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/51a64c3c-5964-4208-aa59-3ff3e1b7729f/call-vcf/inputs/-261044537/upload.txt.gz --id ieu-b-4816 --json /data/cromwell-executions/qc/51a64c3c-5964-4208-aa59-3ff3e1b7729f/call-vcf/inputs/-261044537/ieu-b-4816_data.json --ref /data/cromwell-executions/qc/51a64c3c-5964-4208-aa59-3ff3e1b7729f/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/51a64c3c-5964-4208-aa59-3ff3e1b7729f/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-4816/ieu-b-4816.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/51a64c3c-5964-4208-aa59-3ff3e1b7729f/call-ldsc/inputs/-261044537/ieu-b-4816.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-4816/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Wed Jan 5 04:59:14 2022
Reading summary statistics from /data/cromwell-executions/qc/51a64c3c-5964-4208-aa59-3ff3e1b7729f/call-ldsc/inputs/-261044537/ieu-b-4816.vcf.gz ...
Read summary statistics for 7191573 SNPs.
Dropped 19717 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, 1199274 SNPs remain.
After merging with regression SNP LD, 1199274 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.2122 (0.0103)
Lambda GC: 1.4805
Mean Chi^2: 1.5755
Intercept: 1.1218 (0.0088)
Ratio: 0.2117 (0.0152)
Analysis finished at Wed Jan 5 05:00:50 2022
Total time elapsed: 1.0m:36.49sQC metrics
Metrics
Metrics
{
"af_correlation": "NA",
"inflation_factor": 1.44,
"mean_EFFECT": -0.0021,
"n": 112744,
"n_snps": 7191598,
"n_clumped_hits": 42,
"n_p_sig": 2353,
"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": 7191598,
"n_miss_AF_reference": 46780,
"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": 1199274,
"ldsc_nsnp_merge_regression_ld": 1199274,
"ldsc_observed_scale_h2_beta": 0.2122,
"ldsc_observed_scale_h2_se": 0.0103,
"ldsc_intercept_beta": 1.1218,
"ldsc_intercept_se": 0.0088,
"ldsc_lambda_gc": 1.4805,
"ldsc_mean_chisq": 1.5755,
"ldsc_ratio": 0.2116
}
Flags
| name | value |
|---|---|
| af_correlation | NA |
| inflation_factor | TRUE |
| n | FALSE |
| is_snpid_non_unique | TRUE |
| mean_EFFECT_nonfinite | FALSE |
| mean_EFFECT_05 | FALSE |
| mean_EFFECT_01 | FALSE |
| mean_chisq | TRUE |
| n_p_sig | TRUE |
| 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 | 8 | 0.9999989 | 3 | 58 | 0 | 7191573 | 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 | 7191598 | 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 | 8.631819e+00 | 5.745131e+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 | 7.892427e+07 | 5.636321e+07 | 8.2800e+02 | 3.248775e+07 | 6.955367e+07 | 1.147668e+08 | 2.492223e+08 | ▇▆▅▂▁ |
| numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -2.098800e-03 | 4.847230e-02 | -4.6150e-01 | -2.600000e-02 | -1.400000e-03 | 2.280000e-02 | 4.532000e-01 | ▁▁▇▁▁ |
| numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.639290e-02 | 2.126320e-02 | 1.7800e-02 | 2.060000e-02 | 2.690000e-02 | 4.510000e-02 | 1.329000e-01 | ▇▂▁▁▁ |
| numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.417597e-01 | 3.023377e-01 | 0.0000e+00 | 1.663999e-01 | 4.183001e-01 | 7.028004e-01 | 1.000000e+00 | ▇▆▅▅▅ |
| numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.417600e-01 | 3.023394e-01 | 0.0000e+00 | 1.663803e-01 | 4.183266e-01 | 7.027392e-01 | 1.000000e+00 | ▇▆▅▅▅ |
| numeric | AF_reference | 46780 | 0.9934952 | NA | NA | NA | NA | NA | NA | NA | 2.661372e-01 | 2.522957e-01 | 1.9970e-04 | 5.930510e-02 | 1.805110e-01 | 4.143370e-01 | 1.000000e+00 | ▇▃▂▁▁ |
| numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.038475e+05 | 1.047258e+04 | 6.7656e+04 | 1.001730e+05 | 1.081460e+05 | 1.121830e+05 | 1.127440e+05 | ▁▁▁▂▇ |
Head and tail
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 768448 | rs12562034 | G | A | -0.0153 | 0.0405 | 0.7048002 | 0.7055957 | NA | 0.1918930 | 69965 |
| 1 | 777232 | rs112618790 | C | T | -0.0068 | 0.0425 | 0.8723001 | 0.8728811 | NA | 0.0668930 | 69965 |
| 1 | 791853 | rs6684487 | G | A | -0.0139 | 0.0426 | 0.7437997 | 0.7442041 | NA | 0.0762780 | 69965 |
| 1 | 794332 | rs12127425 | G | A | -0.0272 | 0.0466 | 0.5586001 | 0.5594282 | NA | 0.1162140 | 68637 |
| 1 | 796100 | rs12132398 | C | T | -0.0233 | 0.0464 | 0.6160004 | 0.6155584 | NA | 0.0856629 | 68637 |
| 1 | 797281 | rs76631953 | G | C | -0.0275 | 0.0465 | 0.5540003 | 0.5542539 | NA | 0.0656949 | 68637 |
| 1 | 797325 | rs111739932 | T | C | -0.0269 | 0.0463 | 0.5613995 | 0.5612448 | NA | 0.0680911 | 68637 |
| 1 | 797440 | rs58013264 | T | C | 0.0138 | 0.0311 | 0.6560002 | 0.6572379 | NA | 0.1894970 | 85735 |
| 1 | 798026 | rs4951864 | C | T | 0.0216 | 0.0456 | 0.6348001 | 0.6357251 | NA | 0.8941690 | 68687 |
| 1 | 798400 | rs10900604 | A | G | 0.0024 | 0.0252 | 0.9245000 | 0.9241257 | NA | 0.4105430 | 88327 |
| CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 22 | 51196164 | rs8136603 | A | T | 0.0508 | 0.0508 | 0.3175002 | 0.3173105 | NA | 0.1427720 | 76575 |
| 22 | 51196296 | rs9616961 | G | C | -0.0245 | 0.0465 | 0.5981994 | 0.5982757 | NA | 0.0395367 | 73099 |
| 22 | 51197576 | rs147713773 | G | C | -0.0214 | 0.0467 | 0.6461004 | 0.6467771 | NA | 0.0471246 | 73099 |
| 22 | 51197602 | rs187225588 | T | A | 0.0480 | 0.0501 | 0.3375002 | 0.3380205 | NA | 0.0175719 | 78903 |
| 22 | 51198569 | rs142671391 | G | C | 0.0710 | 0.0535 | 0.1849000 | 0.1844747 | NA | 0.1110220 | 76575 |
| 22 | 51198906 | rs6010079 | G | A | -0.0245 | 0.0468 | 0.5999997 | 0.6006234 | NA | 0.0421326 | 73099 |
| 22 | 51202748 | rs9616963 | A | G | -0.0202 | 0.0466 | 0.6640993 | 0.6646687 | NA | 0.0391374 | 73099 |
| 22 | 51208568 | rs148425445 | G | T | 0.0439 | 0.0496 | 0.3760997 | 0.3761131 | NA | 0.1160140 | 78903 |
| 22 | 51216564 | rs9616970 | T | C | -0.0010 | 0.0352 | 0.9763000 | 0.9773359 | NA | 0.1563500 | 69441 |
| 22 | 51222100 | rs114553188 | G | T | 0.0326 | 0.0509 | 0.5217999 | 0.5218661 | NA | 0.0880591 | 78903 |
bcf preview
1 768448 rs12562034 G A . PASS . ES:SE:LP:SS:ID -0.0153:0.0405:0.151934:69965:rs12562034
1 777232 rs112618790 C T . PASS . ES:SE:LP:SS:ID -0.0068:0.0425:0.0593341:69965:rs112618790
1 791853 rs6684487 G A . PASS . ES:SE:LP:SS:ID -0.0139:0.0426:0.128544:69965:rs6684487
1 794332 rs12127425 G A . PASS . ES:SE:LP:SS:ID -0.0272:0.0466:0.252899:68637:rs12127425
1 796100 rs12132398 C T . PASS . ES:SE:LP:SS:ID -0.0233:0.0464:0.210419:68637:rs12132398
1 797281 rs1347695410 G C . PASS . ES:SE:LP:SS:ID -0.0275:0.0465:0.25649:68637:rs1347695410
1 797325 rs1338750774 T C . PASS . ES:SE:LP:SS:ID -0.0269:0.0463:0.250728:68637:rs1338750774
1 797440 rs58013264 T C . PASS . ES:SE:LP:SS:ID 0.0138:0.0311:0.183096:85735:rs58013264
1 798026 rs4951864 C T . PASS . ES:SE:LP:SS:ID 0.0216:0.0456:0.197363:68687:rs4951864
1 798400 rs10900604 A G . PASS . ES:SE:LP:SS:ID 0.0024:0.0252:0.0340931:88327:rs10900604
1 798801 rs12132517 G A . PASS . ES:SE:LP:SS:ID -0.0214:0.0463:0.191857:68637:rs12132517
