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"Gwas2VCF_command": "--data /data/cromwell-executions/qc/e147171c-91dc-4ef0-b848-2cd7ed6c58ef/call-vcf/inputs/268670775/upload.txt.gz --id ieu-b-115 --json /data/cromwell-executions/qc/e147171c-91dc-4ef0-b848-2cd7ed6c58ef/call-vcf/inputs/268670775/ieu-b-115_data.json --ref /data/cromwell-executions/qc/e147171c-91dc-4ef0-b848-2cd7ed6c58ef/call-vcf/inputs/1899004205/human_g1k_v37.fasta --dbsnp /data/cromwell-executions/qc/e147171c-91dc-4ef0-b848-2cd7ed6c58ef/call-vcf/inputs/-307190728/dbsnp.v153.b37.vcf.gz --out /data/igd/ieu-b-115/ieu-b-115.vcf.gz --alias alias.txt; 1.3.0",
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}
*********************************************************************
* 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/e147171c-91dc-4ef0-b848-2cd7ed6c58ef/call-ldsc/inputs/268670775/ieu-b-115.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-115/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/
Beginning analysis at Thu Apr 1 16:26:04 2021
Reading summary statistics from /data/cromwell-executions/qc/e147171c-91dc-4ef0-b848-2cd7ed6c58ef/call-ldsc/inputs/268670775/ieu-b-115.vcf.gz ...
Read summary statistics for 2624472 SNPs.
Dropped 927 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, 1172478 SNPs remain.
After merging with regression SNP LD, 1172478 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.07 (0.01)
Lambda GC: 1.0679
Mean Chi^2: 1.0842
Intercept: 1.0139 (0.0068)
Ratio: 0.1652 (0.0805)
Analysis finished at Thu Apr 1 16:26:56 2021
Total time elapsed: 51.76s
{
"af_correlation": "NA",
"inflation_factor": 1.064,
"mean_EFFECT": -2.6718e-06,
"n": 51750,
"n_snps": 2624472,
"n_clumped_hits": 4,
"n_p_sig": 34,
"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": 2624472,
"n_miss_AF_reference": 24723,
"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": 1172478,
"ldsc_nsnp_merge_regression_ld": 1172478,
"ldsc_observed_scale_h2_beta": 0.07,
"ldsc_observed_scale_h2_se": 0.01,
"ldsc_intercept_beta": 1.0139,
"ldsc_intercept_se": 0.0068,
"ldsc_lambda_gc": 1.0679,
"ldsc_mean_chisq": 1.0842,
"ldsc_ratio": 0.1651
}
name | value |
---|---|
af_correlation | NA |
inflation_factor | FALSE |
n | FALSE |
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 | FALSE |
ldsc_intercept_beta | FALSE |
n_clumped_hits | FALSE |
r2_sum1 | FALSE |
r2_sum2 | FALSE |
r2_sum3 | FALSE |
r2_sum4 | FALSE |
General metrics
af_correlation
: Correlation coefficient between AF
and AF_reference
.inflation_factor
(lambda
): Genomic inflation factor.mean_EFFECT
: Mean of EFFECT
size.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 below 5e-8
.n_mono
: Number of monomorphic (MAF == 1
or MAF == 0
) SNPs.n_ns
: Number of SNPs with nonsense values:
A, C, G or T
.< 0
or > 1
.<= 0
or = Infinity
).< 0
or > 1
.n_mac
: Number of cases where MAC
(\(2 \times N \times MAF\)) is less than 6
.is_snpid_unique
: true
if the combination of ID
REF
ALT
is unique and therefore no duplication in snpid.n_miss_<*>
: Number of NA
observations 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 expect ratio_se_n
to 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.
ratio_diff
: \(\texttt{ratio_diff} = |\frac{\texttt{mean_diff}}{\texttt{mean_diff2}}|\), absolute ratio between the mean of diff
and the mean of diff2
(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.
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.
