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/98a00699-fda1-4c41-a13f-86bd0ceec3e0/call-vcf/inputs/-261044474/upload.txt.gz --id ieu-b-4837 --json /data/cromwell-executions/qc/98a00699-fda1-4c41-a13f-86bd0ceec3e0/call-vcf/inputs/-261044474/ieu-b-4837_data.json --ref /data/cromwell-executions/qc/98a00699-fda1-4c41-a13f-86bd0ceec3e0/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/98a00699-fda1-4c41-a13f-86bd0ceec3e0/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4837/ieu-b-4837.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/98a00699-fda1-4c41-a13f-86bd0ceec3e0/call-ldsc/inputs/-261044474/ieu-b-4837.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4837/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Wed Jan 5 12:39:36 2022
Reading summary statistics from /data/cromwell-executions/qc/98a00699-fda1-4c41-a13f-86bd0ceec3e0/call-ldsc/inputs/-261044474/ieu-b-4837.vcf.gz ...
Read summary statistics for 6719230 SNPs.
Dropped 18738 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, 1186489 SNPs remain.
After merging with regression SNP LD, 1186489 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1276 (0.0436)
Lambda GC: 1.0368
Mean Chi^2: 1.0396
Intercept: 1.012 (0.0061)
Ratio: 0.3025 (0.1529)
Analysis finished at Wed Jan 5 12:41:12 2022
Total time elapsed: 1.0m:35.56sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.0292,
"mean_EFFECT": 0,
"n": 11302,
"n_snps": 6719302,
"n_clumped_hits": 0,
"n_p_sig": 0,
"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": 6719302,
"n_miss_AF_reference": 53316,
"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": 1186489,
"ldsc_nsnp_merge_regression_ld": 1186489,
"ldsc_observed_scale_h2_beta": 0.1276,
"ldsc_observed_scale_h2_se": 0.0436,
"ldsc_intercept_beta": 1.012,
"ldsc_intercept_se": 0.0061,
"ldsc_lambda_gc": 1.0368,
"ldsc_mean_chisq": 1.0396,
"ldsc_ratio": 0.303
}
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 | FALSE |
| 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 | 45 | 0.9999933 | 3 | 58 | 0 | 6719206 | 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 | 6719302 | 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 | 8.660922e+00 | 5.761272e+00 | 1.000e+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 | 7.862500e+07 | 5.646681e+07 | 8.280e+02 | 3.212334e+07 | 6.907324e+07 | 1.145122e+08 | 2.492385e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.290000e-05 | 2.600020e-02 | -2.392e-01 | -1.330000e-02 | 0.000000e+00 | 1.330000e-02 | 2.267000e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.288930e-02 | 1.166090e-02 | 1.220e-02 | 1.400000e-02 | 1.760000e-02 | 2.890000e-02 | 7.460000e-02 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.951025e-01 | 2.902457e-01 | 3.000e-07 | 2.421001e-01 | 4.937999e-01 | 7.468992e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.951035e-01 | 2.902491e-01 | 2.000e-07 | 2.420769e-01 | 4.938422e-01 | 7.468205e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF_reference | 53316 | 0.9920652 | NA | NA | NA | NA | NA | NA | NA | 2.828646e-01 | 2.508425e-01 | 1.997e-04 | 7.727640e-02 | 2.032750e-01 | 4.369010e-01 | 1.000000e+00 | ▇▃▂▂▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.026034e+04 | 1.180642e+03 | 7.285e+03 | 9.283000e+03 | 1.094000e+04 | 1.130200e+04 | 1.130200e+04 | ▂▁▃▂▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 49298 | rs200943160 | T | C | -0.0019 | 0.0156 | 0.9023001 | 0.9030615 | NA | 0.7821490 | 8201 |
