403:0.0416:0.478339:30390:rs11240777
1 801467 rs61768212 G C . PASS . ES:SE:LP:SS:ID -0.0323:0.0583:0.236797:24227:rs61768212
1 804759 rs7526310 C T . PASS . ES:SE:LP:SS:ID -0.0382:0.0583:0.290221:24227:rs7526310
1 808631 rs11240779 G A . PASS . ES:SE:LP:SS:ID -0.0345:0.0458:0.34592:25258:rs11240779
1 808928 rs1247187939 C T . PASS . ES:SE:LP:SS:ID -0.0338:0.0458:0.336299:25258:rs1247187939
1 845635 rs117086422 C T . PASS . ES:SE:LP:SS:ID -0.0145:0.0416:0.138346:30390:rs117086422
1 845938 rs57760052 G A . PASS . ES:SE:LP:SS:ID -0.0066:0.0413:0.0594337:30390:rs57760052
1 846078 rs778265812 C T . PASS . ES:SE:LP:SS:ID -0.0111:0.0431:0.0982693:30390:rs778265812
1 846398 rs58781670 G A . PASS . ES:SE:LP:SS:ID -0.0158:0.0417:0.151503:30390:rs58781670
1 846808 rs4475691 C T . PASS . ES:SE:LP:SS:ID -0.0058:0.0428:0.0492945:30390:rs4475691
1 846864 rs1269142199 G C . PASS . ES:SE:LP:SS:ID -0.0163:0.0431:0.151503:30390:rs1269142199
1 847228 rs3905286 C T . PASS . ES:SE:LP:SS:ID -0.0096:0.0423:0.0857626:30390:rs3905286
1 847491 rs1158719307 G A . PASS . ES:SE:LP:SS:ID 0.0031:0.0418:0.0264565:30390:rs1158719307
1 848090 rs4246505 G A . PASS . ES:SE:LP:SS:ID -0.0022:0.042:0.0184079:30390:rs4246505
1 848445 rs1156895099 G A . PASS . ES:SE:LP:SS:ID 0.0084:0.0419:0.0748427:30390:rs1156895099
1 848456 rs11507767 A G . PASS . ES:SE:LP:SS:ID 0.0077:0.0419:0.0686439:30390:rs11507767
1 848738 rs3829741 C T . PASS . ES:SE:LP:SS:ID -0.0022:0.042:0.0188159:30390:rs3829741
1 850062 rs28723578 A T . PASS . ES:SE:LP:SS:ID -0.0012:0.0418:0.00970555:30390:rs28723578
1 850123 rs28622257 C T . PASS . ES:SE:LP:SS:ID -0.0062:0.042:0.0537934:30390:rs28622257
1 851190 rs28609852 G A . PASS . ES:SE:LP:SS:ID 0.0026:0.0418:0.0222307:30390:rs28609852
1 851204 rs28552953 G C . PASS . ES:SE:LP:SS:ID -0.0043:0.0415:0.037536:30390:rs28552953
1 852664 rs28605311 C T . PASS . ES:SE:LP:SS:ID -0.0017:0.0424:0.0139004:30390:rs28605311
1 852758 rs4970462 G C . PASS . ES:SE:LP:SS:ID -0.0017:0.0424:0.0137659:30390:rs4970462
1 853239 rs4970380 A G . PASS . ES:SE:LP:SS:ID -0.002:0.0424:0.0167346:30390:rs4970380
1 854250 rs7537756 A G . PASS . ES:SE:LP:SS:ID 0.0021:0.0421:0.0172766:30390:rs7537756
1 856476 rs4040605 A G . PASS . ES:SE:LP:SS:ID 0.0686:0.04:1.06213:25258:rs4040605
1 858040 rs4970460 C A . PASS . ES:SE:LP:SS:ID 0.0169:0.0473:0.141944:25258:rs4970460
1 858051 rs4970459 C T . PASS . ES:SE:LP:SS:ID 0.0171:0.0472:0.144481:25258:rs4970459
1 858801 rs7418179 A G . PASS . ES:SE:LP:SS:ID -0.0414:0.0454:0.441531:25258:rs7418179
1 860416 rs61464428 G A . PASS . ES:SE:LP:SS:ID -0.0518:0.0456:0.592949:25258:rs61464428
1 860688 rs60837925 G A . PASS . ES:SE:LP:SS:ID -0.0494:0.0455:0.555487:25258:rs60837925
1 861630 rs2879816 G A . PASS . ES:SE:LP:SS:ID -0.0509:0.0456:0.578725:25258:rs2879816
1 862866 rs3892970 C T . PASS . ES:SE:LP:SS:ID -0.045:0.0453:0.494307:25258:rs3892970
1 864002 rs1806501 G C . PASS . ES:SE:LP:SS:ID 0.0416:0.0472:0.422853:25258:rs1806501
1 864938 rs1185651409 G A . PASS . ES:SE:LP:SS:ID -0.0237:0.0447:0.2249:25258:rs1185651409
1 865219 rs75551395 G A . PASS . ES:SE:LP:SS:ID 0.0226:0.047:0.200591:25258:rs75551395
1 866893 rs2880024 T C . PASS . ES:SE:LP:SS:ID -0.0393:0.039:0.503347:25258:rs2880024
1 866938 rs74047407 G A . PASS . ES:SE:LP:SS:ID 0.0186:0.0455:0.165834:25258:rs74047407
1 867635 rs76964081 C T . PASS . ES:SE:LP:SS:ID 0.0308:0.047:0.290985:25258:rs76964081
1 870645 rs28576697 T C . PASS . ES:SE:LP:SS:ID 0.0947:0.0424:1.59329:25258:rs28576697
1 871334 rs4072383 G T . PASS . ES:SE:LP:SS:ID -0.0913:0.042:1.52593:25258:rs4072383
1 872352 rs1445142858 G C . PASS . ES:SE:LP:SS:ID 0.1091:0.0429:1.95624:25258:rs1445142858
1 873558 rs1110052 G T . PASS . ES:SE:LP:SS:ID -0.0867:0.0419:1.41218:25258:rs1110052
1 875770 rs4970379 A G . PASS . ES:SE:LP:SS:ID -0.0786:0.0394:1.33611:25258:rs4970379
1 876499 rs755331663 A G . PASS . ES:SE:LP:SS:ID -0.0697:0.0834:0.394479:25824:rs755331663
1 877147 rs114982608 G A . PASS . ES:SE:LP:SS:ID 0.1015:0.0438:1.6855:25258:rs114982608
1 879676 rs6605067 G A . PASS . ES:SE:LP:SS:ID -0.0825:0.0821:0.501138:25824:rs6605067
1 879687 rs2839 T C . PASS . ES:SE:LP:SS:ID -0.0692:0.0834:0.391046:25824:rs2839