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.
r2 metrics
Sum of variance explained, calculated from the clumped top hits sample.
r2_sum<*>
: r2
statistics under various assumptions
1
: \(r^2 = \sum_j{\frac{2 \times \beta_j^2 \times {MAF}_j \times (1 - {MAF}_j)}{\texttt{var1}}}\), \(\texttt{var1} = 1\).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
: NOT is_snpid_unique
.mean_EFFECT_nonfinite
: mean(EFFECT)
is NA
, NaN
, or Inf
.mean_EFFECT_05
: abs(mean(EFFECT))
> 0.5.mean_EFFECT_01
: abs(mean(EFFECT))
> 0.1.mean_chisq
: ldsc_mean_chisq
> 1.3 or ldsc_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<*>
> 0.5Plots
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 | 42 | 0 | 2624466 | 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 | 2624472 | 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 | 8.601995e+00 | 5.675814e+00 | 1.000 | 4.000000e+00 | 8.000000e+00 | 1.200000e+01 | 24.0 | ▇▆▃▃▁ |
numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.881771e+07 | 5.583189e+07 | 6888.000 | 3.246510e+07 | 7.010905e+07 | 1.144077e+08 | 249218992.0 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -2.700000e-06 | 1.924920e-02 | -2.100 | -3.200000e-03 | 0.000000e+00 | 3.200000e-03 | 1.7 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.106400e-03 | 1.735590e-02 | 0.003 | 3.400000e-03 | 4.000000e-03 | 6.000000e-03 | 1.1 | ▇▁▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.892829e-01 | 2.918257e-01 | 0.000 | 2.338003e-01 | 4.865999e-01 | 7.418994e-01 | 1.0 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.892789e-01 | 2.918813e-01 | 0.000 | 2.343652e-01 | 4.866467e-01 | 7.417434e-01 | 1.0 | ▇▇▇▇▇ |
numeric | AF_reference | 24723 | 0.9905798 | NA | NA | NA | NA | NA | NA | NA | 3.594452e-01 | 2.582179e-01 | 0.000 | 1.421730e-01 | 2.965260e-01 | 5.453270e-01 | 1.0 | ▇▆▃▃▂ |
numeric | N | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 5.175000e+04 | 0.000000e+00 | 51750.000 | 5.175000e+04 | 5.175000e+04 | 5.175000e+04 | 51750.0 | ▁▁▇▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 721290 | rs12565286 | G | C | 0.0085 | 0.0140 | 0.5578995 | 0.5437561 | NA | 0.0371406 | 51750 |
1 | 723819 | rs11804171 | T | A | 0.0084 | 0.0140 | 0.5574000 | 0.5485062 | NA | 0.1345850 | 51750 |
1 | 723891 | rs2977670 | G | C | -0.0084 | 0.0150 | 0.5659994 | 0.5754794 | NA | 0.7799520 | 51750 |
1 | 750235 | rs12138618 | G | A | 0.0170 | 0.0170 | 0.3006997 | 0.3173105 | NA | NA | 51750 |
1 | 752566 | rs3094315 | G | A | -0.0024 | 0.0054 | 0.6557994 | 0.6567213 | NA | 0.7182510 | 51750 |
1 | 753405 | rs3115860 | C | A | 0.0120 | 0.0089 | 0.1639000 | 0.1775572 | NA | 0.7517970 | 51750 |
1 | 754192 | rs3131968 | A | G | 0.0050 | 0.0068 | 0.4628998 | 0.4621604 | NA | 0.6785140 | 51750 |
