GSE145173 - Decoding myofibroblast origins in human kidney fibrosis

[ofanobilbao]

GSE145173 - Decoding myofibroblast origins in human kidney fibrosis

Project short name:

Kramann-Human-Smartseq2

Primary Wrangler:

Arsenios Chatzigeorgiou @arschat

Secondary Wrangler:

Link to Ingest

• https://contribute.data.humancellatlas.org/projects/detail?uuid=128952c1-1906-4746-b4dd-6a10d1ff52d0&tab=project

Associated files

• Google Drive: https://drive.google.com/drive/folders/1aZdaFpbHb8R7LKEIPZ9WnLdVNIODIjv_?usp=sharing

Published study links

• Paper: https://www.nature.com/articles/s41586-020-2941-1

• Accessioned data: GSE145173, GSE144528

Key Events

• [x] Convert published metadata to HCA spreadsheet
• [ ] Manually curate dataset to meet HCA metadata standard
• [ ] Collect any matrix and cell-type annotation files
• [ ] Upload sheet to validate metadata
• [ ] Transfer raw files to ingest to validate data files
• [ ] Check linking using ingest graph validator
• [ ] Ask the Secondary Wrangler for an end-to-end review of the project. Ask the Expertise Wrangler to review specific tabs if needed
• [ ] Submit dataset to Production
• [ ] Complete the Export SOP
• [ ] Convert project data to SCEA format following the SCEA conversion SOP if appropriate

[arschat]

Number of mice samples not clear, neither for 10x data nor for Smart-Seq2. Contacted corresponding author to clarify.

[arschat]

Will proceed only with human data.

[arschat]

Deleted ncbi-cloud mouse data.

locate the sra_metadata_UUID.csv file that was created on cloud syncing. download file locally aws s3 cp s3://hca-ncbi-cloud-data/sra_metadata_b2338de6-2faa-4d5b-b731-4a8ba54a3212.csv . validate that the submission column has the correct SRA number(s) awk -F',' '{ print $43}' sra_metadata_b2338de6-2faa-4d5b-b731-4a8ba54a3212.csv | uniq save sra run IDs awk -F',' '{ print $1}' sra_metadata_b2338de6-2faa-4d5b-b731-4a8ba54a3212.csv > rm_ncbi_cloud_s3.csv read file with sra run IDs and delete corresponding directories in ncbi-cloud storage while read p; do aws s3 rm s3://hca-ncbi-cloud-data/$p --recursive; done < rm_ncbi_cloud_s3.csv delete sra_metadata_UUID.csv aws s3 rm s3://hca-ncbi-cloud-data/sra_metadata_b2338de6-2faa-4d5b-b731-4a8ba54a3212.csv

[anu-shiva]

@arschat to contact contributors for donor/specimen info

[arschat]

No update here, commenting just to specifying where dataset is stuck:

Inconsistent donor numbers between Supplementary Table 1 and Source Data Extended Data Fig. 1. See patients_table spreadsheet in google drive for more info. Possibly multiple specimens per donor not mentioned in paper.

Still waiting for author to reply.

[arschat]

Three follow-up emails has been sent from February, without an answer. See here and here