SQANTI3

SQANTI3 performs quality control, curation, and structural and functional annotation of long-read transcript models from third-generation sequencing technologies such as Pacific Biosciences (PacBio) to support accurate isoform-level analyses.

Key Features:

• Integration with FIT pipeline: Functions as the first module of the Functional IsoTranscriptomics (FIT) pipeline to enable isoform-level analyses.
• Quality control and curation: Calculates quality descriptors for transcript models, splice junctions, and transcript ends to detect artifacts and replace erroneous sequences.
• Integrated functional annotation: Provides functional annotation of transcripts to support downstream functional iso-transcriptomics analyses.
• Comprehensive descriptor set: Implements 47 unique descriptors to evaluate transcript and preprocessing-pipeline quality and to inform filtering strategies that remove technical artifacts from sequencing approaches such as Pacific Biosciences (PacBio).
• Impact on quantification: Identifies and curates novel transcripts, including novel combinations of splice sites that produce new open reading frames (ORFs), thereby affecting short-read-based transcript quantification estimates.
• Functional insights and proteogenomics relevance: Characterizes enrichment of novel transcripts in metabolic and neural-specific functions and highlights challenges for proteogenomics detection of alternative isoforms in public proteomics databases.

Scientific Applications:

• Isoform discovery and validation: Enables discovery and validation of novel isoforms from long-read sequencing by identifying artifacts and curating transcript structures.
• Improved transcript quantification: Enhances the accuracy of short-read-based transcript quantification by specifying curated transcript models and filtering technical artifacts.
• Functional iso-transcriptomics analyses: Supports downstream functional analyses within the FIT pipeline through integrated functional annotation of isoforms.
• Proteogenomics target assessment: Assesses detectability of alternative isoforms for proteogenomics by characterizing novel ORFs and their representation in proteomics databases.

Methodology:

Calculates quality descriptors for transcript models, junctions, and transcript ends; applies a set of 47 descriptors to assess transcript and preprocessing-pipeline quality; develops filtering strategies to remove technical artifacts; and identifies and curates novel transcripts, replacing erroneous sequences.