contextmap

contextmap maps short sequencing reads from RNA sequencing (RNA-seq) experiments to reference genomes to identify exon-spanning alignments, junctions, and insertions and deletions (indels) for accurate downstream analysis.

Key Features:

• Plug-in Architecture: Integrates with various short read alignment programs via a plug-in structure to incorporate alternative alignment algorithms.
• Context-Based Alignment: Uses a context-based approach to determine the optimal alignment per read, enabling accurate identification of insertions and deletions (indels) and mapping of reads that span multiple exons and indels.
• Parallel Mapping Capability: Supports parallel mapping against several reference genomes simultaneously to facilitate analyses across multiple species or references.

Scientific Applications:

• RNA-seq Read Mapping: Provides precise placement of short reads for RNA sequencing analyses.
• Gene Expression Quantification: Supplies accurate alignments required for quantifying gene and transcript expression levels.
• Transcriptome Assembly: Delivers exon-spanning and junction-aware mappings useful for transcript reconstruction.
• Variant and Indel Detection: Enables detection and placement of insertions and deletions (indels) from RNA-seq data.
• Splice Junction Prediction: Predicts exon–exon junctions from mapped reads for splice variant analysis.

Methodology:

Employs a context-based alignment strategy to select optimal alignments per read, supports integration with short read alignment programs via a plug-in architecture and parallel mapping against multiple reference genomes, and was evaluated using simulated data and real datasets from the RGASP study with reported recall, precision, junction and indel prediction performance and runtime comparisons.