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/42885d4b-fb0b-481a-9c31-7042290ae633/call-vcf/inputs/-261044536/upload.txt.gz --id ieu-b-4817 --json /data/cromwell-executions/qc/42885d4b-fb0b-481a-9c31-7042290ae633/call-vcf/inputs/-261044536/ieu-b-4817_data.json --ref /data/cromwell-executions/qc/42885d4b-fb0b-481a-9c31-7042290ae633/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/42885d4b-fb0b-481a-9c31-7042290ae633/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4817/ieu-b-4817.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/42885d4b-fb0b-481a-9c31-7042290ae633/call-ldsc/inputs/-261044536/ieu-b-4817.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4817/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Wed Jan 5 05:33:44 2022
Reading summary statistics from /data/cromwell-executions/qc/42885d4b-fb0b-481a-9c31-7042290ae633/call-ldsc/inputs/-261044536/ieu-b-4817.vcf.gz ...
Read summary statistics for 8029585 SNPs.
Dropped 39100 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, 1202658 SNPs remain.
After merging with regression SNP LD, 1202658 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1079 (0.0145)
Lambda GC: 1.0921
Mean Chi^2: 1.1004
Intercept: 1.0195 (0.0063)
Ratio: 0.1944 (0.0632)
Analysis finished at Wed Jan 5 05:35:30 2022
Total time elapsed: 1.0m:46.13sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.0831,
"mean_EFFECT": -0.0009,
"n": 38434,
"n_snps": 8029645,
"n_clumped_hits": 4,
"n_p_sig": 16,
"n_mono": 0,
"n_ns": 285806,
"n_mac": 0,
"is_snpid_unique": false,
"n_miss_EFFECT": 0,
"n_miss_SE": 0,
"n_miss_PVAL": 0,
"n_miss_AF": 8029645,
"n_miss_AF_reference": 162500,
"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": 1202658,
"ldsc_nsnp_merge_regression_ld": 1202658,
"ldsc_observed_scale_h2_beta": 0.1079,
"ldsc_observed_scale_h2_se": 0.0145,
"ldsc_intercept_beta": 1.0195,
"ldsc_intercept_se": 0.0063,
"ldsc_lambda_gc": 1.0921,
"ldsc_mean_chisq": 1.1004,
"ldsc_ratio": 0.1942
}
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 | 16 | 0.9999980 | 3 | 58 | 0 | 8029515 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | REF | 0 | 1.0000000 | 1 | 43 | 0 | 16662 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| character | ALT | 0 | 1.0000000 | 1 | 44 | 0 | 6027 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| logical | AF | 8029645 | 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 | 8.642174e+00 | 5.752157e+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 | 7.886231e+07 | 5.635232e+07 | 3.020e+02 | 3.246903e+07 | 6.943490e+07 | 1.146235e+08 | 2.492223e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -8.639000e-04 | 2.931143e-01 | -2.939e+00 | -1.426000e-01 | -1.000000e-04 | 1.424000e-01 | 3.119900e+00 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.480222e-01 | 1.427660e-01 | 1.045e-01 | 1.398000e-01 | 1.858000e-01 | 3.178000e-01 | 9.213000e-01 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.872821e-01 | 2.916827e-01 | 0.000e+00 | 2.320999e-01 | 4.826997e-01 | 7.394997e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.872822e-01 | 2.916828e-01 | 0.000e+00 | 2.321496e-01 | 4.826483e-01 | 7.394905e-01 | 1.000000e+00 | ▇▇▇▇▇ |
