Request for Information on sQTL "*.all.tsv.gz" Download Locations

[yangchuhua]

To Whom It May Concern,

First and foremost, I would like to express my gratitude for your effort in creating and maintaining the eQTL Catalogue, which has been an invaluable resource for the research community.

I am currently working on a project that requires xQTL data, specifically in the form of ".all.tsv.gz" files for xQTL (quant_method:exon/transcript/transcript reverse/Leafcutter). While I have been able to locate the ".all.tsv.gz" files for eQTLs on the EBI FTP server (http://ftp.ebi.ac.uk/pub/databases/spot/eQTL/sumstats/), I have not been able to find the corresponding files for the xQTL types mentioned above.

Could you please provide guidance on where I can download the "*.all.tsv.gz" files for these xQTLs? Any assistance you can provide would be greatly appreciated, as it would significantly aid my research project.

Thank you in advance for your help. I look forward to hearing from you soon.

Best regards, Chuhua

[kauralasoo]

Dear Chuhua,

Unfortunately we are unable to share the .all.tsv.gz files for the transcript-level quantification methods (exon, transcript, txrevise, Leafcutter) due to their very large size (10+ Tb).

What is the specific use-case that you have in mind? If you are interesting in colocalisation then you should be able to use the .cc.tsv.gz files which contain the full summary statistics for those molecular traits that had at least one significant QTL.

Best wishes, Kaur

[yangchuhua]

Dear Kaur,

Thank you very much for your reply.

PredictDB has developed prediction MASHR-based models for sQTLs, based on the GTEx v8 release data (https://predictdb.org/post/2021/07/21/gtex-v8-models-on-eqtl-and-sqtl/). ↗.)

I am interested in building MASHR-based models using your comprehensive summary statistics of sQTLs (Leafcutter).

Would you be able to share the ".all.tsv.gz files" corresponding to the following list?

study_id	dataset_id	study_label	sample_group	tissue_id	tissue_label	condition_label	sample_size	quant_method
QTS000011	QTD000089	FUSION	muscle_naive	UBERON_0001134	muscle	naive	288	leafcutter
QTS000011	QTD000094	FUSION	adipose_naive	UBERON_0001013	adipose	naive	271	leafcutter
QTS000019	QTD000377	Lepik_2017	blood	UBERON_0000178	blood	naive	471	leafcutter
QTS000029	QTD000538	TwinsUK	fat	UBERON_0001013	adipose	naive	381	leafcutter
QTS000029	QTD000548	TwinsUK	skin	UBERON_0002097	skin	naive	370	leafcutter
QTS000029	QTD000553	TwinsUK	blood	UBERON_0000178	blood	naive	195	leafcutter

If sharing these files is not possible, I kindly request that you run the script (https://github.com/stephenslab/gtexresults/blob/master/workflows/fastqtl_to_mash.ipynb) ↗) on your ".all.tsv.gz files" and share the resulting R objects of the MASH input generated by the script.

Best wishes, Chuhua

[kauralasoo]

Dear Chuhua,

Yes, that should be possible. Please send me an email at kaur.alasoo@ut.ee and we can arrange data transfer.

Best, Kaur

[yangchuhua]

Dear Kaur,

Thank you very much.

I have email you at kaur.alasoo@ut.ee.

Best, Chuhua