Use Cases

GenPipes offers several genomic analysis pipelines that can be used for various bioinformatics analyses. These pipelines can be utilized for performing a wide range of standardized and tailored genomic analysis.

Listed below are key real-life applications of genomic analysis performed with GenPipes:

Detecting COVID-19 Mutations 

GenPipes CoVSeQ Pipeline has been used as part of CoVSeQ project for genome sequencing to detect COVID-19 gene mutations. CoVSeQ deals with real-time tracking of Quebec SARS-CoV-2 evolution.

CoVSeQ is a partnership between the Institut National de Santé Publique du Québec (INSPQ) and the McGill Genome Centre to sequence the viral genome of Quebec patients with COVID-19 disease. The viral samples are taken from a Quebec viral biobank, termed the CoVBanQ, which is hosted in the Laboratoire de Santé; Publique du Québec (LSPQ).

You can obtain a real-time snapshot of evolving SARS-CoV-2 populations in Québec and access interactive data visualizations. It is meant for virologists, epidemiologists, public health officials and citizen scientists. Through interactive data visualizations, CoVSeQ allows exploration of continually up-to-date datasets, providing a novel surveillance tool to the scientific and public health communities.

For more details, visit CoVSeQ Website and Sequencing Workflows.

GenPipes Release version 4.1 supports a new sequencing pipeline to support Nanopore CoVSeQ analysis. For details, visit Nanopore CoVSeQ Pipeline.

RNA Sequencing 

The RNA Sequencing Pipeline helps to quantify transcripts and genes using a reference genome and test for differential expression across experimental conditions. It is also possible to call single nucleotide variants (SNVs), detect fusion gene events and assess alternative splicing events.

Denovo RNA Sequencing 

The De Novo RNA Sequencing Pipeline assembles reads to transcripts in the absence of a reference genome, annotates transcripts and tests for differential expression. This is well suited to organisms that are not yet characterized.

miRNA Sequencing 

This pipeline can be used to quantify known miRNAs, discovers novel ones using a reference genome and performs differential expression analysis. Additional analysis may include pathway testing, target candidates analysis or miRNA editing.

SARS-CoV-2 Genome Sequencing 

The SARS-CoV-2 genome Sequencing Pipeline is designed for COVID-19 Coronavirus research and surveillance, enabling complete genome sequencing of the new SARS-CoV-2 virus responsible for the COVID-19 pandemic.

SARS-CoV-2 Nanopore CoVSeQ 

The SARS-CoV-2 Nanopore CoVSeQ Pipeline is designed to implement ARTIC SARS-CoV2 protocol, Version 4 / 4.1 (V4.1), using Nanopolish. This protocol is closely followed in GenPipes Nanopore sequencing pipeline with majority of changes related to technical adaptation of the protocol to be able to run in a High Performance Computing (HPC) environment.

DNA Methylation 

The Methylation Pipeline helps to analyze data coming from bisulfite converted DNA assayed by various sequencing assays such as RRBS, CpG capture, whole genome sequencing or microarrays. Our analysis computes methylation levels and performs differential analysis between experimental conditions.

Amplicon Sequencing 

The Amplicon Sequencing Pipeline can process Illumina, PacBio pyrotags amplicons from the 16S, 18S or ITS amplicons. OTUs are picked and diversity is analyzed within and between communities. Further analyses include differential abundance testing or metagenome functional content prediction.

DNA Sequencing 

The DNA Sequencing Pipeline offers state of the art DNA-seq analyses detects and annotates variants in whole exomes, whole genomes or high coverage amplicons. The analysis can also be pushed further by assisting with variant prioritization, or perform advanced cancer related analysis.

ChIP Sequencing 

The ChIP Sequencing Pipeline helps in analyzing DNA fragments from immunoprecipitated chromatin by calling alignment peaks on the genome, annotating the said peaks and performing additional analyses such as motif enrichment and discovery. Designed experiments can be analyzed by testing for differential binding between experimental conditions.