| numeric | AF_reference | 162500 | 0.9797625 | NA | NA | NA | NA | NA | NA | NA | 2.622305e-01 | 2.522768e-01 | 1.997e-04 | 5.471250e-02 | 1.757190e-01 | 4.097440e-01 | 1.000000e+00 | ▇▃▂▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.575314e+04 | 4.093965e+03 | 2.171e+04 | 3.605700e+04 | 3.724500e+04 | 3.827800e+04 | 3.843400e+04 | ▁▁▁▁▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 768448 | rs12562034 | G | A | 0.3466 | 0.2660 | 0.1927001 | 0.1925722 | NA | 0.1918930 | 22497 |
| 1 | 777232 | rs112618790 | C | T | 0.2851 | 0.2815 | 0.3112003 | 0.3111611 | NA | 0.0668930 | 22497 |
| 1 | 791853 | rs6684487 | G | A | 0.1455 | 0.2786 | 0.6015005 | 0.6014934 | NA | 0.0762780 | 22497 |
| 1 | 794332 | rs12127425 | G | A | 0.0934 | 0.3082 | 0.7619000 | 0.7618518 | NA | 0.1162140 | 21710 |
| 1 | 795222 | rs12131377 | C | G | 0.1295 | 0.3035 | 0.6696995 | 0.6696061 | NA | 0.0696885 | 21996 |
| 1 | 796100 | rs12132398 | C | T | 0.1208 | 0.3041 | 0.6912004 | 0.6911921 | NA | 0.0856629 | 21996 |
| 1 | 797281 | rs76631953 | G | C | 0.0471 | 0.3065 | 0.8778000 | 0.8778696 | NA | 0.0656949 | 21996 |
| 1 | 797325 | rs111739932 | T | C | 0.1120 | 0.3048 | 0.7132996 | 0.7132803 | NA | 0.0680911 | 21996 |
| 1 | 797440 | rs58013264 | T | C | -0.2263 | 0.2168 | 0.2963999 | 0.2965691 | NA | 0.1894970 | 31443 |
| 1 | 798026 | rs4951864 | C | T | -0.1410 | 0.2964 | 0.6343004 | 0.6342821 | NA | 0.8941690 | 22275 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51195550 | rs148968329 | C | A | 0.2542 | 0.3373 | 0.4510005 | 0.4510704 | NA | 0.0391374 | 21996 |
| 22 | 51196164 | rs8136603 | A | T | -0.1305 | 0.3502 | 0.7093001 | 0.7094133 | NA | 0.1427720 | 21710 |
| 22 | 51196296 | rs9616961 | G | C | 0.2453 | 0.3383 | 0.4684001 | 0.4683931 | NA | 0.0395367 | 21996 |
| 22 | 51197576 | rs147713773 | G | C | 0.2742 | 0.3401 | 0.4201003 | 0.4201082 | NA | 0.0471246 | 21996 |
| 22 | 51197602 | rs187225588 | T | A | 0.0112 | 0.3527 | 0.9747001 | 0.9746674 | NA | 0.0175719 | 21710 |
| 22 | 51198569 | rs142671391 | G | C | -0.2716 | 0.4137 | 0.5115004 | 0.5114932 | NA | 0.1110220 | 21710 |
| 22 | 51198906 | rs6010079 | G | A | 0.1636 | 0.3402 | 0.6306000 | 0.6305921 | NA | 0.0421326 | 21996 |
| 22 | 51202748 | rs9616963 | A | G | 0.1804 | 0.3409 | 0.5966999 | 0.5966754 | NA | 0.0391374 | 21996 |
| 22 | 51208568 | rs148425445 | G | T | -0.1851 | 0.3521 | 0.5990996 | 0.5990946 | NA | 0.1160140 | 21710 |
| 22 | 51222100 | rs114553188 | G | T | -0.3197 | 0.4266 | 0.4536000 | 0.4536077 | NA | 0.0880591 | 21710 |
bcf preview
1 768448 rs12562034 G A . PASS . ES:SE:LP:SS:ID 0.3466:0.266:0.715118:22497:rs12562034
1 777232 rs112618790 C T . PASS . ES:SE:LP:SS:ID 0.2851:0.2815:0.50696:22497:rs112618790
1 791853 rs6684487 G A . PASS . ES:SE:LP:SS:ID 0.1455:0.2786:0.220764:22497:rs6684487
1 794332 rs12127425 G A . PASS . ES:SE:LP:SS:ID 0.0934:0.3082:0.118102:21710:rs12127425
1 795222 rs12131377 C G . PASS . ES:SE:LP:SS:ID 0.1295:0.3035:0.17412:21996:rs12131377
1 796100 rs12132398 C T . PASS . ES:SE:LP:SS:ID 0.1208:0.3041:0.160396:21996:rs12132398
1 797281 rs1347695410 G C . PASS . ES:SE:LP:SS:ID 0.0471:0.3065:0.0566044:21996:rs1347695410
1 797325 rs1338750774 T C . PASS . ES:SE:LP:SS:ID 0.112:0.3048:0.146728:21996:rs1338750774
1 797440 rs58013264 T C . PASS . ES:SE:LP:SS:ID -0.2263:0.2168:0.528122:31443:rs58013264
1 798026 rs4951864 C T . PASS . ES:SE:LP:SS:ID -0.141:0.2964:0.197705:22275:rs4951864
1 798400 rs10900604 A G . PASS . ES:SE:LP:SS:ID -0.1197:0.1773:0.301291:31971:rs10900604
1 798801 rs12132517 G A . PASS . ES:SE:LP:SS:ID 0.0737:0.3031:0.0926424:21996:rs12132517
