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README.md

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----
-license: apache-2.0
----
+# Datasets
+
+Each folder contains either one benchmark or a set of benchmarks. See [docs/](../docs/) for code used to create these benchmarks.
+
+### Naming conventions
+
+* *dummy_...*: small datasets, used for testing purposes
+* *demo_...*: middle size datasets, not necesarily biologically relevant or fully reproducible, used in demos
+
+### Versioning
+
+We recommend to check the version number when working with the dataset (i.e. not using default `None`). The version should be set to 0 when the dataset is proposed, after inicial curration it should be changed to 1 and then increased after every modification.
+
+### Data format
+
+Each benchmark should contain `metadata.yaml` file with its main folder with the specification in YAML format, namely
+
+   * **the version** of the benchmark (0 = in development)
+
+   * **the classes** of genomic sequences, for each class we further need to specify
+
+       - *url* with the reference 
+       - *type* of the reference (currently, only fa.gz implemented)
+       - *extra_processing*, a parameter helping to overcome some know issues with identifiers matching
+
+The main folder should also contain two folders, `train` and `test`. Both those folders should contain gzipped CSV files, one for each class (named `class_name.csv.gz`).
+
+The format of gzipped CSV files closely resemble BED format, the column names must be the following:
+
+* **id**: id of a sequence
+* **region**: chromosome/transcript/... to be matched with the reference
+* **start**, **end**: genomic interval specification (0-based, i.e. same as in Python)
+* **strand**: either '+' or '-'
+
+
+### To contribute a new datasets
+
+Create a new branch. Add the new subfolders to `datasets` and `docs`. The subfolder of `docs` should contain a description of the dataset in `README.md`. If the dataset comes with the paper, link the paper. If the dataset is not taken from the paper, make sure you have described and understand the biological process behind it.
+
+If you have access to `cloud_cache` folder on GDrive, upload your file there and update `CLOUD_CACHE` in [cloud_caching.py](https://github.com/ML-Bioinfo-CEITEC/genomic_benchmarks/blob/main/src/genomic_benchmarks/loc2seq/cloud_caching.py).
+
+### To review a new dataset
+
+Make sure you can run and reproduce the code. Check you can download the actual sequences and/or create a data loader. Do you understand what is behind these data? (either from the paper or the description) Ask for clarification if needed.

demo_coding_vs_intergenomic_seqs/metadata.yaml

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+classes:
+  coding_seqs:
+    extra_processing: ENSEMBL_HUMAN_TRANSCRIPTOME
+    type: fa.gz
+    url: http://ftp.ensembl.org/pub/release-97/fasta/homo_sapiens/cdna/Homo_sapiens.GRCh38.cdna.all.fa.gz
+  intergenomic_seqs:
+    extra_processing: ENSEMBL_HUMAN_GENOME
+    type: fa.gz
+    url: http://ftp.ensembl.org/pub/release-97/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.toplevel.fa.gz
+version: 0

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demo_human_or_worm/metadata.yaml

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+    type: fa.gz
+    url: http://ftp.ensembl.org/pub/release-97/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.toplevel.fa.gz
+  worm:
+    type: fa.gz
+    url: http://ftp.ensembl.org/pub/release-104/fasta/caenorhabditis_elegans/dna/Caenorhabditis_elegans.WBcel235.dna.toplevel.fa.gz
+version: 0

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drosophila_enhancers_stark/metadata.yaml

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+    extra_processing: ENSEMBL_DROSOPHILA_GENOME
+    type: fa.gz
+    url: http://ftp.ensembl.org/pub/release-100/fasta/drosophila_melanogaster/dna/Drosophila_melanogaster.BDGP6.28.dna.toplevel.fa.gz
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+    type: fa.gz
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