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README.txt

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-# K-mer–based Sequence Predictor
-
-This Space predicts the most likely group of **unknown sequences** using
-group-specific **unique k-mers** generated by the companion Space:
-
-?? **Unique k-mer discovery Space:**  
-https://huggingface.co/spaces/<your-username>/<space-1-name>
-
----
-
-## Overview
-
-This tool assigns each unknown sequence to a group by detecting
-group-specific k-mers and computing a confidence score.
-It is designed to work directly with the `kmer_results.zip`
-produced by the Unique k-mer discovery Space.
-
----
-
-## Inputs
-
-### 1. Unknown sequences
-Upload one or more FASTA files containing unknown sequences:
-- `.fa`, `.fasta`, `.fas`, `.fna`
-
-### 2. K-mer results ZIP
-Upload **`kmer_results.zip`** generated by the Unique k-mer discovery Space.
-
-> ?? This Space only accepts ZIP input for k-mers to ensure compatibility
-> and reproducibility.
-
----
-
-## Parameters
-
-- **Sequence type**
-  - `dna` or `protein`
-- **Mode**
-  - **fast**: exact k-mer matching (recommended)
-  - **full**: alignment-based matching + Fisher test + FDR (slower)
-- **Identity / Coverage / FDR**
-  - Used only in *full* mode
-
----
-
-## Outputs
-
-- **predictions_by_alignment.csv**
-  - One row per sequence
-  - Predicted group and confidence metrics
-- **predicted_results_summary.png**
-  - Group counts and confidence distribution
-- **prediction_outputs.zip**
-  - ZIP containing all outputs
-
----
-
-## Performance notes
-
-- The **fast** mode is recommended for large datasets.
-- The **full** mode is computationally intensive and best suited for
-  small validation sets.
-
----
-
-## Citation
-
-If you use this tool, please cite:
-
-Muhamed-Kheir TAHA, Institut Pasteur, Paris France.
-
----
-
-## License
-Others