File path: LncReader/test/Mouse_coding_lncRNA_test_dataset.fa
This test dataset contains data specifically for mouse coding long non-coding RNAs (lncRNAs).
File path: LncReader/test/Drosophila_coding_lncRNA_test_dataset.fa
Similarly, this test dataset includes data specifically for fruit fly coding long non-coding RNAs (lncRNAs).
File path: LncReader/test/RNA-Ribosome-MS.xlsx
This test dataset includes data specifically for leukaemia cell lines.
Prepare your input file, which should be in fasta format. For example, the file name could be input.fasta
.
Define a name for your output file, which will be used to store the results processed by the script. For example, you might name your output file output.txt
.
Open a terminal (Linux or MacOS) or Command Prompt/PowerShell (Windows).
Use the cd
command to navigate to the directory where your script is saved. For example:
cd LncReader/myPackage/
Use the following command to run the script, replacing <input_file> and <output_file> with your actual file paths.
python run_lncReader.py <input_file> <output_file>
For example:
python run_lncReader.py ../test/Drosophila_coding_lncRNA_test_dataset.fa output.txt
The output file will contain the identifier of each sequence, the calculated score (the probility of dual functional lncRNA), and the sequence itself. For example:
>Sequence1 0.4789213 GATTACAGATTACA...
>Sequence2 0.5293812 GTCAGTCAGTCAGT...
...
We aim to explore whether LncReader provides a sophisticated and practical tool to identify dual functional lncRNAs and explore potentially lncRNA-encoded micropeptides, which might assist dissection the key roles of dual functional lncRNAs in either physiology or pathology conditions.
The research of LncReader is online. Please cite us with LncReader: identification of dual functional long noncoding RNAs using a multi-head self-attention mechanism