Update README.md

README.md

@@ -1,3 +1,43 @@
----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+tags:
+  - biology
+  - rna
+  - genomics
+configs:
+  - config_name: utr3
+    data_files:
+    - split: train
+      path: utr-variants-bohn-utr3.parquet
+  - config_name: utr5
+    data_files:
+    - split: train
+      path: utr-variants-bohn-utr5.parquet
+---
+
+# Overview
+
+This utr variant effect prediction task measures the pathogenicity of single nucleotide polymorpism (SNPs) and indels (insertion-deletions) in 3' and 5' UTRs. This dataset is a reprocessing of the DeepGenomics dataset (https://github.com/deepgenomics/UTR_variants_DL_manuscript), see the original paper for data generation process. We provide the mRNA transcript sequence context for the variant and wildtype sequences using the specified transcript id from RefSeq v109.
+
+This dataset is redistributed as part of mRNABench: https://github.com/morrislab/mRNABench
+
+# Data Format
+
+Description of data columns:
+- `target`: Whether the specified sequence contains a pathogenic mutation.
+- `cds`: Binary track which reports position of first nucleotide in each codon in CDS.
+- `splice`: Binary track which reports position of the 3' end of each exon, indicating splice sites.
+- `description`: Description of the sequence, either in the format `chr{chr}:{position} {ref_base}:{alt_base}` (with an optional description of the impact of the variant) or with the word wild-type for the unmodified sequence.
+
+Note: The position of the variant is 1-indexed (ClinVar notation) and refers to the position of the variant on the positive strand.
+
+# Data Source
+This dataset is generated using a dataset collected by a team at DeepGenomics and is under a CC by 4.0 license.
+
+Please attribute:
+
+Original paper: https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2023.1257550/full  
+Original paper GitHub: https://github.com/deepgenomics/UTR_variants_DL_manuscript  
+3' UTR Variant data source: https://github.com/deepgenomics/UTR_variants_DL_manuscript/blob/main/data/utr3_plp_benchmark.tsv  
+5' UTR Variant data source: https://github.com/deepgenomics/UTR_variants_DL_manuscript/blob/main/data/utr5_plp_benchmark.tsv  
+Citation: Bohn E, Lau TTY, Wagih O, Masud T and Merico D (2023) A curated census of pathogenic and likely pathogenic UTR variants and evaluation of deep learning models for variant effect prediction. Front. Mol. Biosci. 10:1257550. doi: 10.3389/fmolb.2023.1257550