idr-sequence-predict datasets: inputs, controls, feature rankings, and consensus region calls

This record includes datasets used by the idr-sequence-predict Snakemake pipeline, designed for proteome-wide identification of intrinsically disordered sequence fragments similar to a small positive set, such as transactivation-domain-like IDRs. This dataset mainly includes the files for the prediction of acidic/hydrophobic short IDRs within TFs across the proteome, based on a small curated dataset. The workflow can expand sequences with sliding windows, compute features using the published idr.mol.feats toolkit, develop control regimes, train multiple ML models, and produce proteome-wide predictions. Predicted fragments are summarised at consensus thresholds, merged into regions, and exported as FASTA files for further analysis. Contents include example inputs, control ID lists, feature importance rankings, selected feature sets, trained models, prediction lists, consensus fragment lists (e.g., 100/95/90/85%), merged region tables, and FASTA sequences of merged regions. The pipeline code is available on GitHub (https://doi.org/10.5281/zenodo.18375255); the feature generator idr.mol.feats is an external dependency (https://github.com/IPritisanac/idr.mol.feats). For reproduction instructions, see the GitHub README for environment setup, configuration, and Snakemake commands.本数据集记录包含idr-sequence-predict Snakemake工作流所使用的数据集，该工作流旨在全蛋白质组范围内鉴定与小型阳性集（如反式激活结构域样内在无序区域（intrinsically disordered regions, IDRs））相似的内在无序序列片段。本数据集主要涵盖基于小型精选数据集、用于预测全蛋白质组中转录因子（transcription factors, TFs）内酸性/疏水短内在无序区域的相关文件。该工作流支持通过滑动窗口扩展序列、使用已发表的idr.mol.feats工具包计算特征、构建对照体系、训练多类机器学习（machine learning, ML）模型，并生成全蛋白质组范围的预测结果。预测得到的片段将基于共识阈值进行汇总、合并为区域，并导出为FASTA格式文件以供后续分析。数据集内容包含示例输入文件、对照ID列表、特征重要性排名、精选特征集、训练完成的模型、预测结果列表、共识片段列表（如100/95/90/85%阈值版本）、合并区域表以及合并区域的FASTA序列。该工作流的代码已开源至GitHub（https://doi.org/10.5281/zenodo.18375255）；其特征生成工具idr.mol.feats为外部依赖项，开源地址为https://github.com/IPritisanac/idr.mol.feats。如需复现实验结果，请参考该GitHub仓库的README文档，其中包含环境配置、参数设置及Snakemake运行命令的详细说明。