- Expression Analysis in RNASeq
- Use Cases
- Summary and Methods
- Inputs
- Outputs
- Workflow Walkthrough
- Results Walkthrough
- Citations
- Built with
- Genomic Variant Analysis
- Use Cases
- Summary and Methods
- Inputs
- Outputs
- Workflow Walkthrough
- Results Walkthrough
- Citations
- Built with
- Human Haplotype
- Summary
- Workflow Walkthrough
- Citations
- Built with
Expression Analysis in RNASeq
This workflow can be used to determine gene expression, splice variants and differential expression analysis.
Version 1.1.1
Use Cases
- Determine differentially expressed genes between two or more groups of samples (treated vs untreated, knock-out vs wildtype, cell type A vs cell type B)
- Determine differentially expressed transcripts between two or more groups of samples
- Compare the gene expression profiles of samples
Summary and Methods
This workflow is designed to help the user thoroughly analyze RNA sequencing data. Currently, two functions are supported: Full Analysis and Recalculate Statistics. Both functions include the option to specify whether the data include Human Cancer Samples. Click the toggles below to learn more about each function.
Full Analysis
Recalculate Statistics
Human Cancer
Inputs
Outputs
Workflow Walkthrough
Results Walkthrough
Citations
Built with
Genomic Variant Analysis
Identify single-nucleotide variants (SNVs), indels, and structural variants in a diploid genome resequencing projects by comparison to a reference genome.
Version 1.6.1
Use Cases
- Determine variants in DNA samples compared to a reference genome including single nucleotide variants (SNVs), insertions, deletions and structural variants
- Germline Variant Calling
- Variant Calling in Ancient DNA
- Somatic Mutation Detection
- Determine variants in DNA samples compared to a custom reference genome for small or synthetic genomes
- Plasmid
- Virus
- Bacteria
- Synthetic Genome
- Sequencing Platform supported include Illumina, Pacbio and Oxford Nanopore (ONT)
Summary and Methods
This workflow is designed to help the user determine variants in DNA samples when compared to a reference genome. Currently, four different input DNA datatypes are supported: Germline (Diploid), Ancient DNA, Small Genomes (Viral/Prokaryotic/Synthetic), and Somatic (Human Cancer). Workflows can be run either with Parabricks, Sentieon or native open-source tools (NOST). Click the toggles below to learn more about each supported dataype.
Germline (Diploid)
Ancient DNA
Small Genomes (Viral/Prokaryotic/Synthetic)
Somatic (Human Cancer)
Inputs
Outputs
Workflow Walkthrough
Results Walkthrough
Citations
Built with
Human Haplotype
Determine the haplotype of certain human genes, include HLA, RBG, and Codis.
Version 0.0.2
Summary
Sequence reads are aligned and their haplotype is predicted using Hisat-Genotype [1].