| 1 | 54676 | rs2462492 | C | T | -0.0217 | 0.0164 | 0.1855000 | 0.1857786 | NA | NA | 8201 |
| 1 | 86028 | rs114608975 | T | C | -0.0011 | 0.0305 | 0.9713000 | 0.9712301 | NA | 0.0277556 | 7911 |
| 1 | 91536 | rs6702460 | G | T | -0.0309 | 0.0158 | 0.0499701 | 0.0505010 | NA | 0.4207270 | 8201 |
| 1 | 234313 | rs8179466 | C | T | -0.0053 | 0.0374 | 0.8877999 | 0.8873081 | NA | NA | 7911 |
| 1 | 534192 | rs6680723 | C | T | -0.0062 | 0.0184 | 0.7375000 | 0.7361497 | NA | NA | 8201 |
| 1 | 546697 | rs12025928 | A | G | 0.0121 | 0.0285 | 0.6710996 | 0.6711564 | NA | NA | 7911 |
| 1 | 693731 | rs12238997 | A | G | -0.0461 | 0.0238 | 0.0520403 | 0.0527484 | NA | 0.1417730 | 8220 |
| 1 | 705882 | rs72631875 | G | A | 0.0096 | 0.0338 | 0.7756004 | 0.7763922 | NA | 0.0315495 | 7911 |
| 1 | 706368 | rs55727773 | A | G | -0.0070 | 0.0148 | 0.6343997 | 0.6362325 | NA | 0.2751600 | 8201 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51218377 | rs2519461 | G | C | 0.0080 | 0.0250 | 0.7496007 | 0.7489683 | NA | 0.0826677 | 9573 |
| 22 | 51219006 | rs28729663 | G | A | -0.0078 | 0.0191 | 0.6843007 | 0.6829969 | NA | 0.2052720 | 9568 |
| 22 | 51219387 | rs9616832 | T | C | 0.0032 | 0.0270 | 0.9049000 | 0.9056568 | NA | 0.0654952 | 8201 |
| 22 | 51219704 | rs147475742 | G | A | 0.0160 | 0.0321 | 0.6192999 | 0.6181723 | NA | 0.0473243 | 9283 |
| 22 | 51221190 | rs369304721 | G | A | 0.0386 | 0.0291 | 0.1856000 | 0.1846872 | NA | NA | 9283 |
| 22 | 51221731 | rs115055839 | T | C | 0.0060 | 0.0270 | 0.8252999 | 0.8241409 | NA | 0.0625000 | 8201 |
| 22 | 51222100 | rs114553188 | G | T | -0.0293 | 0.0308 | 0.3423001 | 0.3414528 | NA | 0.0880591 | 9283 |
| 22 | 51223637 | rs375798137 | G | A | -0.0296 | 0.0309 | 0.3375997 | 0.3380987 | NA | 0.0788738 | 9283 |
| 22 | 51229805 | rs9616985 | T | C | 0.0069 | 0.0271 | 0.7979001 | 0.7990224 | NA | 0.0730831 | 8201 |
| 22 | 51237063 | rs3896457 | T | C | -0.0009 | 0.0157 | 0.9568001 | 0.9542864 | NA | 0.2050720 | 8510 |
bcf preview
1 49298 rs10399793 T C . PASS . ES:SE:LP:SS:ID -0.0019:0.0156:0.044649:8201:rs10399793
1 54676 rs2462492 C T . PASS . ES:SE:LP:SS:ID -0.0217:0.0164:0.731656:8201:rs2462492
1 86028 rs114608975 T C . PASS . ES:SE:LP:SS:ID -0.0011:0.0305:0.0126466:7911:rs114608975
1 91536 rs1251109649 G T . PASS . ES:SE:LP:SS:ID -0.0309:0.0158:1.30129:8201:rs1251109649
1 234313 rs8179466 C T . PASS . ES:SE:LP:SS:ID -0.0053:0.0374:0.0516849:7911:rs8179466
1 534192 rs6680723 C T . PASS . ES:SE:LP:SS:ID -0.0062:0.0184:0.132238:8201:rs6680723
1 546697 rs12025928 A G . PASS . ES:SE:LP:SS:ID 0.0121:0.0285:0.173213:7911:rs12025928
1 693731 rs12238997 A G . PASS . ES:SE:LP:SS:ID -0.0461:0.0238:1.28366:8220:rs12238997
1 705882 rs72631875 G A . PASS . ES:SE:LP:SS:ID 0.0096:0.0338:0.110362:7911:rs72631875
1 706368 rs963699400 A G . PASS . ES:SE:LP:SS:ID -0.007:0.0148:0.197637:8201:rs963699400
1 714596 rs149887893 T C . PASS . ES:SE:LP:SS:ID 0.0056:0.0433:0.0469172:7911:rs149887893
1 715265 rs12184267 C T . PASS . ES:SE:LP:SS:ID 0.0097:0.0418:0.0881502:7911:rs12184267