1 | 754334 | rs3131967 | T | C | 0.0200 | 0.0097 | 0.0348201 | 0.0392215 | NA | 0.6843050 | 51750 |
1 | 761147 | rs3115850 | T | C | 0.0190 | 0.0096 | 0.0487405 | 0.0477972 | NA | 0.7334270 | 51750 |
1 | 765948 | rs1335857654 | C | T | -0.1100 | 0.1200 | 0.3587996 | 0.3593173 | NA | NA | 51750 |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51217134 | rs117417021 | A | G | 0.0096 | 0.0061 | 0.1142999 | 0.1155405 | NA | 0.2671730 | 51750 |
22 | 51222100 | rs114553188 | G | T | 0.0044 | 0.0093 | 0.6395007 | 0.6361288 | NA | 0.0880591 | 51750 |
22 | 51223637 | rs375798137 | G | A | 0.0044 | 0.0093 | 0.6339004 | 0.6361288 | NA | 0.0788738 | 51750 |
22 | 51229805 | rs9616985 | T | C | 0.0180 | 0.0110 | 0.0983400 | 0.1017635 | NA | 0.0730831 | 51750 |
23 | 35921591 | rs2204667 | C | G | -0.0032 | 0.0043 | 0.4616002 | 0.4567639 | NA | NA | 51750 |
23 | 51666786 | rs14115 | A | G | -0.0001 | 0.0067 | 0.9894000 | 0.9880917 | NA | NA | 51750 |
23 | 70163799 | rs1626496 | A | C | 0.0028 | 0.0065 | 0.6635001 | 0.6666362 | NA | NA | 51750 |
23 | 91415872 | rs6562597 | G | A | -0.0065 | 0.0140 | 0.6428002 | 0.6424431 | NA | 0.0021192 | 51750 |
23 | 118495837 | rs12882977 | G | A | -0.0012 | 0.0032 | 0.7149999 | 0.7076605 | NA | 0.2307280 | 51750 |
24 | 3631296 | rs2176440 | T | C | 0.0180 | 0.1400 | 0.8975999 | 0.8976968 | NA | NA | 51750 |
1 721290 rs12565286 G C . PASS . ES:SE:LP:SS:ID 0.0085:0.014:0.253444:51750:rs12565286
1 723819 rs11804171 T A . PASS . ES:SE:LP:SS:ID 0.0084:0.014:0.253833:51750:rs11804171
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1 750235 rs12138618 G A . PASS . ES:SE:LP:SS:ID 0.017:0.017:0.521867:51750:rs12138618
1 752566 rs3094315 G A . PASS . ES:SE:LP:SS:ID -0.0024:0.0054:0.183229:51750:rs3094315
1 753405 rs3115860 C A . PASS . ES:SE:LP:SS:ID 0.012:0.0089:0.785421:51750:rs3115860
1 754192 rs3131968 A G . PASS . ES:SE:LP:SS:ID 0.005:0.0068:0.334513:51750:rs3131968
1 754334 rs3131967 T C . PASS . ES:SE:LP:SS:ID 0.02:0.0097:1.45817:51750:rs3131967
1 761147 rs3115850 T C . PASS . ES:SE:LP:SS:ID 0.019:0.0096:1.31211:51750:rs3115850
1 765948 rs1335857654 C T . PASS . ES:SE:LP:SS:ID -0.11:0.12:0.445148:51750:rs1335857654
1 768448 rs12562034 G A . PASS . ES:SE:LP:SS:ID 0.0062:0.0098:0.278519:51750:rs12562034
1 775659 rs2905035 A G . PASS . ES:SE:LP:SS:ID 0.0001:0.0062:0.00322573:51750:rs2905035
1 776546 rs12124819 A G . PASS . ES:SE:LP:SS:ID 0.0038:0.0061:0.271403:51750:rs12124819
1 777122 rs2980319 A T . PASS . ES:SE:LP:SS:ID 0:0.0062:8.68676e-05:51750:rs2980319
1 779322 rs4040617 A G . PASS . ES:SE:LP:SS:ID 0.0003:0.0062:0.0155627:51750:rs4040617
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1 784023 rs17160939 A G . PASS . ES:SE:LP:SS:ID 0.016:0.024:0.282746:51750:rs17160939
