Comments (4)
Hi, I'm not able to reproduce this. Can you please check if this still occurs with v1.0.7?
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Hi Francois,
Thanks for your reply.
Just upgraded to v1.0.7 but encountered an error when importing the mixqtl.py from the tensorqtl. It seems to be a minor import syntax error in line#59 of mixqtl.py induced by a typo I believe.
I've tested it on my machine and after removing the asterisk it's good to run. I've submitted a pull request for you to review.
Unfortunately, the inconsistency of tss_distance between cis.map_nominal and indep_df was still there.
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Hi @francois-a ,
I have used v1.0.7 and re-ran all the analyses. I found that there are always ~10% variants that showed inconsistent results between cis.map_nominal() and cis_df().
Here is the example for chromosome 22 in my data. I tested 408 genes and 69805 variants. After matching nominal associations with significant associations, 43 / 408 eQTLs showed inconsistent pval_nominal, slope/slope_se, tss_distance. The allele freq, ma_samples, ma_count.
Nominal associations:
head(nom[index, -1])
phenotype_id variant_id tss_distance af ma_samples ma_count pval_nominal slope slope_se pair
102 DDTL 22:24266726 -42364 0.38367346 603 752 3.084511e-34 0.0054795183 0.0004317051 22:24266726_DDTL
103 KB-226F1.2 22:24267047 -44354 0.38265306 602 750 4.183513e-07 0.0009024401 0.0001770988 22:24267047_KB-226F1.2
104 DDT 22:24245292 -68263 0.33214286 525 651 2.866474e-19 -0.0525704920 0.0057343070 22:24245292_DDT
136 HSCB 22:28339553 -798467 0.15306123 263 300 7.034724e-01 0.0009122025 0.0023957987 22:28339553_HSCB
137 CCDC117 22:28303075 -865588 0.05408163 104 106 1.195958e-01 -0.0037228062 0.0023896908 22:28303075_CCDC117
138 XBP1 22:28629713 -560831 0.16938776 296 332 1.304909e-30 0.1073389800 0.0090110050 22:28629713_XBP1
Significant associations:
head(sig[index,colnames(nom)[-1]])
phenotype_id variant_id tss_distance af ma_samples ma_count pval_nominal slope slope_se pair
102 DDTL 22:24266726 -46829 0.38367346 603 752 9.790065e-49 -0.082714660 0.0053232773 22:24266726_DDTL
103 KB-226F1.2 22:24267047 -42043 0.38265306 602 750 2.517564e-34 0.005490042 0.0004319025 22:24267047_KB-226F1.2
104 DDT 22:24245292 -66109 0.33214286 525 651 1.776509e-08 0.001006383 0.0001771545 22:24245292_DDT
136 HSCB 22:28339553 -940028 0.15306123 263 300 3.107622e-04 0.001176659 0.0003251019 22:28339553_HSCB
137 CCDC117 22:28303075 -834945 0.05408163 104 106 2.647748e-03 0.012170344 0.0040382070 22:28303075_CCDC117
138 XBP1 22:28629713 -538950 0.16938776 296 332 1.030225e-04 0.005427211 0.0013917054 22:28629713_XBP1
And if I plot the pval_nominal between the two results, it looks like this
The allele frequency is consistent
Hope to get some advice from you on how I can dig into and solve the problem.
Thank you!
Cheers,
Angli
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Hi, I'm unable to reproduce this. The TSS distances between the different modes (cis permutations, nominal, independent) are consistent in my tests. Do you have duplicate gene symbols in your inputs? Otherwise, can you share a small subset of your dataset that reproduces the problem?
Edit: resolved (not a TensorQTL issue).
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Related Issues (20)
- Issues with TensorQTL in Trans Mode HOT 1
- AttributeError: 'dict' object has no attribute 'T' tensorqtl HOT 2
- broken link HOT 1
- Tensorqtl installation HOT 3
- No credible sets output from susie.map because pval_nominal=0 HOT 3
- ValueError: array must not contain infs or NaNs HOT 1
- interaction HOT 1
- [Susie] ValueError: prior variance must be non-negative HOT 4
- [trans] trans.map_permutations(): KeyError: 'r2' HOT 2
- [map_trans] R2 not returned in interaction analysis HOT 2
- [pval post-processing] Interaction output for cis/trans HOT 1
- Which beta coresponds to which allele in the outputs? HOT 3
- cis-mapping with interaction HOT 1
- Errors in the BackgroundGenerator cause main thread to get stuck HOT 1
- Questions about the `map_permutations` and `apply_permutations` functions
- cis_independent requires covariate_df HOT 1
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- Any way i can go around this error? HOT 2
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