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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_6177_2.vcf.gz --id UKB-b:14395 --data /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukbiobank/raw-output/data.batch_6177_2.txt.gz --cohort_cases 51976 --cohort_controls 157662 --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",
"file_date": "2019-09-13T07:23:03.047163",
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"bcftools_viewCommand": "view -T ^/mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14395/mac_discard.txt -Oz /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14395/UKB-b-14395_raw.vcf.gz; Date=Thu Oct 17 12:30:31 2019",
"bcftools_viewCommand.1": "view -h /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/ukb-b-14395/ukb-b-14395.vcf.gz; Date=Sat May 9 13:17:36 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-14395/UKB-b-14395_data.vcf.gz \
--ref-ld-chr ../reference/eur_w_ld_chr/ \
--out /mnt/storage/private/mrcieu/research/scratch/IGD/data/public/UKB-b-14395/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-14395/UKB-b-14395_data.vcf.gz ...
Read summary statistics for 8296230 SNPs.
Dropped 6697 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, 1284372 SNPs remain.
After merging with regression SNP LD, 1284372 SNPs remain.
Using two-step estimator with cutoff at 30.
Total Observed scale h2: 0.1028 (0.0049)
Lambda GC: 1.3373
Mean Chi^2: 1.4708
Intercept: 1.0408 (0.0107)
Ratio: 0.0866 (0.0227)
Analysis finished at Thu Oct 17 14:44:39 2019
Total time elapsed: 1.0m:14.43s
{
"af_correlation": 0.9446,
"inflation_factor": 1.2544,
"mean_EFFECT": -6.2975e-07,
"n": "-Inf",
"n_snps": 9851866,
"n_clumped_hits": 76,
"n_p_sig": 4535,
"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": 78021,
"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": 1284372,
"ldsc_nsnp_merge_regression_ld": 1284372,
"ldsc_observed_scale_h2_beta": 0.1028,
"ldsc_observed_scale_h2_se": 0.0049,
"ldsc_intercept_beta": 1.0408,
"ldsc_intercept_se": 0.0107,
"ldsc_lambda_gc": 1.3373,
"ldsc_mean_chisq": 1.4708,
"ldsc_ratio": 0.0867
}
name | value |
---|---|
af_correlation | FALSE |
inflation_factor | TRUE |
n | TRUE |
is_snpid_non_unique | FALSE |
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 |
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 | 8289563 | 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 | 8296230 | 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 | 8.655224e+00 | 5.762352e+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 | 7.873728e+07 | 5.638700e+07 | 828.0000000 | 3.232778e+07 | 6.922757e+07 | 1.145508e+08 | 2.492385e+08 | ▇▆▅▂▁ |
numeric | EFFECT | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | -6.000000e-07 | 3.810600e-03 | -0.0400819 | -1.789800e-03 | -2.500000e-06 | 1.781700e-03 | 4.138950e-02 | ▁▁▇▁▁ |
numeric | SE | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.997200e-03 | 1.920600e-03 | 0.0012787 | 1.493200e-03 | 2.135200e-03 | 3.993800e-03 | 2.007990e-02 | ▇▂▁▁▁ |
