Comments (3)
Hi,
Please see this wrapper to see how the files should be formatted and sorted (the format for FastQTL/tensorQTL is the same):
https://github.com/broadinstitute/gtex-pipeline/blob/master/qtl/leafcutter/src/cluster_prepare_fastqtl.py
This needs to be better documented and I'll add a standalone version to this repository. Thanks for pointing it out!
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Thanks, I've formatted the input accordingly, and the phenotype_group analysis now runs without issues after setting the coordinate for each intron to the TSS of the gene it maps to.
In a related question I wonder if you could comment on the coordinates to use when running tensorQTL on leafcutter introns without phenotype_groups. For the equivalent fastQTL analysis I typically provide the intron-start and intron-end coordinates as input in the bedfile. However, tensorQTL expects a single-base coordinates (where end = start+1). I've considered using the intron mid-point as a proxy but I wonder if it is possible to mimic the fastQTL approach of using the complete intron region instead (i.e. centered on the full intron)?
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Hi @francois-a
I use https://github.com/broadinstitute/gtex-pipeline/blob/master/qtl/leafcutter/src/cluster_prepare_fastqtl.py output phenotype_group ,but still get 'Groups defined in input do not match phenotype file (check sort order).
leafcutter.phenotype_groups.txt looks like
chr1:17055:17606:clu_4_-:ENSG00000227232.5 ENSG00000227232.5
chr1:17055:17233:clu_4_-:ENSG00000227232.5 ENSG00000227232.5
chr1:17368:17606:clu_4_-:ENSG00000227232.5 ENSG00000227232.5
chr1:17055:17915:clu_4_-:ENSG00000227232.5 ENSG00000227232.5
chr1:17742:17915:clu_4_-:ENSG00000227232.5 ENSG00000227232.5
chr1:18366:24738:clu_5_-:ENSG00000227232.5 ENSG00000227232.5
chr1:16765:16858:clu_21_-:ENSG00000227232.5 ENSG00000227232.5
chr1:15947:16607:clu_20_-:ENSG00000227232.5 ENSG00000227232.5
chr1:495049:497109:clu_6_-:ENSG00000239906.1 ENSG00000239906.1
leafcutter.bed.gz looks like
#chr start end ID EP01 EP02
chr1 29569 29570 chr1:17055:17606:clu_4_-:ENSG00000227232.5 0.9728448646222656 -0.6436624661405189
chr1 29569 29570 chr1:17055:17233:clu_4_-:ENSG00000227232.5 -0.3398869558227139 0.16595345366554864
chr1 29569 29570 chr1:17368:17606:clu_4_-:ENSG00000227232.5 -0.10604641028690409 0.38290377873207204
chr1 29569 29570 chr1:17055:17915:clu_4_-:ENSG00000227232.5 1.0070764565362778 -1.1825607021977453
chr1 29569 29570 chr1:17742:17915:clu_4_-:ENSG00000227232.5 -0.47132492764348966 -0.4698074437133793
chr1 29569 29570 chr1:18366:24738:clu_5_-:ENSG00000227232.5 0.07113184542813797 0.6983021090538163
chr1 29569 29570 chr1:16765:16858:clu_21_-:ENSG00000227232.5 0.8037980146700746 0.4932037806525865
chr1 29569 29570 chr1:15947:16607:clu_20_-:ENSG00000227232.5 0.0840760379764529 0.04758884271101856
chr1 140338 140339 chr1:495049:497109:clu_6_-:ENSG00000239906.1 -1.3746907828020156 -1.1099506748505505
Thanks in advanced!
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Related Issues (20)
- missing tss_distance in cis output HOT 1
- Abnormal results of interaction model HOT 4
- scipy.optimize.newton failed to converge HOT 1
- Warning and Error in tensorQTL trans mode HOT 9
- Memory Allocation Issue during trans-QTL Mapping HOT 3
- Issues with TensorQTL in Trans Mode
- 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 2
- ValueError: array must not contain infs or NaNs
- 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
- Which beta coresponds to which allele in the outputs?
- cis-mapping with interaction
- Errors in the BackgroundGenerator cause main thread to get stuck
- Questions about the `map_permutations` and `apply_permutations` functions
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