Hw18

README.md

@@ -1 +1,83 @@
-# misc_module
+# misc_module
+
+This module contains assignments for the BI course on python. The scripts include tasks on OOP, API and various functions useful for basic bioinformatics.
+The following functions can be found in `bio_files_processor.py`:
+
+```
+convert_multiline_fasta_to_oneline
+```
+
+Example:
+
+`
+convert_multiline_fasta_to_oneline(input_fasta='example_multiline_fasta.fasta')
+`
+
+Input file:
+
+![before](https://github.com/sme229/misc_module/assets/104040609/65e68a7a-a47c-4335-8d10-a88387fa3bdd)
+
+After conversion to a single line:
+
+![after](https://github.com/sme229/misc_module/assets/104040609/c85e4283-295e-4689-a156-5c464cec2164)
+
+```
+OpenFasta
+```
+
+This is a context manager that works with fasta files.
+
+- It returns records as `FastaRecord` class objects
+- Includes `read_record` and `read_records` methods
+
+Input and output example:
+
+```fasta
+>GTD326487.1 Species anonymous 24 chromosome
+ATCGACTACGACTAGCATCACGATCACGATACG
+ATGCATCAGTAGCACTAGATCA
+```
+
+```python
+id = 'GTD326487.1'
+description = 'Species anonymous 24 chromosome'
+sequence = 'ATCGACTACGACTAGCATCACGATCACGATACGATGCATCAGTAGCACTAGATCA'
+```
+
+In biopython_fastq_filter.py the following functions are located:
+
+```
+fastq_filter
+```
+
+This function uses BioPython and filters fastq sequences by GC content, sequence length and quality score. 
+
+
+```
+BiologicalSequence
+```
+
+This is an abstract class that includes:
+
+Class NucleicAcidSequence which has `complement` and `gc_content` methods. It's a parent class to DNASequence and RNASequence classes.
+
+Class AminoAcidSequence has `amino_acid_frequency` method.
+
+
+```
+telegram_logger
+```
+
+This function send a message from a telegram bot about the status of some process:
+
+![Untitled](https://github.com/sme229/misc_module/assets/104040609/141f1cd1-1430-48c7-b8ab-dda41db214ea)
+
+
+```
+run_genscan
+```
+
+This is a python API for this web tool http://hollywood.mit.edu/GENSCAN.html
+
+
+In `custom_random_forest.py` there is a `RandomForestClassifierCustom` class that works with a custom number of threads which makes it fast.