As one of the most commonly requested services, our Services team can help you get the most out of RNA-seq data. This service typically includes:
- Preprocessing: Alignment, assembly, quantification of expression
- Expert QC and EDA (e.g. PCA)
- Testing for simple or complex differential expression using linear models
- Customized visualisations
- Testing pathways & gene Sets
- Other: eSNV calling, fusion detection, deconvolution, PDX, decontamination etc.
- Others: Alternate-splicing analysis etc.
(scRNA-Seq) is widely used to measure the genome-wide expression profile of individual cells. This allows us to study new biological questions in which cell-specific changes in transcriptome are important (e.g., cell type identification and heterogeneity of cell responses). Strategies for scRNA-Seq data analysis differ markedly from those for bulk RNA-Seq.
- Our pipeline uses Cell Ranger (10X Genomics) to process 10X single-cell data and generate count matrices.
- Our pipeline uses the R package Seurat to carry out scRNA-Seq analysis, which includes:
- Quality-control assessment
- Data exploration
- Clustering and cell-type identification
- ‘Per-cluster’ differential expression
- Trajectory analysis is also performed to uncover continuous, dynamically changing cellular identities, using Monocle.
- Our scRNA-Seq pipeline is also tailored to process and analyze single-cell data from different platforms.
Basic deliverables for amplicon-based metagenomics (16S, 18S, ITS, COI) sequencing data analysis include
- Denoising of raw reads to ASVs using a dada2- or Qiime-based workflow
- Taxonomy assignments
- Functional annotations
- Output files directly usable with Microbiomeanalyst or Calypso, allowing researchers to easily create their own tailored publication-standard figures.
We are also particularly committed to leading innovation in both metagenomics and metatranscriptomics. We offer state-of-the-art integrated analytic pipelines for amplicon-based metagenomics (16S, 18S, ITS, COI) or whole genome sequencing metagenomics (WGS), and metatranscriptomics (RNA-Seq) services.KEGG global metabolic networks (top picture) and co-occurrence networks (bottom picture) can be derived from WGS and 16S deliverables using the microbiome analyst interactive platform.
We have extensive experience de novo assembling small (haploid; prokaryotes, archaea) and large (diploid; eukaryotes) novel genomes using both long read technologies and short reads for hybrid assembly approaches.
Our toolbox also includes:
- Detection, polishing and circularization of bacterial chromosome/s or other circular molecules (plasmid, mitochondria)
- Refinement of de novo assembly using data from supporting technologies (ex.: Hi-C (Click here for more details)
- Complete annotation processes (eg. PGAP for prokaryotes, Augustus/MAKER for eukaryotes)
- Reference-based variant detection (INDEL, SNP, large structural rearrangements, phased alleles) and multi genome comparison
- Full-length RNA transcript isoform identification and detection of novel isoforms
- Epigenetic base modification detection (ie. microbial/eukaryotic DNA modifications)
- Multiplexed environmental samples (eg. species-level resolution via full-length 16S/18S rDNA, ITS regions)
Long read sequencing offered by third-generation sequencing providers (eg. PacBio (Click here for more details), Oxford nanopore (Click here for more details) allows for large and difficult to assemble regions of the genome (eg. TE’s, repeats, rRNA islands) to be captured in single long reads which can then be accurately anchored in the de novo assembly.
The addition of PacBio HiFi long reads (PacBio (Click here for more details), which are of Illumina-type quality, along with increasing progress in terms of throughput and cost reduction make long-read sequencing an attractive solution for many types of projects.
We are always eager and motivated to innovate and use the latest advancements in Sequencing technologies to allow for the greatest success with our clients and collaborators.
We have extensive experience with the identification of variants from whole genome sequencing (WGS) or whole exome sequencing (WES) data. This service generally involves:
- Processing raw sequencing data to variant calls following the GATK best practices
- Detecting structural variants and CNVs
- Annotating and filtering variants according to specific needs of the project to help with variant prioritization (e.g. de novo, compound het. in trios using the GEMINI framework.)
Publications & Examples of our work for DNA-Seq can be found in these papers:
- Nicolas, G., Charbonnier, C., Wallon, D. et al. SORL1 rare variants: a major risk factor for familial early-onset Alzheimer’s disease. Mol Psychiatry 21, 831–836 (2016). Click here access the paper.
- Monlong J, Girard SL, Meloche C, Cadieux-Dion M, Andrade DM, Lafreniere RG, et al. (2018) Global characterization of copy number variants in epilepsy patients from whole-genome sequencing. PLoS Genet 14(4): e1007285. Click here to access the paper.