1 798959 rs11240777 G A . PASS . ES:SE:LP:SS:ID -0.1297:0.177:0.333763:31971:rs11240777
1 799499 rs147634896 T C . PASS . ES:SE:LP:SS:ID -0.0006:0.3046:0.000651931:21996:rs147634896
1 800383 rs4951931 C T . PASS . ES:SE:LP:SS:ID 0.0513:0.301:0.063235:22218:rs4951931
1 801467 rs61768212 G C . PASS . ES:SE:LP:SS:ID -0.2159:0.2186:0.490529:31164:rs61768212
1 801661 rs12132974 C T . PASS . ES:SE:LP:SS:ID -0.0993:0.3124:0.124534:21710:rs12132974
1 801680 rs12134490 A C . PASS . ES:SE:LP:SS:ID -0.0941:0.3125:0.117305:21710:rs12134490
1 801858 rs17276806 C T . PASS . ES:SE:LP:SS:ID -0.0471:0.313:0.05532:21710:rs17276806
1 801943 rs7516866 C T . PASS . ES:SE:LP:SS:ID 0.088:0.3039:0.112383:22218:rs7516866
1 802856 rs139867617 C T . PASS . ES:SE:LP:SS:ID 0.0072:0.3136:0.00806545:21710:rs139867617
1 804759 rs7526310 C T . PASS . ES:SE:LP:SS:ID -0.2403:0.2186:0.56623:31164:rs7526310
1 808223 rs1557576983 G C . PASS . ES:SE:LP:SS:ID 0.1719:0.1948:0.422968:25385:rs1557576983
1 808631 rs11240779 G A . PASS . ES:SE:LP:SS:ID 0.0741:0.1716:0.176461:31729:rs11240779
1 808928 rs1247187939 C T . PASS . ES:SE:LP:SS:ID 0.0629:0.1715:0.146423:31729:rs1247187939
1 833223 rs13303211 C T . PASS . ES:SE:LP:SS:ID 0.1879:0.2:0.459295:22275:rs13303211
1 833302 rs28752186 C T . PASS . ES:SE:LP:SS:ID 0.1881:0.1999:0.460046:22275:rs28752186
1 833641 rs28594623 T C . PASS . ES:SE:LP:SS:ID 0.1794:0.1998:0.432738:22275:rs28594623
1 833824 rs28484835 T C . PASS . ES:SE:LP:SS:ID 0.1894:0.1997:0.464833:22275:rs28484835
1 833927 rs28593608 T C . PASS . ES:SE:LP:SS:ID 0.1228:0.201:0.266642:22275:rs28593608
1 834056 rs28482280 A C . PASS . ES:SE:LP:SS:ID 0.8283:0.5989:0.778064:21710:rs28482280
1 834198 rs28385272 T C . PASS . ES:SE:LP:SS:ID 0.1305:0.2008:0.287519:22275:rs28385272
1 834832 rs796468152 G C . PASS . ES:SE:LP:SS:ID 0.2011:0.1993:0.504594:22275:rs796468152
1 834928 rs4422949 A G . PASS . ES:SE:LP:SS:ID 0.1162:0.201:0.24926:22275:rs4422949
1 834956 rs7518581 G A . PASS . ES:SE:LP:SS:ID 0.8967:0.5987:0.872247:21710:rs7518581
1 834999 rs28570054 G A . PASS . ES:SE:LP:SS:ID 0.111:0.2006:0.236572:22275:rs28570054
1 835092 rs72631887 T G . PASS . ES:SE:LP:SS:ID -0.0083:0.5675:0.00506726:21710:rs72631887
1 835499 rs4422948 A G . PASS . ES:SE:LP:SS:ID 0.2854:0.1982:0.824488:22275:rs4422948
1 836529 rs1192410597 C G . PASS . ES:SE:LP:SS:ID 0.0732:0.1982:0.147764:22497:rs1192410597
1 836684 rs74460547 G A . PASS . ES:SE:LP:SS:ID -0.6177:0.6606:0.45618:21710:rs74460547
1 836896 rs28705752 T C . PASS . ES:SE:LP:SS:ID 0.1247:0.1862:0.298518:22275:rs28705752
1 836924 rs72890788 G A . PASS . ES:SE:LP:SS:ID 0.0728:0.1982:0.146606:22497:rs72890788
1 837192 rs57494724 A G . PASS . ES:SE:LP:SS:ID 0.5056:0.3673:0.773142:21710:rs57494724
1 837657 rs149737509 G C . PASS . ES:SE:LP:SS:ID 0.4076:0.5706:0.323306:21710:rs149737509
1 838387 rs4970384 T C . PASS . ES:SE:LP:SS:ID 0.0291:0.1973:0.0541377:22497:rs4970384
1 838555 rs4970383 C A . PASS . ES:SE:LP:SS:ID 0.0525:0.184:0.11053:22275:rs4970383
1 838665 rs28678693 T C . PASS . ES:SE:LP:SS:ID 1.0216:0.598:1.0575:21710:rs28678693
1 838732 rs952157075 G A . PASS . ES:SE:LP:SS:ID 1.007:0.6:1.03026:21710:rs952157075
1 838890 rs28437697 A G . PASS . ES:SE:LP:SS:ID 1.0064:0.5985:1.03325:21710:rs28437697
1 838916 rs28539852 A T . PASS . ES:SE:LP:SS:ID 1.0089:0.5999:1.03339:21710:rs28539852