Transcriptomics Service
Transcriptome Assembly and Transcripts Quantitative Profiling
Understanding the full set of transcripts is crucial for insights into gene function and expression. We provide high-quality de novo and reference-guided assembly to accurately reconstruct the complete set of transcripts in your samples.
We meticulously pre-process and normalize raw sequencing data to ensure accurate and reliable gene abundance comparisons across samples for downstream analyses.
Differentially Expression Identification
We utilize sophisticated statistical methods to discover genes that exhibit significant differences in expression levels between experimental conditions or biological types. The selection of statistical methods is tailored to the experiment design or requirements, ensuring precise and contextually appropriate results.
Enrichment and Network Analysis
By employing functional annotations from various biological pathway databases (Gene Ontology, KEGG, Reactome, or WikiPathways), we determine associations between specific gene sets and particular biological processes or molecular functions.
The network analysis investigates how key components of different pathways interact, identifying crucial regulatory events that play roles in multiple biological processes and pathways.
Expression Pattern Profiling and Clustering
The service encompasses gene expression clustering for single-cell-seq data. Additionally, for the sample collected in a time series, we provide the developmental trajectories of genes in different experimental conditions or biological states and cluster trajectories with similar expression profiles using various clustering techniques.
Customized Analysis and More...
We also provide customizable analysis options tailored to your research needs, including multi-omics comparisons, helping to uncover the biological significance behind gene expression changes and offering deeper insights into underlying molecular mechanisms.