# DNAAnalyzer Class

---

## Overview
The `DNAAnalyzer` class provides tools for analyzing DNA sequences, detecting genetic markers, and predicting traits based on genetic mutations. It supports various analyses such as GC content, CpG islands, tandem repeats, promoter regions, codon bias, gene clusters, nucleotide distribution, palindromic sequences, and GC skew. Additionally, it can detect specific genetic markers for conditions like hemophilia and color blindness, and it allows for the addition of custom genetic markers.

---

## Class Definition

```python
class DNAAnalyzer:
    def __init__(self, dna):
        """
        Initialize a new DNAAnalyzer object.
        :param dna: DNA object to analyze
        """
        ...
```

---

## Attributes

| Attribute | Type | Description |
|-----------|------|-------------|
| `dna` | `DNA` | The DNA object to analyze. |
| `hemophilia_markers` | `List[GeneticMarker]` | List of genetic markers for hemophilia. |
| `color_blindness_markers` | `List[GeneticMarker]` | List of genetic markers for color blindness. |
| `custom_markers` | `List[Tuple[GeneticMarker, str]]` | List of custom genetic markers and their associated traits. |

---

## Enums

### MutationType
```python
class MutationType(Enum):
    MISSENSE = 1
    NONSENSE = 2
    FRAMESHIFT = 3
    SPLICE_SITE = 4
    INVERSION = 5
    DELETION = 6
    INSERTION = 7
```
- Represents the types of genetic mutations.

---

## Classes

### GeneticMarker
```python
class GeneticMarker:
    def __init__(self, name, sequence, mutation_type, impact):
        """
        Initialize a new GeneticMarker object.
        :param name: Name of the genetic marker
        :param sequence: DNA sequence of the marker
        :param mutation_type: Type of mutation
        :param impact: Impact on trait expression (0.0 to 1.0)
        """
        ...
```
- Represents a genetic marker with a name, sequence, mutation type, and impact on trait expression.

---

## Methods

### Initialization
- **`__init__(self, dna)`**
  Initializes a new `DNAAnalyzer` instance with the specified DNA object.

- **`_initialize_hemophilia_markers(self) -> List[GeneticMarker]`**
  Initializes and returns a list of genetic markers for hemophilia.

- **`_initialize_color_blindness_markers(self) -> List[GeneticMarker]`**
  Initializes and returns a list of genetic markers for color blindness.

---

### DNA Analysis
- **`analyze_gc_content(self) -> float`**
  Analyzes and returns the GC content of the DNA sequence.

- **`find_cpg_islands(self, window_size=200, gc_threshold=55, obs_exp_ratio=0.65) -> List[Tuple[int, int]]`**
  Finds and returns CpG islands in the DNA sequence.

- **`find_tandem_repeats(self, min_length=2, max_length=6) -> List[Tuple[str, int, int]]`**
  Finds and returns tandem repeats in the DNA sequence.

- **`find_promoter_regions(self, tata_box='TATAAA', upstream_range=(-35, -25)) -> List[Tuple[int, int]]`**
  Finds and returns potential promoter regions based on TATA box presence.

- **`analyze_codon_bias(self) -> Dict[str, float]`**
  Analyzes and returns codon usage bias in the DNA sequence.

- **`find_gene_clusters(self, max_distance=1000) -> List[List[Gene]]`**
  Finds and returns clusters of genes that are close to each other.

- **`analyze_nucleotide_distribution(self, window_size=100) -> List[Dict[str, Union[int, float]]]`**
  Analyzes and returns the distribution of nucleotides along the DNA sequence.

- **`find_palindromic_sequences(self, min_length=4, max_length=10) -> List[Tuple[str, int, int]]`**
  Finds and returns palindromic sequences in the DNA.

- **`analyze_gc_skew(self, window_size=1000) -> List[Tuple[int, int, float]]`**
  Analyzes and returns GC skew along the DNA sequence.

- **`predict_open_reading_frames(self, min_length=100) -> List[Tuple[int, int]]`**
  Predicts and returns open reading frames (ORFs) in the DNA sequence.

