CView

CView provides dynamic network-based visualization and quantitative summaries of sequence alignments to reveal regional diversity and relationships among sequences that vary by location, date, and subtype.

Key Features:

• Dynamic network visualization: Summarizes diversity across alignment regions using a network of nodes and edges.
• Windowed clustering: Represents clusters of sequence fragments derived from consecutive windows along the alignment.
• Shared-sequence edges: Connects nodes when they share sequence identifications, linking different regions of the same sequences.
• Path tracing: Traces paths through the network from a selected node to observe how sequences passing through that node relate to other regions.
• Variant summarization export: Exports summaries of sequence variants derived from the alignment.
• Per-site residue frequency export: Computes and exports per-site nucleotide or amino acid residue frequencies.
• K-mer frequency export: Computes and exports k-mer frequency counts from the alignment.
• Consensus sequence generation: Generates consensus sequences from full alignments or selected alignment regions.
• Alignment dissection export: Exports sub-alignments or dissected regions of the full alignment.
• Clustering export: Exports clustering results of sequence fragments or alignment regions.

Scientific Applications:

• Regional diversity mapping: Reveals and summarizes diversity across different regions of sequence alignments for datasets stratified by location, date, or subtype.
• Sequence relationship tracing: Identifies how individual sequences traverse diverse alignment regions via network paths.
• Variant and frequency analysis: Produces variant summaries and per-site and k-mer frequency spectra for population-level analyses.
• Consensus generation: Produces consensus sequences for representative or partitioned sets of sequences.
• Alignment dissection and clustering: Provides dissected alignment regions and clustered fragments for downstream analyses.

Methodology:

Constructs a network by clustering sequence fragments from consecutive alignment windows into nodes, connects nodes by edges when they share sequence identifiers, enables path tracing through the network, and computes per-site residue and k-mer frequencies, variant summaries, consensus sequences, alignment dissections, and clustering results.