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/cee7629b-3402-4b4c-82fd-5413a6bd64ff/call-ldsc/inputs/-261021446/ieu-b-5122.vcf.gz \
--ref-ld-chr /data/ref/eur_w_ld_chr/ \
--out /data/igd/ieu-b-5122/ldsc.txt \
--w-ld-chr /data/ref/eur_w_ld_chr/ 

Beginning analysis at Mon Apr 22 13:41:33 2024
Reading summary statistics from /data/cromwell-executions/qc/cee7629b-3402-4b4c-82fd-5413a6bd64ff/call-ldsc/inputs/-261021446/ieu-b-5122.vcf.gz ...
Read summary statistics for 0 SNPs.
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.
Traceback (most recent call last):
  File "./ldsc/ldsc.py", line 647, in <module>
    sumstats.estimate_h2(args, log)
  File "/ldsc/ldscore/sumstats.py", line 330, in estimate_h2
    args, log, args.h2)
  File "/ldsc/ldscore/sumstats.py", line 252, in _read_ld_sumstats
    sumstats = _merge_and_log(ref_ld, sumstats, 'reference panel LD', log)
  File "/ldsc/ldscore/sumstats.py", line 238, in _merge_and_log
    raise ValueError(msg.format(N=len(sumstats), F=noun))
ValueError: After merging with reference panel LD, 0 SNPs remain.

Analysis finished at Mon Apr 22 13:42:42 2024
Total time elapsed: 1.0m:9.43s

QC metrics

Metrics

Metrics

{
    "af_correlation": "NA",
    "inflation_factor": 1.1713,
    "mean_EFFECT": 0.0001,
    "n": "-Inf",
    "n_snps": 10032271,
    "n_clumped_hits": 18,
    "n_p_sig": 1607,
    "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": 10032271,
    "n_miss_AF_reference": 412549,
    "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": 0,
    "ldsc_nsnp_merge_regression_ld": "NA",
    "ldsc_observed_scale_h2_beta": "NA",
    "ldsc_observed_scale_h2_se": "NA",
    "ldsc_intercept_beta": "NA",
    "ldsc_intercept_se": "NA",
    "ldsc_lambda_gc": "NA",
    "ldsc_mean_chisq": "NA",
    "ldsc_ratio": "NA"
}

Flags

name value
af_correlation NA
inflation_factor FALSE
n TRUE
is_snpid_non_unique TRUE
mean_EFFECT_nonfinite FALSE
mean_EFFECT_05 FALSE
mean_EFFECT_01 FALSE
mean_chisq NA
n_p_sig TRUE
miss_EFFECT FALSE
miss_SE FALSE
miss_PVAL FALSE
ldsc_ratio NA
ldsc_intercept_beta NA
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 232939 0.9767810 3 58 0 9798602 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 10032271 0.0000000 NA NA NA NA NA NaN : NA NA NA NA NA NA NA NA
logical N 10032271 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 5.752624e+00 4.106101e+00 1.0000 3.000000e+00 5.000000e+00 8.000000e+00 2.100000e+01 ▇▅▂▁▁
numeric POS 0 1.0000000 NA NA NA NA NA NA NA 8.982537e+07 6.168103e+07 10469.0000 3.442007e+07 8.452336e+07 1.332326e+08 2.492314e+08 ▇▆▆▃▁
numeric EFFECT 0 1.0000000 NA NA NA NA NA NA NA 1.490000e-04 3.961940e-02 -0.5807 -5.700000e-03 -1.000000e-04 5.700000e-03 1.478200e+00 ▁▇▁▁▁
numeric SE 0 1.0000000 NA NA NA NA NA NA NA 2.376630e-02 3.067160e-02 0.0021 3.000000e-03 8.500000e-03 3.310000e-02 1.478000e-01 ▇▂▁▁▁
numeric PVAL 0 1.0000000 NA NA NA NA NA NA NA 4.736320e-01 2.965838e-01 0.0000 2.098998e-01 4.653996e-01 7.306006e-01 1.000000e+00 ▇▆▆▆▆
numeric PVAL_ztest 0 1.0000000 NA NA NA NA NA NA NA 4.737207e-01 2.966135e-01 0.0000 2.097558e-01 4.658997e-01 7.302240e-01 1.000000e+00 ▇▆▆▆▆
numeric AF_reference 412549 0.9588778 NA NA NA NA NA NA NA 1.582568e-01 2.354441e-01 0.0000 5.391400e-03 3.873800e-02 2.138580e-01 1.000000e+00 ▇▁▁▁▁

