| --- |
| license: mit |
| tags: |
| - biology |
| - plants |
| - gene expression |
| pretty_name: Maize and Arabidopsis gene expression |
| --- |
| # Dataset Card for Maize and Arabidopsis gene expression |
| Plant Gene expression data used for benchmarking sequence to gene expression prediction ML models. |
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| ### Dataset Description |
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| Species included are Maize and Arabidopsis thaliana. Dataset includes gene expression values for leaf and root tissues. |
| Within the `tasks` folder, datasets are broken down by `species-task-tissue`. Genomes in the `genomes` folders include the annotation and the GFF files associated with that specific genome. |
| All tasks are split by 80% train, 10% validation, and 10% test. |
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| ## Dataset Structure |
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| ``` |
| dataset |
| genomes/ |
| Arabidopsis_thaliana/ |
| annotation.fa |
| ath.gff |
| Zea_mays/ |
| annotation.fa |
| ath.gff |
| tasks/ |
| species-task-tissue/ |
| train.tsv |
| validate.tsv |
| test.tsv |
| ``` |
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| - **Curated by:** Taylor Ferebee, Travis Wrightsman, Jingjing Zhai, Aaron Gokaslan, Volodymyr Kuleshov, Edward S. Buckler |
| - **Repository:** [https://github.com/maize-genetics/expression-survey] |
| - **Paper:** PLExBench: A benchmarking suite for predicting gene expression in plants |
| - **License:** MIT |
|
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| ### Dataset Sources |
| | | | | | | | | | | | | | |
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| |sample_name|species|genotype|library_layout|library_selection|reads_location|organ|age|condition|replicate|batch|reference| |
| |SRR505743|Arabidopsis_thaliana|Col-0|single-read|random|sra|root|seedling|controlled|1|1|SRP013631| |
| |SRR505744|Arabidopsis_thaliana|Col-0|single-read|random|sra|leaf|seedling|controlled|1|1|SRP013631| |
| |SRR953400|Arabidopsis_thaliana|Col-0|single-read|random|sra|leaf|seeding|controlled|1|1|PRJNA215448| |
| |SRR1005386|Arabidopsis_thaliana|Col-0|single-read|random|sra|leaf|seedling|controlled|1|1|PRJNA222364| |
| |SRR578947|Arabidopsis_thaliana|Col-0|single-read|random|sra|root|seedling|controlled|1|1|SRP013631| |
| |SRR578948|Arabidopsis_thaliana|Col-0|single-read|random|sra|root|seedling|controlled|1|1|SRP013631| |
| |ERR2096663|Zea_mays|B73|paired-end|polyA|sra|leaf|seedling|controlled|1|1|PRJEB22166| |
| |ERR2096664|Zea_mays|B73|paired-end|polyA|sra|leaf|seedling|controlled|1|1|PRJEB22166| |
| |ERR2096665|Zea_mays|B73|paired-end|polyA|sra|leaf|seedling|controlled|1|1|PRJEB22166| |
| |ERR2096666|Zea_mays|B73|paired-end|polyA|sra|leaf|seedling|controlled|1|1|PRJEB22166| |
| |ERR2096667|Zea_mays|B73|paired-end|polyA|sra|leaf|seedling|controlled|1|1|PRJEB22166| |
| |ERR3773807|Zea_mays|B73|paired-end|polyA|sra|root|seedling|controlled|1|1|PRJEB35943| |
| |ERR3773808|Zea_mays|B73|paired-end|polyA|sra|root|seedling|controlled|1|1|PRJEB35943| |
| |ERR986091|Zea_mays|B73|paired-end|random|sra|root|seedling|controlled|1|1|PRJEB10406| |
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| ### Curation Rationale |
| To choose experiments for leaf and root tissues, we focused on datasets that have been used in a recent study and can be found in |
| multiple databases. |
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| #### Data Collection and Processing |
| In the max gene expression datasets, for each gene, we take the maximum transcript per million TPM value over experiments. Similarly, for the |
| absolute expression datasets, we take the mean TPM value over experiments. Finally, for the on-off ex- |
| pression, we assign 1 to a gene if it has a TPM value in one of the tissues. To create train-test-validation |
| splits, we use orthogroup guided splitting as introduced by Washburn et al. 2019. Then, we split the training test sets so |
| that we train on 80% of the orthogroups and test on 10%. Note that for each of the task-based datasets, we |
| keep the same train-test-validate split. |
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| **BibTeX:** |
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| ## Dataset Card Authors |
| Taylor Ferebee (tf259@cornell.edu) |
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| ## Dataset Card Contact |
| Taylor Ferebee (tf259@cornell.edu), Cinta Romay, Edward S. Buckler |
