updated bedboss docs

docs/bedboss/how-to-run-in-docker.md

@@ -0,0 +1,42 @@
+# Running Bedboss in Docker
+
+To run bedboss in docker, go through the following steps:
+
+1. Clone the bedboss repository:
+
+    ```bash
+    git clone [email protected]:databio/bedboss.git
+    ```
+
+2. Go to the bedboss directory.
+
+3. Build the docker image:
+
+    ```bash
+    docker build -t my_bedboss .
+    ```
+
+4. source the environment variables:
+
+    ```bash
+    source production/production.env
+    ```
+
+5. Run the docker container with setting limit of the files that have to be processed:
+
+    ```bash
+    docker run --rm -it \
+        --env POSTGRES_DB=$POSTGRES_DB \
+        --env POSTGRES_HOST=$POSTGRES_HOST \
+        --env POSTGRES_USER=$POSTGRES_USER \
+        --env POSTGRES_PASSWORD=$POSTGRES_PASSWORD \
+        --env QDRANT_API_KEY=$QDRANT_API_KEY \
+        --env QDRANT_API_HOST=$QDRANT_API_HOST \
+        --env AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
+        --env AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
+        --env AWS_ENDPOINT_URL=$AWS_ENDPOINT_URL \
+        --env UPLOAD_LIMIT=1 \
+        -t my_bedboss
+    ```
+
+If everything is set up correctly, you should see the bedboss prompt.

docs/bedboss/tutorials/python/bedclassifier_tutorial.md

@@ -1,4 +1,15 @@
 # BED classifier tutorial
 
+BED classifier is a utility that allows you to classify BED files based on their columns.
+The function output is a tuple of two strings: `bed_format` and `bed_type`. e.g. `('narrowpeak', 'bed3+5')`.
 
-### 🚧 Tutorial in progress! Stay tuned for updates. We're working hard to bring you valuable content soon!
+Example usage of the BED classifier:
+
+```python
+from bedboss.bedclassifier.bedclassifier import get_bed_type
+
+f = get_bed_type("path/to/bedfile.bed")
+print(f)
+
+## > ('narrowpeak', 'bed3+5')
+```

docs/bedboss/tutorials/python/ref_genome_tutorial.md

@@ -1,3 +1,62 @@
 # Reference genome validator
 
-### 🚧 Tutorial in progress! Stay tuned for updates. We're working hard to bring you valuable content soon!
+Reference genome validator is a set of functions that allow to validate the reference genome of the bed files.
+Functions include different statistical analysis and comparison of the reference genome of the bed files that produce a compatibility rating.
+
+To run the reference genome validator, you need to have the input bed file and the chrom sizes files.
+
+Examples usage of the reference genome validator:
+
+### Example 1
+Run validator with default parameters, with include default chrom sizes files.
+
+```python
+
+from bedboss.refgenome_validator.main import ReferenceValidator
+
+validator_obj = ReferenceValidator()
+
+results = validator_obj.determine_compatibility("path/to/bedfile.bed")
+
+print(results)
+# >>{'ensembl_hg38.chrom.sizes': CompatibilityStats(chrom_name_stats=ChromNameStats(xs=0.0, q_and_m=0.0, q_and_not_m=86.0, not_q_and_m=68.0, jaccard_index=0.0, jaccard_index_binary=0.0, passed_chrom_names=False), chrom_length_stats=ChromLengthStats(oobr=None, beyond_range=False, num_of_chrom_beyond=0, percentage_bed_chrom_beyond=0.0, percentage_genome_chrom_beyond=0.0), chrom_sequence_fit_stats=SequenceFitStats(sequence_fit=None), igd_stats=None, compatibility=RatingModel(assigned_points=10, tier_ranking=4)),
+# >> 'ncbi_hg38.chrom.sizes': CompatibilityStats(chrom_name_stats=ChromNameStats(xs=0.0, q_and_m=0.0, q_and_not_m=86.0, not_q_and_m=705.0, jaccard_index=0.0, jaccard_index_binary=0.0, passed_chrom_names=False), chrom_length_stats=ChromLengthStats(oobr=None, beyond_range=False, num_of_chrom_beyond=0, percentage_bed_chrom_beyond=0.0, percentage_genome_chrom_beyond=0.0), chrom_sequence_fit_stats=SequenceFitStats(sequence_fit=None), igd_stats=None, compatibility=RatingModel(assigned_points=10, tier_ranking=4)),
+
+```
+
+### Example 2
+Run validator with custom reference genome chrom sizes files.
+
+```python
+
+from bedboss.refgenome_validator.main import ReferenceValidator
+
+
+ref_gen_list = [GenomeModel(
+    genome_alias="ensembl_hg38",
+    chrom_sizes_path="path/to/ensembl_hg38.chrom.sizes"
+)
+    ]
+validator_obj = ReferenceValidator(
+    genome_models=ref_gen_list,
+)
+
+results = validator_obj.determine_compatibility("path/to/bedfile.bed")
+
+print(results)
+# >>{'ensembl_hg38': CompatibilityStats(chrom_name_stats=ChromNameStats(xs=0.0, q_and_m=0.0, q_and_not_m=86.0, not_q_and_m=68.0, jaccard_index=0.0, jaccard_index_binary=0.0, passed_chrom_names=False), chrom_length_stats=ChromLengthStats(oobr=None, beyond_range=False, num_of_chrom_beyond=0, percentage_bed_chrom_beyond=0.0, percentage_genome_chrom_beyond=0.0), chrom_sequence_fit_stats=SequenceFitStats(sequence_fit=None), igd_stats=None, compatibility=RatingModel(assigned_points=10, tier_ranking=4))}
+```
+
+### Example 3
+Run genome predictor on a bed file with default reference genomes chrom sizes files.
+
+```python
+from bedboss.refgenome_validator.main import ReferenceValidator
+
+validator_obj = ReferenceValidator()
+
+results = validator_obj.predict("path/to/bedfile.bed")
+
+print(results)
+
+```

docs/bedboss/usage.md

@@ -1,4 +1,4 @@
-# Usage reference
+# Command line interface reference
 
 BEDboss is command-line tool-manager and a set of tools for working with BED files and BEDbase. Main components of BEDboss are: </br>
 1) Pipeline for processing BED files: bedmaker, bedqc, and bedstats.</br>

mkdocs.yml

@@ -81,11 +81,11 @@ nav:
         - Command line interface: bedboss/usage.md
     - How to guides:
       - Create BEDbase database: bedboss/how-to-create-database.md
+      - Run BEDboss in Docker: bedboss/how-to-run-in-docker.md
       - Create config file: bedbase/how-to-configure.md
       - Install dependencies: bedboss/how-to-install-requirements.md
     - Reference:
       - How to cite: citations.md
-      - Usage: bedboss/usage.md
       - Changelog: bedboss/changelog.md
   - Geniml:
     - Geniml: geniml/README.md