numeric | PVAL | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.617199e-01 | 2.992092e-01 | 0.0000000 | 1.900002e-01 | 4.500005e-01 | 7.199992e-01 | 1.000000e+00 | ▇▆▆▆▆ |
numeric | PVAL_ztest | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 4.617210e-01 | 2.991838e-01 | 0.0000000 | 1.930178e-01 | 4.485557e-01 | 7.204203e-01 | 1.000000e+00 | ▇▆▆▆▆ |
numeric | AF | 0 | 1.0000000 | NA | NA | NA | NA | NA | NA | NA | 2.374970e-01 | 2.602588e-01 | 0.0067340 | 3.019300e-02 | 1.255330e-01 | 3.761318e-01 | 9.932660e-01 | ▇▂▂▁▁ |
numeric | AF_reference | 78021 | 0.9905956 | NA | NA | NA | NA | NA | NA | NA | 2.369845e-01 | 2.521466e-01 | 0.0000000 | 2.995210e-02 | 1.413740e-01 | 3.724040e-01 | 1.000000e+00 | ▇▂▂▁▁ |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 49298 | rs200943160 | T | C | 0.0002489 | 0.0023500 | 0.9199999 | 0.9156366 | 0.624267 | 0.7821490 | NA |
1 | 54676 | rs2462492 | C | T | 0.0021331 | 0.0023335 | 0.3599996 | 0.3606543 | 0.399695 | NA | NA |
1 | 86028 | rs114608975 | T | C | -0.0016320 | 0.0037144 | 0.6600001 | 0.6603849 | 0.103686 | 0.0277556 | NA |
1 | 91536 | rs6702460 | G | T | 0.0022015 | 0.0022958 | 0.3400001 | 0.3376096 | 0.456603 | 0.4207270 | NA |
1 | 234313 | rs8179466 | C | T | 0.0057546 | 0.0045147 | 0.2000000 | 0.2024301 | 0.074622 | NA | NA |
1 | 534192 | rs6680723 | C | T | 0.0032476 | 0.0026210 | 0.2200002 | 0.2153298 | 0.240711 | NA | NA |
1 | 546697 | rs12025928 | A | G | -0.0026322 | 0.0032702 | 0.4199997 | 0.4208629 | 0.913394 | NA | NA |
1 | 693731 | rs12238997 | A | G | -0.0002608 | 0.0021990 | 0.9100000 | 0.9055768 | 0.115933 | 0.1417730 | NA |
1 | 705882 | rs72631875 | G | A | 0.0024277 | 0.0032161 | 0.4500005 | 0.4503396 | 0.067538 | 0.0315495 | NA |
1 | 706368 | rs55727773 | A | G | -0.0009547 | 0.0016276 | 0.5600000 | 0.5575140 | 0.516309 | 0.2751600 | NA |
CHROM | POS | ID | REF | ALT | EFFECT | SE | PVAL | PVAL_ztest | AF | AF_reference | N |
---|---|---|---|---|---|---|---|---|---|---|---|
22 | 51219006 | rs28729663 | G | A | 0.0002507 | 0.0019624 | 0.9000000 | 0.8983468 | 0.137965 | 0.2052720 | NA |
22 | 51219387 | rs9616832 | T | C | 0.0001913 | 0.0025493 | 0.9400001 | 0.9401871 | 0.073841 | 0.0654952 | NA |
22 | 51219704 | rs147475742 | G | A | 0.0009196 | 0.0034157 | 0.7899998 | 0.7877639 | 0.042049 | 0.0473243 | NA |
22 | 51221190 | rs369304721 | G | A | 0.0006427 | 0.0034076 | 0.8499999 | 0.8503890 | 0.049860 | NA | NA |
22 | 51221731 | rs115055839 | T | C | -0.0000060 | 0.0025516 | 1.0000000 | 0.9981116 | 0.073283 | 0.0625000 | NA |
22 | 51222100 | rs114553188 | G | T | -0.0014483 | 0.0030074 | 0.6300007 | 0.6301135 | 0.054302 | 0.0880591 | NA |
22 | 51223637 | rs375798137 | G | A | -0.0013986 | 0.0030222 | 0.6400000 | 0.6435304 | 0.053924 | 0.0788738 | NA |
22 | 51229805 | rs9616985 | T | C | 0.0000557 | 0.0025610 | 0.9800000 | 0.9826527 | 0.073082 | 0.0730831 | NA |
22 | 51232488 | rs376461333 | A | G | -0.0056638 | 0.0060320 | 0.3500000 | 0.3477536 | 0.020066 | NA | NA |
22 | 51237063 | rs3896457 | T | C | 0.0006653 | 0.0015683 | 0.6700003 | 0.6714035 | 0.298014 | 0.2050720 | NA |
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