1 784904 rs2519068 G A . PASS . ES:SE:LP:SS:ID 0.97:0.74:0.727462:51750:rs2519068
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1 798026 rs4951864 C T . PASS . ES:SE:LP:SS:ID -0.0055:0.011:0.214741:51750:rs4951864
1 798801 rs12132517 G A . PASS . ES:SE:LP:SS:ID 0.0065:0.011:0.263046:51750:rs12132517
1 798959 rs11240777 G A . PASS . ES:SE:LP:SS:ID -0.0049:0.0078:0.274007:51750:rs11240777
1 846808 rs4475691 C T . PASS . ES:SE:LP:SS:ID -0.0006:0.0088:0.024798:51750:rs4475691
1 846864 rs1269142199 G C . PASS . ES:SE:LP:SS:ID 0.028:0.05:0.24003:51750:rs1269142199
1 882033 rs2272756 G A . PASS . ES:SE:LP:SS:ID 0.024:0.035:0.310247:51750:rs2272756
1 888659 rs3748597 T C . PASS . ES:SE:LP:SS:ID 0.021:0.02:0.54607:51750:rs3748597
1 918384 rs13303118 G T . PASS . ES:SE:LP:SS:ID -0.0063:0.0068:0.452225:51750:rs13303118
1 928836 rs9777703 C T . PASS . ES:SE:LP:SS:ID 0.0045:0.02:0.0834934:51750:rs9777703
1 943468 rs3121567 T C . PASS . ES:SE:LP:SS:ID 0.011:0.021:0.208871:51750:rs3121567
1 962210 rs3128126 A G . PASS . ES:SE:LP:SS:ID -0.0022:0.0078:0.107961:51750:rs3128126
1 990380 rs3121561 C T . PASS . ES:SE:LP:SS:ID 0.0012:0.0056:0.0776898:51750:rs3121561
1 990417 rs2465136 T C . PASS . ES:SE:LP:SS:ID 0.0058:0.01:0.245422:51750:rs2465136
1 990517 rs2710872 C T . PASS . ES:SE:LP:SS:ID -0.025:0.017:0.860436:51750:rs2710872
1 998501 rs3813193 G C . PASS . ES:SE:LP:SS:ID 0.0018:0.0053:0.131591:51750:rs3813193
1 1003629 rs4075116 C T . PASS . ES:SE:LP:SS:ID -0.004:0.004:0.502379:51750:rs4075116
1 1005806 rs3934834 C T . PASS . ES:SE:LP:SS:ID 0.0026:0.0052:0.212256:51750:rs3934834
1 1017170 rs3766193 C G . PASS . ES:SE:LP:SS:ID -0.0032:0.0039:0.397072:51750:rs3766193
1 1017197 rs3766192 C T . PASS . ES:SE:LP:SS:ID -0.0034:0.0037:0.443939:51750:rs3766192
1 1017587 rs3766191 C T . PASS . ES:SE:LP:SS:ID 0.0022:0.0054:0.168194:51750:rs3766191
1 1018562 rs9442371 C T . PASS . ES:SE:LP:SS:ID -0.0031:0.0036:0.412514:51750:rs9442371
1 1018704 rs9442372 A G . PASS . ES:SE:LP:SS:ID -0.0031:0.0036:0.415217:51750:rs9442372
1 1021346 rs10907177 A G . PASS . ES:SE:LP:SS:ID 0.0026:0.0054:0.194703:51750:rs10907177
1 1021415 rs386627436 A G . PASS . ES:SE:LP:SS:ID -0.0041:0.0039:0.539553:51750:rs386627436
1 1021583 rs10907178 A C . PASS . ES:SE:LP:SS:ID 0.0029:0.0055:0.227385:51750:rs10907178
1 1021695 rs9442398 A G . PASS . ES:SE:LP:SS:ID -0.0041:0.004:0.519418:51750:rs9442398
1 1022037 rs6701114 C T . PASS . ES:SE:LP:SS:ID -0.0031:0.0039:0.363612:51750:rs6701114
1 1025301 rs9442400 T C . PASS . ES:SE:LP:SS:ID -0.0071:0.019:0.154654:51750:rs9442400
1 1026707 rs4074137 C A . PASS . ES:SE:LP:SS:ID -0.0011:0.0045:0.0898026:51750:rs4074137