Head and tail

CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
1 30923 rs806731 G T -0.0094 0.0070 0.1788999 0.1793182 NA 0.8724040 NA
1 51479 rs116400033 T A 0.0035 0.0048 0.4625003 0.4658997 NA 0.1281950 NA
1 52238 rs2691277 T G -0.0149 0.0146 0.3078003 0.3074687 NA 0.9217250 NA
1 54353 rs140052487 C A -0.0876 0.1141 0.4423999 0.4426372 NA 0.0089856 NA
1 54490 rs141149254 G A 0.0028 0.0054 0.5959996 0.6040965 NA 0.0960463 NA
1 55164 rs3091274 C A -0.0234 0.0168 0.1655000 0.1636630 NA 0.9233230 NA
1 55326 rs3107975 T C -0.0149 0.0228 0.5125002 0.5134283 NA 0.0459265 NA
1 55852 rs184233019 G C 0.0086 0.0385 0.8229999 0.8232424 NA 0.0007987 NA
1 58814 rs114420996 G A 0.0032 0.0069 0.6438000 0.6428139 NA 0.1090260 NA
1 59040 rs62637815 T C 0.0002 0.0069 0.9719000 0.9768761 NA 0.0615016 NA
CHROM POS ID REF ALT EFFECT SE PVAL PVAL_ztest AF AF_reference N
20 62960292 rs11698187 A G -0.0012 0.0062 0.8405000 0.8465295 NA 0.0137780 NA
20 62962048 rs186809596 G A 0.0150 0.0242 0.5347995 0.5353666 NA 0.0019968 NA
20 62962869 rs140775622 C T -0.0043 0.0035 0.2202997 0.2192325 NA 0.0788738 NA
20 62962955 rs184838619 G A -0.0152 0.0370 0.6818000 0.6812113 NA 0.0007987 NA
20 62963094 rs188402642 T C -0.0095 0.0419 0.8213000 0.8206335 NA 0.0003994 NA
21 29695296 NA A C -0.0191 0.0657 0.7718004 0.7712690 NA NA NA
21 29926213 NA A G 0.0000 0.0230 0.9994000 1.0000000 NA NA NA
21 29933472 rs1486874840 A T 0.0079 0.0527 0.8803999 0.8808395 NA NA NA
21 29939303 rs1020851252 T C 0.0270 0.0799 0.7352008 0.7354217 NA NA NA
21 29940577 rs1348236229 A G 0.1303 0.0867 0.1329000 0.1328691 NA NA NA

