Update Dataset Card according to basic template

README.md

@@ -1,3 +1,96 @@
 ---
 license: mit
+tags:
+- biology
+- plants
+- gene expression
+pretty_name: Maize and Arabidopsis gene expression
 ---
+# Dataset Card for Dataset Name
+Plant Gene expression data used for benchmarking sequence to gene expression prediction ML models. 
+
+## Dataset Details
+
+### Dataset Description
+
+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`, so the structure looks like:
+```
+    species-task-tissue/
+      train.tsv
+      validate.tsv
+      test.tsv
+```
+All tasks are split by 80% train, 10% validation, and 10% test. 
+
+
+- **Curated by:** Taylor Ferebee, Travis Wrightsman, Jingjing Zhai, Aaron Gokaslan, Volodymyr Kuleshov, Edward S. Buckler
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** MIT
+
+### Dataset Sources 
+| | | | | | | | | | | | |
+|-|-|-|-|-|-|-|-|-|-|-|-|
+|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|
+
+
+
+- **Repository:** [https://github.com/maize-genetics/expression-survey]
+- **Paper:** PLExBench: A benchmarking suite for predicting gene expression in plants
+
+
+## Dataset Structure
+
+```
+dataset
+  genomes/
+    Arabidopsis_thaliana/
+      annotation.fa
+      ath.gff
+    Zea_mays/
+      annotation.fa
+      ath.gff
+  tasks/
+    species-task-tissue/
+      train.tsv
+      validate.tsv
+      test.tsv
+```
+
+
+### 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.
+
+#### 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. 
+
+**BibTeX:**
+
+
+## Dataset Card Authors
+Taylor Ferebee (tf259@cornell.edu)
+
+## Dataset Card Contact
+Taylor Ferebee (tf259@cornell.edu)