weiskenyon/aav2_capsid_viability

--- tags: - biology - protein-sequence - aav - regression pretty_name: "AAV2 Capsid Viability Dataset" size_categories: - 100K<n<1M # 289,736 variants source_datasets: - custom # Derived from Bryant et al. 2021, Nature Biotechnology (https://www.nature.com/articles/s41587-020-00793-4) # Dataset Configurations (assuming one file 'aav2_viability_processed.csv' loaded as 'train') configs: - config_name: default data_files: - split: train # Single file defaults to 'train' split path: aav2_processed.csv # Optional but recommended: Dataset structure information # You can often auto-generate this using: datasets-cli dummy-metadata --repo_id your_username/your_dataset_name dataset_info: features: - name: variable_region_sequence dtype: string - name: source_partition dtype: string - name: viral_selection dtype: float32 # Or float64 if that's the precision used - name: vp1_sequence dtype: string - name: vp2_sequence dtype: string - name: vp3_sequence dtype: string - name: edit_distance_from_wt dtype: int32 config_name: default splits: - name: train num_bytes: 568803013 # <-- FILL IN: Get size of your CSV file in bytes num_examples: 289805 download_size: 568579900 # <-- FILL IN: Size of file(s) to download (usually same as dataset_size for single CSV) dataset_size: 568803013 # <-- FILL IN: Total size on disk (usually same as num_bytes for single CSV) --- # AAV2 Capsid Viability Dataset This dataset contains a preprocessed version of the Adeno-associated virus 2 (AAV2) capsid viability dataset from [Bryant et al. 2021](https://www.nature.com/articles/s41587-020-00793-4), including the full VP1, VP2, and VP3 sequences for each variant.  ## Description This processed version of the dataset contains 289,805 variants with the following columns: - `variable_region_sequence` (str): The unique amino acid sequence of the variable region for each AAV2 variant - `source_partition` (str): Metadata field indicating the source partition aka method used to generate the variant in the original paper. - `viral_selection` (float): The viral selection of the variant. See [Viral Selection Values](#viral-selection-values) for more details. - `vp1_sequence` (str): The VP1 sequence of the variant. - `vp2_sequence` (str): The VP2 sequence of the variant. - `vp3_sequence` (str): The VP3 sequence of the variant. - `edit_distance_from_wt` (int): The edit distance from the wild type variable region sequence. ### Preprocessing - We removed 57 variants because they contained a premature stop codon (denoted as "*") in the variable region. - We also removed all instances of variants that had a duplicate sequence in the dataset as in all of these cases multiple viral_selection values were present. This resulted in the removal of 7,108 variants. ### Viral Selection Values The experiments conducted in the paper aimed to generate diverse AAV2 capsid variants far beyond natural diversity while maintaining viability, using machine learning guidance. Viability was assessed using a high-throughput assay measuring the ability of each variant sequence to assemble an integral capsid that packages the viral genome. For each variant, the fitness or 'viral selection' was calculated as the log of the ratio of the variant's read counts in the output 'viral library' pool to the read counts in the input 'DNA library' pool: $$ \text{Viral Selection for Variant i} = log(\frac{n_{i,viral}}{n_{i,DNA}}) $$   ### VP1, VP2, and VP3 sequences [The AAV2 capsid is a 60-unit multimer made up of a 5:5:50 ratio of three viral proteins: VP1, VP2, and VP3. Through alternative splicing and leaky ribosomal scanning, the same mRNA (mRNA9) can give rise to VP2 and VP3, depending on which start codon is used. VP1 is translated from a distinct transcript initiated by the P5 promoter.](https://viralzone.expasy.org/226). We have provided the full VP1, VP2, and VP3 sequences for each variant in the `vp1_sequence`, `vp2_sequence`, and `vp3_sequence` columns respectively. To recreate the full VP1, VP2, and VP3 sequences for each variant, we collected the following wildtype source sequences: - VP1 Source Sequence: [YP_680426.1](https://www.ncbi.nlm.nih.gov/protein/YP_680426.1?report=fasta) - VP2 Source Sequence: [YP_680427.1](https://www.ncbi.nlm.nih.gov/protein/YP_680427.1?report=fasta) - VP3 Source Sequence: [YP_680428.1](https://www.ncbi.nlm.nih.gov/protein/YP_680428.1?report=fasta) We then replaced the wildtype variable region (`DEEEIRTTNPVATEQYGSVSTNLQRGNR`) in each of these source sequences with the corresponding `variable_region_sequence` for each variant. ## Source Data The sequences in this dataset are sourced from the