By sequencing the DNA from both the tumour and healthy cells, WGS also enables the discovery of novel cancer-associated variants, including single nucleotide variants (SNVs), insertions/deletions (INDELs), structural variants (SVs), and copy number alterations (CNAs).
- We employ a combination of callers that result in a reliable set of variants from matched tumor-normal pairs. For SNVs and INDELs calling, we applied Bcbio.variations ensemble approach with GATK MuTect2, VarDict, Strelka2 and VarScan2 calls. Variants discovered by at least two variant callers are selected.
- Similarly, SVs are identified using multiple callers such as DELLY, LUMPY, WHAM, and SvABA were combined using MetaSV.
- Chromosomal and specific gene-level amplification and deletion events can be deduced from sequencing data using CNVkit, which analyzes coverage information. Our pipeline also integrates specific cancer tools to estimate tumor purity and tumor ploidy of sample pair normal-tumor.
- The list of variants are annotated with different types of information such as genes/transcripts affected, genomic location, consequence/effect, and known variants from clinical databases (e.g., ClinVar and CIViC).
- Our tumor-normal WGS pipeline is also applicable to patient-derived xenograft (PDX) and mouse models
For organisms lacking a good reference genome or transcriptome, we can perform de novo assembly and annotation using the latest approaches.
- Assembly and transcript quantification with Trinity
- Annotation using Trinotate
- Differential expression analysis & GO/KEGG enrichment analysis
- Customized visualisations
A few examples of publications our RNA-seq assembly services contributed to:
- RNA-sequencing to assess the health of wild yellow perch (Perca flavescens) populations from the St. Lawrence River, Canada. [PMID: 30296762]
- Snow crab (Chionoecetes opilio) hepatopancreas transcriptome: Identification and testing of candidate molecular biomarkers of seismic survey impact. Click here to access the publication.
- Transcriptomic Response of Purple Willow ( Salix purpurea) to Arsenic Stress [PMID: 28702037]
Genome-wide profiles of DNA-protein interaction/histone modification and chromatin accessibility sites obtained by Chip-Seq and ATAC-Seq, respectively, provide valuable insights into the regulatory landscape of the genome.
- For both Chip-Seq and ATAC-Seq, we deliver a list of significant peaks that are annotated with the genomic location (distance to nearest gene and genic annotation) and motif enrichments.
- For visualization, we generate the epigenetic tracks via UCSC Genome Browser or WashU epigenome browser. Metagene plots and enrichment density heatmaps are also generated using ngs.plot or HOMER.
- Differential binding and accessibility could also be assessed by first obtaining a ‘reference peak set’ by merging peaks across samples in different groups.
These datasets can be integrated with other methods, such as RNA-Seq, for a multi-omic approach to studying gene expression.
Epigenomics analyses also involve studying changes in DNA methylation. With our Methyl-Seq pipeline:
- Reads are aligned to a bisulfite-converted reference genome, and methylation levels for each CpG site are estimated using Bismark.
- Differential methylation is performed using simple or complex linear models
Our Methyl-Seq pipeline is also applicable to reduced representation bisulfite sequencing (RRBS) and targeted bisulfite sequencing using the SeqCap Epi system.
We can help you map long-range chromatin interactions to interrogate the genome’s 3D structure This service typically includes:
- Preprocessing: Alignment, filtering pairs
- ENCODE QC standards
- Contact maps, TAD domain annotation
- Others: Visualization, integration with other genomics data (ChIP-Seq) ,etc.
Lalonde, Simon, et al. “Integrative analysis of vascular endothelial cell genomic features identifies AIDA as a coronary artery disease candidate gene.” Genome biology 20.1 (2019): 1-13.
We can help you with structural bioinformatics that integrates with other genomics studies. This service typically includes:
- Structure visualization
- Mutation mapping.
- MD simulation, binding energy
- Contact maps
In addition, we also offer a wide range of services to clients as listed below
- Other Single-Cell Assays (snATAC-seq, snDNA-seq)
- Integrative Analyses (e.g. with SNF)
- Expression & Methylation microarrays
- Misc. sequencing assays: DRIPc-seq, RIP-seq, etc.
- miRNA and other small RNA-seqs
- CRISPR-Cas9 data and statistical analysis
- Sequencing of pools (Pool-seq)
- Population Genomics: GBS, RAD-Seq
- Metabolomics data integration(processed data only)
- Proteomics(same caveat as for metabolomics)
- Rare Diseases
- Secure Computing
- Network Visualization and Analysis
- Image Analysis