1 715367 rs12184277 A G . PASS . ES:SE:LP:SS:ID 0.0036:0.0416:0.031097:7911:rs12184277
1 717485 rs12184279 C A . PASS . ES:SE:LP:SS:ID 0.0043:0.0417:0.0372519:7911:rs12184279
1 720381 rs116801199 G T . PASS . ES:SE:LP:SS:ID 0.003:0.0417:0.0252581:7911:rs116801199
1 721290 rs12565286 G C . PASS . ES:SE:LP:SS:ID 0.006:0.0414:0.053204:7911:rs12565286
1 722670 rs116030099 T C . PASS . ES:SE:LP:SS:ID 0.0143:0.027:0.224972:7911:rs116030099
1 723891 rs2977670 G C . PASS . ES:SE:LP:SS:ID -0.0173:0.0374:0.191451:7911:rs2977670
1 726794 rs28454925 C G . PASS . ES:SE:LP:SS:ID 0.0156:0.0417:0.149967:7911:rs28454925
1 729632 rs116720794 C T . PASS . ES:SE:LP:SS:ID 0.0167:0.0418:0.161655:7911:rs116720794
1 729679 rs4951859 C G . PASS . ES:SE:LP:SS:ID 0.0289:0.0198:0.843148:8510:rs4951859
1 730087 rs148120343 T C . PASS . ES:SE:LP:SS:ID -0.0672:0.0342:1.30364:7911:rs148120343
1 731718 rs58276399 T C . PASS . ES:SE:LP:SS:ID -0.0634:0.0224:2.33753:8540:rs58276399
1 732989 rs369030935 C T . PASS . ES:SE:LP:SS:ID -0.0169:0.0525:0.126215:7911:rs369030935
1 734349 rs141242758 T C . PASS . ES:SE:LP:SS:ID -0.0643:0.0226:2.35962:8540:rs141242758
1 736289 rs1254887344 T A . PASS . ES:SE:LP:SS:ID -0.0438:0.0219:1.34037:8510:rs1254887344
1 752478 rs146277091 G A . PASS . ES:SE:LP:SS:ID 0.0107:0.0416:0.0985962:7911:rs146277091
1 752566 rs3094315 G A . PASS . ES:SE:LP:SS:ID 0.032:0.0187:1.05576:9174:rs3094315
1 752721 rs3131972 A G . PASS . ES:SE:LP:SS:ID 0.033:0.0192:1.06905:8830:rs3131972
1 753405 rs3115860 C A . PASS . ES:SE:LP:SS:ID 0.0465:0.0214:1.53091:8540:rs3115860
1 753541 rs1388595942 G A . PASS . ES:SE:LP:SS:ID -0.0609:0.0219:2.27124:8540:rs1388595942
1 754063 rs12184312 G T . PASS . ES:SE:LP:SS:ID 0.0135:0.0417:0.127436:7911:rs12184312
1 754105 rs12184325 C T . PASS . ES:SE:LP:SS:ID 0.0123:0.0416:0.115091:7911:rs12184325
1 754182 rs3131969 A G . PASS . ES:SE:LP:SS:ID 0.0452:0.0213:1.47108:8540:rs3131969
1 754192 rs3131968 A G . PASS . ES:SE:LP:SS:ID 0.0448:0.0213:1.45284:8540:rs3131968
1 754211 rs12184313 G A . PASS . ES:SE:LP:SS:ID 0.0144:0.0416:0.136796:7911:rs12184313
1 754334 rs3131967 T C . PASS . ES:SE:LP:SS:ID 0.0432:0.0213:1.37141:8540:rs3131967
1 754503 rs3115859 G A . PASS . ES:SE:LP:SS:ID 0.0315:0.0191:1.00529:8830:rs3115859
1 754629 rs10454459 A G . PASS . ES:SE:LP:SS:ID 0.0156:0.0417:0.150151:7911:rs10454459
1 754964 rs3131966 C T . PASS . ES:SE:LP:SS:ID 0.0316:0.0191:1.01006:8830:rs3131966
1 755775 rs3131965 A G . PASS . ES:SE:LP:SS:ID 0.0336:0.0191:1.10265:8830:rs3131965
1 755890 rs1280367067 A T . PASS . ES:SE:LP:SS:ID 0.0412:0.0213:1.27778:8540:rs1280367067
1 756604 rs3131962 A G . PASS . ES:SE:LP:SS:ID 0.0414:0.0212:1.28802:8540:rs3131962
1 757640 rs3115853 G A . PASS . ES:SE:LP:SS:ID 0.0357:0.0212:1.03626:8540:rs3115853
1 757734 rs1557551770 C T . PASS . ES:SE:LP:SS:ID 0.0416:0.0213:1.29697:8540:rs1557551770
1 757936 rs1360886751 C A . PASS . ES:SE:LP:SS:ID 0.0416:0.0213:1.29697:8540:rs1360886751
1 758144 rs3131956 A G . PASS . ES:SE:LP:SS:ID 0.0416:0.0213:1.29697:8540:rs3131956
1 758626 rs3131954 C T . PASS . ES:SE:LP:SS:ID 0.0407:0.0213:1.25461:8540:rs3131954
1 759036 rs114525117 G A . PASS . ES:SE:LP:SS:ID -0.0048:0.0413:0.041962:7911:rs114525117
1 760912 rs1048488 C T . PASS . ES:SE:LP:SS:ID 0.0344:0.0192:1.14225:8830:rs1048488