publication *"Deep diversification of an AAV capsid protein by machine learning"* [(Bryant et al. 2021)](https://www.nature.com/articles/s41587-020-00793-4), which contains 293,574 experimentally characterized variants of a wild-type AAV2 capsid protein sequence. The mutations introduced to create the variants focused on a 28-amino acid segment (residue positions 561-588 of the full VP1 AAV2 capsid protein sequence) which were targeted due to this region being involved in a variety of structural and functional roles. ### Original Dataset Availability GitHub containing the original dataset: [https://github.com/alibashir/aav](https://github.com/alibashir/aav) Source Publication: [Bryant et al. 2021](https://www.nature.com/articles/s41587-020-00793-4) # Citation If you use this dataset in your research, please cite the original publication these variants are sourced from: ```bibtex @article{bryant2021deep, title={"Deep diversification of an AAV capsid protein by machine learning"}, author={Bryant, Drew H and Bashir, Ali and Sinai, Sam and Jain, Nina K and Ogden, Pierce J and Riley, Patrick F and Church, George M and Colwell, Lucy J and Kelsic, Eric D}, journal={Nature Biotechnology}, volume={39}, number={6}, pages={691--696}, year={2021}, publisher={Springer Science and Business Media LLC}, doi={10.1038/s41587-020-00793-4} } ```tags: - 生物学 - 蛋白质序列 - AAV - 回归任务 pretty_name: "AAV2衣壳活力数据集" size_categories: - 100K<n<1M # 共289736个变体 source_datasets: - 自定义数据集 # 源自Bryant等人2021年发表于《自然·生物技术》的研究（https://www.nature.com/articles/s41587-020-00793-4） # 数据集配置（默认将文件`aav2_viability_processed.csv`加载为训练集） configs: - config_name: default data_files: - split: train # 单个文件默认分配至「train」划分 path: aav2_processed.csv # 可选但推荐：数据集结构信息 # 可通过以下命令自动生成：datasets-cli dummy-metadata --repo_id your_username/your_dataset_name dataset_info: features: - name: variable_region_sequence dtype: string - name: source_partition dtype: string - name: viral_selection dtype: float32 # 若使用更高精度则为float64 - name: vp1_sequence dtype: string - name: vp2_sequence dtype: string - name: vp3_sequence dtype: string - name: edit_distance_from_wt dtype: int32 config_name: default splits: - name: train num_bytes: 568803013 # <-- 请填入CSV文件的字节大小 num_examples: 289805 download_size: 568579900 # <-- 请填入待下载文件的总大小（单个CSV文件通常与dataset_size一致） dataset_size: 568803013 # <-- 请填入磁盘上的总占用大小（单个CSV文件通常与num_bytes一致） --- # AAV2衣壳活力数据集 本数据集为源自Bryant等人2021年研究的腺相关病毒2型（Adeno-associated virus 2, AAV2）衣壳活力数据集的预处理版本，包含所有变体的完整VP1、VP2、VP3序列。  ## 数据集说明 本预处理版本共包含289805个变体，各字段说明如下： - `variable_region_sequence`（字符串）：每个AAV2变体可变区的独特氨基酸序列 - `source_partition`（字符串）：元数据字段，用于标注原始研究中生成该变体所使用的来源分组与方法 - `viral_selection`（浮点型）：该变体的病毒选择力，详见[病毒选择力取值说明](#病毒选择力取值说明) - `vp1_sequence`（字符串）：该变体的VP1序列 - `vp2_sequence`（字符串）：该变体的VP2序列 - `vp3_sequence`（字符串）：该变体的VP3序列 - `edit_distance_from_wt`（整型）：该变体可变区序列与野生型序列的编辑距离 ### 预处理流程 1. 移除了57个在可变区中存在提前终止密码子（以`*`标记）的变体 2. 移除了所有序列重复的变体（此类变体存在多个病毒选择力取值），共移除7108个变体 ### 病毒选择力取值说明 原研究中的实验旨在借助机器学习指导，生成远超自然多样性的多样化AAV2衣壳变体并保留其活力。活力通过高通量实验评估：检测各变体序列组装完整衣壳并包装病毒基因组的能力。对于每个变体，其适合度或「病毒选择力」的计算方式为变体在输出「病毒文库」池中的读段数与输入「DNA文库」池中的读段数之比的对数： $$ ext{变体}i ext{的病毒选择力} = log(frac{n_{i,viral}}{n_{i,DNA}})$$   ### VP1、VP2及VP3序列说明 AAV2衣壳为60个亚基组成的多聚体，由VP1、VP2、VP3三种病毒蛋白以5:5:50的比例构成。通过可变剪接和渗漏核糖体扫描，同一mRNA（mRNA9）可根据起始密码子的不同翻译产生VP2和VP3；VP1则由P5启动子启动的独立转录本翻译而来。本数据集已在`vp1_sequence`、`vp2_sequence`、`vp3_sequence`字段中分别提供每个变体的完整VP1、VP2、VP3序列。 为重构每个变体的完整VP1、VP2、VP3序列，我们采用了以下野生型参考序列： - VP1参考序列：[YP_680426.1](https://www.ncbi.nlm.nih.gov/protein/YP_680426.1?report=fasta) - VP2参考序列：[YP_680427.1](https://www.ncbi.nlm.nih.gov/protein/YP_680427.1?report=fasta) - VP3参考序列：[YP_680428.1](https://www.ncbi.nlm.nih.gov/protein/YP_680428.1?report=fasta) 我们将各参考序列中的野生型可变区（`DEEEIRTTNPVATEQYGSVSTNLQRGNR`）替换为对应变体的`variable_region_sequence`。 ## 源数据说明 本数据集的序列源自论文《通过机器学习深度改造AAV衣壳蛋白》（*Deep diversification of an AAV capsid protein by machine learning*，Bryant等人2021年发表），该研究包含293574个经过实验表征的野生型AAV2衣壳蛋白变体。用于生成变体的突变集中于VP1全长序列的561-588位共28个氨基酸区段，该区域因参与多种结构与功能过程而被选为靶向位点。 ### 原始数据集获取渠道 包含原始数据集的GitHub仓库：[https://github.com/alibashir/aav](https://github.com/alibashir/aav) 原始研究论文：[Bryant et al. 2021](https://www.nature.com/articles/s41587-020-00793-4) ## 引用说明 若您在研究中使用本数据集，请引用该变体的原始来源论文： bibtex @article{bryant2021deep, title={"Deep diversification of an AAV capsid protein by machine learning"}, author={Bryant, Drew H and Bashir, Ali and Sinai, Sam and Jain, Nina K and Ogden, Pierce J and Riley, Patrick F and Church, George M and Colwell, Lucy J and Kelsic, Eric D}, journal={Nature Biotechnology}, volume={39}, number={6}, pages={691--696}, year={2021}, publisher={Springer Science and Business Media LLC}, doi={10.1038/s41587-020-00793-4} }