Statistics API

Namespace: fq::statistic

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StatisticCalculatorInterface

Abstract interface for statistical calculation tasks, create instances via factory function.

Factory Creation

fq::statistic::StatisticOptions options;
options.inputFastqPath = "input.fastq.gz";
options.outputStatPath = "output.stat.txt";
options.threadCount = 4;

auto calculator = fq::statistic::createStatisticCalculator(options);
calculator->run();

Interface Definition

class StatisticCalculatorInterface {
public:
    virtual ~StatisticCalculatorInterface() = default;
    virtual void run() = 0;
};

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StatisticOptions

Statistics task configuration.

Field	Type	Description
inputFastqPath	std::string	Input FASTQ file path
outputStatPath	std::string	Output statistics file path
threadCount	size_t	Number of threads
batchSize	size_t	Batch processing size

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StatisticInterface

Low-level abstract interface for statistical calculation, supports custom statistics logic extension.

class StatisticInterface {
public:
    using Batch = fq::io::FastqBatch;
    using Result = FqStatisticResult;

    virtual ~StatisticInterface() = default;
    virtual auto calculateStats(const Batch& batch) -> Result = 0;
};

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FqStatisticResult

Statistics result data structure.

Field	Type	Description
readCount	uint64_t	Total read count
totalBases	uint64_t	Total base count
maxReadLength	uint32_t	Maximum read length
posQualityDist	vector<vector<uint64_t>>	Position quality distribution
posBaseDist	vector<vector<uint64_t>>	Position base distribution

Supports operator+= to merge statistics results from multiple batches.

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Parallel Processing Architecture

Statistical analysis uses TBB parallel pipeline:

Input file → FastqReader → [Source] → [Processing] → [Aggregation] → Output file
                          Serial read  Parallel calc    Serial merge

1. Source (serial_in_order): Serially read FastqBatch
2. Processing (parallel): Parallelly calculate statistics for each batch
3. Aggregation (serial_in_order): Merge all statistics results

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Output Format

Statistics results support JSON and text format output, containing:

• Total reads, valid reads
• Sequence length distribution (min/max/average)
• Base composition (A/T/C/G/N ratio)
• GC content
• Position quality distribution (Q20/Q30 percentage)