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"gwas_harmonisation_command": "--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/vcf_09_19b/bgzip_vcf/data.batch_20094_1.vcf.gz --id UKB-b:3381 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_20094_1.txt.gz --cohort_cases 4849 --cohort_controls 60100 --ref /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/human_g1k_v37.fasta --json /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/ukb_gwas.json; 1.1.1",
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"bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-3381/ukb-b-3381.vcf.gz; Date=Sat May 9 13:20:08 2020"
}
*********************************************************************
* 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 /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3381/UKB-b-3381_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3381/ldsc.txt \
--w-ld-chr ../reference/eur_w_ld_chr/
Beginning analysis at Thu Oct 17 14:43:24 2019
Reading summary statistics from /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-3381/UKB-b-3381_data.vcf.gz ...
Read summary statistics for 4856607 SNPs.
Dropped 1296 SNPs with duplicated rs numbers.
Reading reference panel LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read reference panel LD Scores for 1290028 SNPs.
Removing partitioned LD Scores with zero variance.
Reading regression weight LD Score from ../reference/eur_w_ld_chr/[1-22] ...
Read regression weight LD Scores for 1290028 SNPs.
After merging with reference panel LD, 1095820 SNPs remain.
After merging with regression SNP LD, 1095820 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.0042 (0.0069)
Lambda GC: 1.0042
Mean Chi^2: 1.0106
Intercept: 1.0049 (0.0075)
Ratio: 0.4596 (0.7066)
Analysis finished at Thu Oct 17 14:44:23 2019
Total time elapsed: 58.64s
{
"af_correlation": 0.9031,
"inflation_factor": 1,
"mean_EFFECT": -4.3558e-06,
"n": "-Inf",
"n_snps": 9851866,
"n_clumped_hits": 0,
"n_p_sig": 0,
"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": 0,
"n_miss_AF_reference": 41175,
"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": 1095820,
"ldsc_nsnp_merge_regression_ld": 1095820,
"ldsc_observed_scale_h2_beta": 0.0042,
"ldsc_observed_scale_h2_se": 0.0069,
"ldsc_intercept_beta": 1.0049,
"ldsc_intercept_se": 0.0075,
"ldsc_lambda_gc": 1.0042,
"ldsc_mean_chisq": 1.0106,
"ldsc_ratio": 0.4623
}
name | value |
---|---|
af_correlation | FALSE |
inflation_factor | FALSE |
n | TRUE |
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 | 58 | 0 | 4855320 | 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 | N | 4856607 | 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 | 8.665988e+00 | 5.766907e+00 | 1.0000000 | 4.000000e+00 | 8.000000e+00 | 1.300000e+01 | 2.200000e+01 | ▇▅▅▂▂ |
numeric | POS | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 7.858716e+07 | 5.666249e+07 | 828.0000000 | 3.186610e+07 | 6.895414e+07 | 1.146625e+08 | 2.492385e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -4.400000e-06 | 1.904700e-03 | -0.0117570 | -1.227100e-03 | -1.290000e-05 | 1.210400e-03 | 1.280900e-02 | ▁▂▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 1.852400e-03 | 3.874000e-04 | 0.0014081 | 1.522700e-03 | 1.715500e-03 | 2.103400e-03 | 5.361300e-03 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.982469e-01 | 2.890363e-01 | 0.0000016 | 2.500000e-01 | 5.000000e-01 | 7.499995e-01 | 1.000000e+00 | ▇▇▇▇▇ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.982472e-01 | 2.890081e-01 | 0.0000016 | 2.480758e-01 | 4.981786e-01 | 7.481318e-01 | 9.999999e-01 | ▇▇▇▇▇ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 3.578227e-01 | 2.353576e-01 | 0.0721800 | 1.547620e-01 | 2.948590e-01 | 5.238535e-01 | 9.278200e-01 | ▇▅▃▂▂ |
numeric | AF_reference | 41175 | 0.9915219 | NA | NA | NA | NA | NA | NA | NA | 3.506330e-01 | 2.329306e-01 | 0.0000000 | 1.585460e-01 | 2.963260e-01 | 5.127800e-01 | 1.000000e+00 | ▇▇▅▃▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 49298 | rs200943160 | T | C | -0.0057884 | 0.0025950 | 0.0259998 | 0.0257091 | 0.623812 | 0.7821490 | NA |
1 | 54676 | rs2462492 | C | T | 0.0041655 | 0.0025875 | 0.1100001 | 0.1074239 | 0.399144 | NA | NA |
1 | 86028 | rs114608975 | T | C | 0.0047636 | 0.0041189 | 0.2500000 | 0.2474671 | 0.103536 | 0.0277556 | NA |
1 | 91536 | rs6702460 | G | T | -0.0016627 | 0.0025450 | 0.5099998 | 0.5135541 | 0.455916 | 0.4207270 | NA |
1 | 234313 | rs8179466 | C | T | 0.0026076 | 0.0050330 | 0.5999997 | 0.6043826 | 0.074455 | NA | NA |
1 | 534192 | rs6680723 | C | T | -0.0043182 | 0.0028986 | 0.1400000 | 0.1362877 | 0.242057 | NA | NA |
1 | 546697 | rs12025928 | A | G | -0.0049728 | 0.0035965 | 0.1700000 | 0.1667652 | 0.912862 | NA | NA |
1 | 693731 | rs12238997 | A | G | 0.0006533 | 0.0024169 | 0.7899998 | 0.7869167 | 0.117313 | 0.1417730 | NA |
1 | 706368 | rs55727773 | A | G | -0.0010513 | 0.0017940 | 0.5600000 | 0.5578814 | 0.513304 | 0.2751600 | NA |
1 | 722670 | rs116030099 | T | C | -0.0006646 | 0.0029276 | 0.8200001 | 0.8204194 | 0.102736 | 0.0413339 | NA |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51202748 | rs9616963 | A | G | 0.0000539 | 0.0028114 | 0.9800000 | 0.9847117 | 0.073992 | 0.0391374 | NA |
22 | 51208537 | rs72619593 | G | A | 0.0026393 | 0.0023896 | 0.2700001 | 0.2693843 | 0.120936 | 0.1142170 | NA |
22 | 51210289 | rs112565862 | C | T | 0.0027859 | 0.0023832 | 0.2399999 | 0.2424289 | 0.129762 | 0.1018370 | NA |
22 | 51211106 | rs9628250 | T | C | -0.0013834 | 0.0017738 | 0.4400003 | 0.4354483 | 0.271468 | 0.1671330 | NA |
22 | 51211392 | rs3888396 | T | C | 0.0024441 | 0.0023620 | 0.2999998 | 0.3007736 | 0.132383 | 0.1641370 | NA |
22 | 51212875 | rs2238837 | A | C | 0.0012359 | 0.0016862 | 0.4600002 | 0.4635847 | 0.331351 | 0.3724040 | NA |
22 | 51213613 | rs34726907 | C | T | -0.0029294 | 0.0022377 | 0.1900002 | 0.1904824 | 0.126422 | 0.1727240 | NA |
22 | 51216564 | rs9616970 | T | C | -0.0028256 | 0.0022289 | 0.2000000 | 0.2049012 | 0.126887 | 0.1563500 | NA |
22 | 51219006 | rs28729663 | G | A | -0.0025923 | 0.0021820 | 0.2300001 | 0.2348232 | 0.136315 | 0.2052720 | NA |
22 | 51237063 | rs3896457 | T | C | 0.0024649 | 0.0017226 | 0.1499999 | 0.1524584 | 0.298393 | 0.2050720 | NA |
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