bcf preview

1   30923   rs1165072081    G   T   .   PASS    .   ES:SE:LP:ID -0.0094:0.007:0.74739:rs1165072081
1   51479   rs116400033 T   A   .   PASS    .   ES:SE:LP:ID 0.0035:0.0048:0.334888:rs116400033
1   52238   rs2691277   T   G   .   PASS    .   ES:SE:LP:ID -0.0149:0.0146:0.511731:rs2691277
1   54353   rs140052487 C   A   .   PASS    .   ES:SE:LP:ID -0.0876:0.1141:0.354185:rs140052487
1   54490   rs141149254 G   A   .   PASS    .   ES:SE:LP:ID 0.0028:0.0054:0.224754:rs141149254
1   55164   rs3091274   C   A   .   PASS    .   ES:SE:LP:ID -0.0234:0.0168:0.781202:rs3091274
1   55326   rs3107975   T   C   .   PASS    .   ES:SE:LP:ID -0.0149:0.0228:0.290306:rs3107975
1   55852   rs184233019 G   C   .   PASS    .   ES:SE:LP:ID 0.0086:0.0385:0.0846002:rs184233019
1   58814   rs114420996 G   A   .   PASS    .   ES:SE:LP:ID 0.0032:0.0069:0.191249:rs114420996
1   59040   rs62637815  T   C   .   PASS    .   ES:SE:LP:ID 0.0002:0.0069:0.0123784:rs62637815
1   61743   rs184286948 G   C   .   PASS    .   ES:SE:LP:ID 0.0373:0.0227:0.998266:rs184286948
1   63671   rs80011619  G   A   .   PASS    .   ES:SE:LP:ID 0.0016:0.0052:0.116623:rs80011619
1   64649   rs181431124 A   C   .   PASS    .   ES:SE:LP:ID 0.0076:0.012:0.279427:rs181431124
1   66219   rs1557435148    A   T   .   PASS    .   ES:SE:LP:ID 0.0006:0.0137:0.0153377:rs1557435148
1   66457   rs1227875005    T   A   .   PASS    .   ES:SE:LP:ID 0.0326:0.0731:0.183096:rs1227875005
1   67181   rs28503582  A   G   .   PASS    .   ES:SE:LP:ID 0.0138:0.0239:0.247875:rs28503582
1   77874   rs62641297  G   A   .   PASS    .   ES:SE:LP:ID 0.0027:0.0074:0.146606:rs62641297
1   79033   rs2462495   A   G   .   PASS    .   ES:SE:LP:ID -0.0064:0.0493:0.0473528:rs2462495
1   79137   rs143777184 A   T   .   PASS    .   ES:SE:LP:ID 0.1037:0.0607:1.05725:rs143777184
1   82163   rs139113303 G   A   .   PASS    .   ES:SE:LP:ID 0.0006:0.0072:0.0307239:rs139113303
1   82609   rs149189449 C   G   .   PASS    .   ES:SE:LP:ID 0.0009:0.0072:0.045661:rs149189449
1   83084   rs4030326   T   A   .   PASS    .   ES:SE:LP:ID 0.0051:0.014:0.144299:rs4030326
1   83771   rs189906733 T   G   .   PASS    .   ES:SE:LP:ID 0.0132:0.079:0.0616304:rs189906733
1   84139   rs183605470 A   T   .   PASS    .   ES:SE:LP:ID 0.0483:0.1075:0.18502:rs183605470
1   86000   rs140628094 A   C   .   PASS    .   ES:SE:LP:ID 0.1585:0.107:0.857924:rs140628094
1   86028   rs114608975 T   C   .   PASS    .   ES:SE:LP:ID -0.0011:0.007:0.059633:rs114608975
1   86065   rs116504101 G   C   .   PASS    .   ES:SE:LP:ID -0.0017:0.0072:0.0924274:rs116504101
1   86331   rs115209712 A   G   .   PASS    .   ES:SE:LP:ID 0.0035:0.0064:0.235226:rs115209712
1   87021   rs188486692 T   C   .   PASS    .   ES:SE:LP:ID -0.0146:0.0172:0.403843:rs188486692
1   87360   rs180907504 C   T   .   PASS    .   ES:SE:LP:ID 0.0176:0.0153:0.601192:rs180907504
1   87409   rs139490478 C   T   .   PASS    .   ES:SE:LP:ID -0.0009:0.0072:0.0443603:rs139490478
1   87647   rs146836579 T   C   .   PASS    .   ES:SE:LP:ID -0.0028:0.016:0.0659563:rs146836579
1   88169   rs940550    C   T   .   PASS    .   ES:SE:LP:ID -0.0034:0.0047:0.332827:rs940550
1   88172   rs940551    G   A   .   PASS    .   ES:SE:LP:ID -0.0122:0.0074:1.00846:rs940551
1   88177   rs143215837 G   C   .   PASS    .   ES:SE:LP:ID -0.0112:0.0075:0.876475:rs143215837
1   88188   rs148331237 C   A   .   PASS    .   ES:SE:LP:ID -0.0227:0.0231:0.487582:rs148331237
1   88236   rs1461774651    C   T   .   PASS    .   ES:SE:LP:ID 0.0045:0.0221:0.0772227:rs1461774651
1   88316   rs113759966 G   A   .   PASS    .   ES:SE:LP:ID -0.0094:0.0075:0.683401:rs113759966
1   88338   rs55700207  G   A   .   PASS    .   ES:SE:LP:ID 0.0044:0.0073:0.260744:rs55700207
1   88370   rs185487977 G   A   .   PASS    .   ES:SE:LP:ID -0.0091:0.0267:0.134245:rs185487977
1   88710   rs186575039 C   G   .   PASS    .   ES:SE:LP:ID 0.0002:0.0072:0.00961674:rs186575039
1   89946   rs138808727 A   T   .   PASS    .   ES:SE:LP:ID 0.0001:0.0048:0.00974997:rs138808727
1   91190   rs143856811 G   A   .   PASS    .   ES:SE:LP:ID 0.0001:0.007:0.00388252:rs143856811
1   91536   rs1251109649    G   T   .   PASS    .   ES:SE:LP:ID 0.0008:0.0043:0.066614:rs1251109649
1   91581   rs1524604   G   A   .   PASS    .   ES:SE:LP:ID -0.0061:0.0039:0.929962:rs1524604
1   92633   rs149776517 C   T   .   PASS    .   ES:SE:LP:ID 0.004:0.0129:0.122398:rs149776517
1   92858   rs147061536 G   T   .   PASS    .   ES:SE:LP:ID 0.0016:0.0047:0.136499:rs147061536
1   92875   rs193157612 T   C   .   PASS    .   ES:SE:LP:ID 0.0026:0.029:0.0317039:rs193157612
1   99671   rs146209971 A   T   .   PASS    .   ES:SE:LP:ID -0.0558:0.0206:2.16775:rs146209971
1   99687   rs139153227 C   T   .   PASS    .   ES:SE:LP:ID -0.01:0.0078:0.694864:rs139153227