Bioinformatics Analysis

  1. Illumina Sequencing Data Analysis

    1. Genome-wide Variant Analysis

      For WGS and WES data, also for targeted gene panels data: germline and somatic variant calling; copy number variation analysis; structural variant analysis (better combined with PacBio data); and de novo genome assembly (better combined with PacBio data).

    2. Genome-wide Gene Expression Analysis

      Mainly for RNA-Seq data, also for small RNA sequencing data, or for a combination of both: differential expression analysis; functional annotation of differential gene expression with pathways and networks; gene fusion identification; variant identification; isoform identification and differential expression; and allele-specific expression.

    3. Genome-wide Epigenetic Analysis

      For ChIP-Seq, ATAC-Seq, or 3C/HiC-Seq data: peak calling for delineation of transcription factor binding and histone modification; and motif enrichment analysis.

    4. Metagenomics Analysis

      For 16S/ITS and DNA/RNA shotgun metagenomics data: genus/species identification; taxonomy classification; microbiota composition analysis; de novo microbiome assembly; inter-species interaction and pathogen/microbiota-host interaction.

  2. PacBio Sequencing SMRTLink Data Analysis

    he following analysis pipelines are available within PacBio SMRTLink software and can be performed upon request. Additional custom bioinformatics services are also available upon request, including genome assembling, transcriptome annotation, and others.

    1. Circular Consensus Sequencing (CCS)

      Identify consensus sequences for single molecules.

    2. Hierarchical Genome Assembly (HGAP)

      Generate de novo assemblies of genomes using Continuous Long Reads (CLR).

    3. Microbial Assembly

      Generate de novo assemblies of small prokaryotic genomes between 1.9 – 10 Mb and companion plasmids between 2 – 220 kb.

    4. Base Modifications

      Identify common bacterial base modifications (6mA, 4mC) and optionally analyze the methyltransferase recognition motifs.

    5. Iso-Seq

      Characterize full-length transcript isoforms.

    6. Minor Variants Analysis

      Identify and phase minor single nucleotide substitution variants in complex populations.

    7. Structural Variant Calling

      Identify structural variants (default: ≥ 20 bp) in a sample or set of samples relative to a reference.

  3. Single-Cell Sequencing Data Analysis

    The BIG Core offers a wide range of standard and custom single-cell analysis approaches to explore the molecular aspects of cellular heterogeneity, population diversity, and complexity within single-cell samples. Please contact the BIG Core for more detail of options.

  4. Spatial Sequencing Data Analysis

    The BIG Core offers standard and custom spatial transcriptomics approaches to explore molecular and cellular aspects, preserving the spatial context within tissue sections, for the study of cell-cell networks and interactions. Please contact the BIG Core for more detail of options.