---

### Genetic Marker Detection
- **`_detect_markers(self, sequence: str, markers: List[GeneticMarker]) -> List[GeneticMarker]`**
  Detects genetic markers in a DNA sequence.

- **`_partial_match(self, sequence: str, marker_sequence: str, threshold: float) -> bool`**
  Checks for a partial match between a DNA sequence and a marker sequence.

- **`detect_hemophilia_markers(self) -> List[GeneticMarker]`**
  Detects and returns hemophilia markers in the DNA sequence.

- **`detect_color_blindness_markers(self) -> List[GeneticMarker]`**
  Detects and returns color blindness markers in the DNA sequence.

- **`add_custom_marker(self, name: str, sequence: str, mutation_type: MutationType, impact: float, trait: str)`**
  Adds a custom genetic marker.

- **`detect_custom_markers(self) -> List[Tuple[GeneticMarker, str]]`**
  Detects and returns custom markers in the DNA sequence.

---

### Trait Analysis
- **`analyze_trait_probability(self, detected_markers: List[GeneticMarker]) -> float`**
  Analyzes and returns the probability of a trait based on detected genetic markers.

- **`detect_traits(self) -> Tuple[Dict[str, float], Dict[str, List[GeneticMarker]]]`**
  Detects and returns traits and their probabilities based on detected genetic markers.

- **`simulate_environmental_factors(self) -> Dict[str, float]`**
  Simulates and returns environmental factors that might influence trait expression.

- **`generate_trait_report(self) -> str`**
  Generates and returns a report of trait analysis.

- **`analyze_gene_interactions(self) -> List[str]`**
  Analyzes and returns potential interactions between detected genetic markers.

- **`predict_severity(self, probability: float) -> str`**
  Predicts and returns the potential severity of a trait based on genetic probability.

- **`generate_comprehensive_report(self) -> str`**
  Generates and returns a comprehensive genetic analysis report.

---

## Example Usage

```python
# Initialize a DNA object
dna = DNA(sequence="ATGCGATCGATCGATCGATCGATCGATCGATCG")

# Initialize the DNAAnalyzer
analyzer = DNAAnalyzer(dna)

# Analyze GC content
gc_content = analyzer.analyze_gc_content()
print(f"GC Content: {gc_content:.2f}%")

# Find CpG islands
cpg_islands = analyzer.find_cpg_islands()
print(f"CpG Islands: {cpg_islands}")

# Detect hemophilia markers
hemophilia_markers = analyzer.detect_hemophilia_markers()
print(f"Hemophilia Markers: {[marker.name for marker in hemophilia_markers]}")

# Detect color blindness markers
color_blindness_markers = analyzer.detect_color_blindness_markers()
print(f"Color Blindness Markers: {[marker.name for marker in color_blindness_markers]}")

# Add a custom marker
analyzer.add_custom_marker("CustomMarker1", "ATGCGATCG", MutationType.MISSENSE, 0.6, "CustomTrait")

# Detect custom markers
custom_markers = analyzer.detect_custom_markers()
print(f"Custom Markers: {[marker[0].name for marker in custom_markers]}")

# Detect traits
trait_probabilities, detected_traits = analyzer.detect_traits()
print(f"Trait Probabilities: {trait_probabilities}")

# Generate a comprehensive report
report = analyzer.generate_comprehensive_report()
print(report)
```

---

## Dependencies
- **`re`**: For regular expression operations.
- **`collections.Counter`**: For counting elements in sequences.
- **`random`**: For simulating random environmental factors.
- **`enum.Enum`**: For defining the `MutationType` enum.
- **`DNA`**: Class representing DNA sequences.

---

## Error Handling
- The class includes checks for valid sequences and handles potential errors during analysis.

---

## Notes
- The `DNAAnalyzer` class is designed for advanced genetic analysis and trait prediction.
- It supports the detection of specific genetic markers for conditions like hemophilia and color blindness.
- The class allows for the addition of custom genetic markers and traits.
- The `generate_comprehensive_report` method provides a detailed analysis of genetic traits, including potential interactions and severity predictions.
