Conditional statements
Conditional statements are a fundamental aspect of programming, allowing you to control the flow of your code based on certain conditions. In Python, conditional statements are implemented using if, elif (short for “else if”), and else statements. Understanding how to use these statements is crucial for writing dynamic and responsive programs, particularly in bioinformatics where data analysis often involves complex decision-making processes.
Basic Structure of Conditional Statements:
1. if Statement:
The ‘if’ statement is used to execute a block of code if a specified condition is true.
sequence_quality = 38
if sequence_quality >= 30:
print("Sequence quality is high.")
2. if-else Statement:
The ‘if-else’ statement allows you to execute one block of code if the condition is true and another block if it is false.
gene_expression = 0.3
if gene_expression > 0.8:
print("High gene expression.")
else:
print("Low gene expression.")
3. if-elif-else Statement:
The ‘if-elif-else’ statement is used when there are multiple conditions to check. It allows you to specify multiple conditions and execute the block of code associated with the first true condition.
dna_sequence = "ATGCTAGCTGACTAGC"
if "ATG" in dna_sequence:
print("Start codon present.")
elif "TAA" in dna_sequence or "TAG" in dna_sequence or "TGA" in dna_sequence:
print("Stop codon present.")
else:
print("No recognizable codons found.")
Conditional statements are essential tools for incorporating decision-making logic into your Python programs. In bioinformatics, where data analysis often involves complex conditions and thresholds, mastering conditional statements allows you to write more flexible and adaptive code. These statements empower you to create programs that respond dynamically to various scenarios, making them invaluable in the next-generation biologist’s toolkit.
Some more examples
cell_marker_expression = {'CD3': 0.8, 'CD19': 0.1, 'CD56': 0.5}
if cell_marker_expression['CD3'] > 0.5:
print("Likely T-cell.")
elif cell_marker_expression['CD19'] > 0.5:
print("Likely B-cell.")
elif cell_marker_expression['CD56'] > 0.5:
print("Likely NK cell.")
else:
print("Cell type unclear.")
gene_variant = 'KRAS_G12C'
if gene_variant == 'EGFR_Exon19Deletion':
print("Highly responsive to EGFR inhibitors.")
elif gene_variant.startswith('KRAS'):
print("Consider alternative treatment strategies for KRAS mutations.")
else:
print("Drug response prediction uncertain for this gene variant.")
Common Pitfalls & Troubleshooting Checklist
- Java Heap Exhaustion (GATK / Picard): If processes terminate with
java.lang.OutOfMemoryError, set your environment variable explicitly:export _JAVA_OPTIONS="-Xmx16g -Djava.io.tmpdir=/tmp". - Index Timestamp Mismatch: If tools complain that a BAM index is missing or out of date, regenerate with
samtools index -@ 4 sample.bam. - Conda Channel Conflicts: Avoid ABI incompatibilities between bioconda and conda-forge by setting strict priority:
conda config --set channel_priority strict. - Chromosome Naming Contamination: Always verify whether reference FASTA headers use
chr1or1; divergent naming causes silent alignment drops.