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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}
 

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/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

QC metrics

Metrics

Metrics

{
    "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
}
 

Flags

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

Definitions

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 SNPs
  • n_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:
    • alleles other than A, C, G or T.
    • P-values < 0 or > 1.
    • negative or infinite standard errors (<= 0 or = Infinity).
    • infinite beta estimates or allele frequencies < 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.
    • \(\widehat{\beta_j^{std}} = \sqrt{\frac{{z}_j^2 / ({z}_j^2 + n -2)}{2 \times {MAF}_j \times (1 - {MAF}_j)}} \times sign({z}_j)\),
    • \({z}_j = \frac{\beta_j}{{se}_j}\),
    • 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 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.
    • \(\texttt{mean_diff2} = \sum_{j} \frac{\widehat{\beta_j^{std}} - \beta^{\prime}_j}{\texttt{n_snps}}\)
    • \(\beta^{\prime}_j = \frac{\beta_j}{\widehat{\texttt{sd2}}_{y}}\)
  • 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<*>: 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 > 0.5
  • ldsc_intercept_beta: ldsc_intercept_beta > 1.5
  • n_clumped_hits: n_clumped_hits > 1000
  • r2_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 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 ▁▁▇▁▁

Head and tail

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

bcf preview

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
1   723891  rs2977670   G   C   .   PASS    .   ES:SE:LP:SS:ID  -0.0084:0.015:0.247184:51750:rs2977670
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
1   780785  rs2977612   T   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0001:0.0062:0.00524306:51750:rs2977612
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
1   785050  rs2905062   G   A   .   PASS    .   ES:SE:LP:SS:ID  -0.0006:0.0063:0.0363538:51750:rs2905062
1   785989  rs2980300   T   C   .   PASS    .   ES:SE:LP:SS:ID  -0.0027:0.0061:0.182831:51750:rs2980300
1   793947  rs2519031   A   G   .   PASS    .   ES:SE:LP:SS:ID  -0.012:0.01:0.635074:51750:rs2519031
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