RecountDB

RecountDB provides corrected read counts and genome-mapped data derived from next-generation sequencing (NGS) datasets in NCBI's Short Read Archive to mitigate sequencer errors and improve detection and quantification of rare transcripts in RNA-seq and 5' capped transcription start site experiments.

Key Features:

• Source provenance: Secondary database entries are derived from primary datasets housed in NCBI's Short Read Archive (SRA).
• Corrected read counts: Supplies read counts that have undergone a correction process to reduce the impact of sequencer errors.
• Genome-mapped data: Provides read data mapped to the relevant genome for each dataset.
• Experimental scope: Includes datasets specific to RNA-seq and 5' capped transcription start site experiments.
• Error mitigation focus: Designed to improve accuracy and reliability by addressing high-throughput sequencing error effects on transcript detection and quantification.
• Taxonomic coverage: Comprises 2265 entries spanning 45 different organisms.
• Content updates: Repository content is maintained with ongoing updates to expand entries and organism coverage.

Scientific Applications:

• Rare transcript detection: Enables more reliable detection and quantification of rare transcripts in RNA-seq and 5' capped TSS experiments by using corrected counts.
• Cross-species expression studies: Supports comparative gene expression analyses across the 45 organisms represented in the database.
• Transcriptomic accuracy improvements: Serves to increase the accuracy and reliability of downstream transcriptomic analyses affected by sequencer errors.
• Molecular and systems biology: Facilitates basic molecular biology investigations and advanced studies of complex biological systems that depend on high-quality transcript counts.

Methodology:

Entries are derived from primary NGS datasets in NCBI's Short Read Archive and are processed with a correction procedure applied to read counts and genome-mapped data to mitigate sequencer errors.