1 798959 rs11240777 G A . PASS . ES:SE:LP:SS:ID 0.0009:0.0245:0.0126019:92072:rs11240777
1 799499 rs147634896 T C . PASS . ES:SE:LP:SS:ID -0.0213:0.0465:0.189096:68637:rs147634896
1 800383 rs4951931 C T . PASS . ES:SE:LP:SS:ID 0.0162:0.0455:0.141282:69354:rs4951931
1 801467 rs61768212 G C . PASS . ES:SE:LP:SS:ID 0.0116:0.031:0.149599:85124:rs61768212
1 801661 rs12132974 C T . PASS . ES:SE:LP:SS:ID -0.0256:0.0467:0.234182:68637:rs12132974
1 801680 rs12134490 A C . PASS . ES:SE:LP:SS:ID -0.0258:0.0467:0.235824:68637:rs12134490
1 801858 rs17276806 C T . PASS . ES:SE:LP:SS:ID -0.0241:0.0467:0.217456:68637:rs17276806
1 802856 rs139867617 C T . PASS . ES:SE:LP:SS:ID -0.0205:0.0467:0.179536:68637:rs139867617
1 804759 rs7526310 C T . PASS . ES:SE:LP:SS:ID 0.009:0.0311:0.112214:85124:rs7526310
1 808631 rs11240779 G A . PASS . ES:SE:LP:SS:ID -0.0117:0.0245:0.198185:86452:rs11240779
1 808928 rs1247187939 C T . PASS . ES:SE:LP:SS:ID -0.0127:0.0245:0.219395:86452:rs1247187939
1 833223 rs13303211 C T . PASS . ES:SE:LP:SS:ID -0.0362:0.03:0.640734:69965:rs13303211
1 833302 rs28752186 C T . PASS . ES:SE:LP:SS:ID -0.0372:0.03:0.667158:69965:rs28752186
1 833824 rs28484835 T C . PASS . ES:SE:LP:SS:ID -0.0372:0.03:0.667764:69965:rs28484835
1 833927 rs28593608 T C . PASS . ES:SE:LP:SS:ID -0.0363:0.0309:0.620151:70526:rs28593608
1 834198 rs28385272 T C . PASS . ES:SE:LP:SS:ID -0.0368:0.0309:0.629857:70526:rs28385272
1 834832 rs796468152 G C . PASS . ES:SE:LP:SS:ID -0.0365:0.03:0.650917:69965:rs796468152
1 834928 rs4422949 A G . PASS . ES:SE:LP:SS:ID -0.0375:0.0309:0.64859:70526:rs4422949
1 834999 rs28570054 G A . PASS . ES:SE:LP:SS:ID -0.0355:0.0309:0.60206:70526:rs28570054
1 835499 rs4422948 A G . PASS . ES:SE:LP:SS:ID -0.0336:0.0299:0.583692:69965:rs4422948
1 836529 rs1192410597 C G . PASS . ES:SE:LP:SS:ID -0.0393:0.031:0.686133:69965:rs1192410597
1 836896 rs28705752 T C . PASS . ES:SE:LP:SS:ID -0.0328:0.0284:0.605023:70526:rs28705752
1 836924 rs72890788 G A . PASS . ES:SE:LP:SS:ID -0.0409:0.0309:0.733298:70526:rs72890788
1 838387 rs4970384 T C . PASS . ES:SE:LP:SS:ID -0.0399:0.0308:0.708631:70526:rs4970384
1 838555 rs4970383 C A . PASS . ES:SE:LP:SS:ID -0.038:0.0291:0.717605:70526:rs4970383
1 839103 rs28562941 A G . PASS . ES:SE:LP:SS:ID -0.0303:0.0285:0.542724:70526:rs28562941
1 841085 rs1264290483 C G . PASS . ES:SE:LP:SS:ID -0.0348:0.0297:0.616903:69965:rs1264290483
1 842013 rs1191510089 T G . PASS . ES:SE:LP:SS:ID -0.0438:0.0309:0.806875:70526:rs1191510089
1 845635 rs117086422 C T . PASS . ES:SE:LP:SS:ID 0.0022:0.0248:0.0311436:99733:rs117086422
1 845938 rs57760052 G A . PASS . ES:SE:LP:SS:ID 0.0038:0.0246:0.0567034:99733:rs57760052
1 846078 rs778265812 C T . PASS . ES:SE:LP:SS:ID -0.0097:0.0254:0.152798:99733:rs778265812
1 846398 rs58781670 G A . PASS . ES:SE:LP:SS:ID 0.0031:0.025:0.0455645:99733:rs58781670
1 846465 rs60454217 C T . PASS . ES:SE:LP:SS:ID 0.0893:0.0802:0.575445:90493:rs60454217
1 846543 rs79396034 G T . PASS . ES:SE:LP:SS:ID 0.1238:0.0851:0.837436:81346:rs79396034
1 846808 rs4475691 C T . PASS . ES:SE:LP:SS:ID -0.0073:0.0253:0.11227:99733:rs4475691
1 846864 rs1269142199 G C . PASS . ES:SE:LP:SS:ID -0.0116:0.0255:0.187688:99172:rs1269142199
1 847228 rs3905286 C T . PASS . ES:SE:LP:SS:ID -0.0042:0.025:0.0616805:99733:rs3905286
1 847491 rs1158719307 G A . PASS . ES:SE:LP:SS:ID -0.0073:0.0246:0.114978:99733:rs1158719307
1 848090 rs4246505 G A . PASS . ES:SE:LP:SS:ID -0.0095:0.0247:0.15515:99733:rs4246505