// Configure the alignment parameters
let aln_params = AlignmentParametersBuilder::new()
    .alignment_mode(AlignmentMode::Global)
    .gap_affine_penalties(0, 4, 6, 2)
    .verbosity(Verbosity::None)
    .build();

// Create a new empty POA graph
let mut graph = Graph::new(&aln_params);

let test_seq: Vec<&[u8]> = vec![
    b"ACGTGTACAGTTGAC",
    b"AGGTACACGTTAC",
    b"AGTGTCACGTTGAC",
    b"ACGTGTACATTGAC",
];

// Align and add each sequence to the graph
for (i, seq) in test_seq.iter().enumerate() {
    let weights = vec![1; seq.len()];
    let result = graph
        .align_and_add_sequence(&aln_params, seq, &weights, format!("seq{}", i + 1).as_bytes())
        .unwrap();

    eprintln!("Sequence {}: score = {}", i + 1, result.get_best_score());
}

// Compute the row-column MSA output
graph.generate_rc_msa();
let msa = graph.get_msa();
assert_eq!(msa.len(), 4);

let truth = [
    b"ACGTGTACAGTTGAC",
    b"A--GGTACACGTTAC",
    b"A-GTGTCACGTTGAC",
    b"ACGTGTACA-TTGAC",
];

for (i, seq) in msa.sequences().iter().enumerate() {
    // The sequence in the MSA object is coded, so we use `reverse_seq` to convert it to ASCII.
    let ascii = aln_params.reverse_seq(seq);
    assert_eq!(&ascii, truth[i]);
}

// Generate consensus
graph.generate_consensus(ConsensusAlgorithm::HeaviestBundle);

let consensus = graph.get_consensus().unwrap();
let ascii = aln_params.reverse_seq(consensus.sequences().iter().next().unwrap());

eprintln!("Consensus: {}", std::str::from_utf8(ascii).unwrap());