Galaxy cannot recognize csv files

I am trying to develop tools on my local galaxy. The tool works fine on another desktop, and when I uploaded a csv file, it shows the file name with parentheses (as csv). However, on this desktop, it cannot recognize the csv files i uploaded, and thus are not able to analyze the csv files. How to make galaxy to recognize my csv files?

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Hi @zhaoranz

Clarifications to help with troubleshooting:

  • Are you connecting to the same Galaxy server each time? Which servers for each? Please share base URL(s) if public or note if non-public and what the sources were (can be generalized if private). Including the Galaxy version and last time updated – if you know or one/both are yours. You categorized this as using Galaxy Main, but also state using a local in your question (?).

What results from Upload if using a public server? Good choices to test with:

Where was the original data sourced from, before upload, and how uploaded:

  • Local file or public source (base URL)? For each.
  • Browser upload or FTP or URL or Pasted in raw data into the Upload tool? For each.
  • Autodetect for datatype, or set by you? For each.

This shouldn’t matter – but just in case:

  • What web browser was used for Upload? Chrome, Safari, Firefox…? For each.
  • What OS did you access Galaxy from? MAC OSX, Windows, Lunix? For each.

Thanks! Consolidate the extra info per Galaxy server, for each data Upload. Will help to troubleshoot.

Hello, thanks for the help!!

I have solved the problem by re-writing my csv file without separating data with tab. then galaxy can recognize it. This problem happened in Ubuntu 18.

Hi @zhaoranz

Super, glad you found the problem and were able to fix it. Sounds like it was a data format issue – if I am understanding your reply correctly.

Uploaded data is format checked (first few lines). If data doesn’t meet the datatype specification (guessed with “autodetect” or directly assigned), issues can come up. The goal is to catch out-of-specification format problems early – before they lead to tool errors (red dataset with odd error messages, etc) or a putatively successful job (green dataset, sometimes with warning messages) that has scientific content issues – and those are often not obvious/easy to recognize.

Thanks :slight_smile: