RNA-SEQ ANALYSIS

Accurately align RNA-Seq data of any size and sequencing technology against a reference sequence, then perform extensive, in-depth analysis, from differential gene expression to mRNA isoform visualization.

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Use Lasergene Genomics to get the whole picture of your RNA-Seq data.

RNA-seq is currently one of the leading technologies available for exploring the transcriptome, which is crucial to connecting the information about a genome with its functional protein expression. But RNA-Seq data analysis can prove to be a challenge for many researchers as the applications for this technology are quite broad. Lasergene Genomics quickly and easily aligns any size RNA-Seq or miRNA data set — from bacteria to human— against a reference genome, and then offers extensive RNA-Seq data analysis tools to explore your results in-depth. Perform statistical analyses of differential gene expression using EdgeR or DESeq2, easily identify genes of interest using comprehensive filtering tools, utilize gene ontologies to identify the relationship between genes with known biological functions, easily visualize and analyze mRNA isoforms using Sashimi plots, see variants detected in the sequencing data, and more. We don’t always know what we are looking for when we begin RNA-Seq analysis. Lasergene Genomics makes it easy to explore points of interest so that you can get the whole picture of your data set.

RNA-Seq analysis in 4 simple steps

Step 1

Set up RNA-Seq alignment

Step 2

Select DESEQ2 or EdgeR to identify differentially expressed genes

Step 3

Analyze and compare gene sets

Step 4

Visualize results

Learn more about RNA-Seq Analysis

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Resources

Please see our resources below for more information on RNA-Seq data analysis.

Unlocking RNA-Seq Data: From Reads to Results

Watch Webinar

RNA-Seq Assembly and Normalization Methods

Read Blog Post

Automating Workflows in DNASTAR’s Lasergene Genomics Suite for High-Throughput Applications

View Poster

Considerations for Next-Gen Sequence Assembly and Analysis Software Selection

Read White Paper

Cloud Assemblies for NGS Sequences

Watch Webinar

Free NGS Assembly and Alignment for Genomic Sequencing Data

Read Blog Post

Is Open Source NGS Software for You?

Read Blog Post

Q&A: NGS Sequence Assembly on the Cloud

Read Blog Post

Tutorials

Watch one of our videos or check out one of our written tutorials to learn more about RNA-Seq data analysis.

RNA-Seq Project Set Up in SeqMan NGen

Learn how to set up an RNA-Seq project with replicates in SeqMan NGen.

Creating Gene Sets and Comparing in the Venn Diagram

See various ways to filter and create gene sets of interest, then compare the gene sets in the Venn diagram in ArrayStar.

Using Sashimi Plots in GenVision Pro

This quick tip video demonstrates how to interpret Sashimi plots in GenVision Pro.

Visualizing Genes and SNPS from ArrayStar in GenVision Pro

This quick tip video demonstrates how to visualize groups of genes or SNPs from ArrayStar in GenVision Pro.

FAQs

Which RNA-seq analysis methods are used to identify differentially expressed genes?

BioConductor’s DESEQ2 and EdgeR statistical packages can be used to identify differentially expressed genes. Start by using the SeqMan NGen wizard to specify a Bioconductor statistical package as the normalization method, then perform the assembly. Open the finished assembly in ArrayStar to perform downstream analysis.

How do I visualize mRNA isoforms?

To visualize mRNA isoforms, use GenVision Pro’s Sashimi plots. Isoforms can also be analyzed in text format using ArrayStar’s Isoform table.

Can I align RNA-Seq sequence data to mRNA sequences?

Yes, RNA-seq assemblies can be run with either mRNA reference sequences or whole genome reference sequences.

What types of read technology are supported for an RNA-Seq alignment?

Lasergene Genomics supports Illumina, 454, Ion Torrent, and Sanger read technology for aligning and performing RNA-Seq data analysis.

Where do I get the reference sequence for my RNA-Seq alignment?

If your organism of interest is a commonly-studied species, you can choose to download a DNASTAR genome template package or import a reference sequence from NCBI from within the SeqMan NGen wizard while setting up your RNA-Seq project.

If I have multiple samples, can I run them as separate RNA-Seq alignments?

Yes. To run multiple samples as separate RNA-Seq alignments, choose Multi Sample as the experiment type in the Input Sequence screen of the SeqMan NGen wizard. You will be prompted to group and name each experiment, which you can do automatically or manually. Each data set will be run against the reference sequence independently and an .assembly package will be created for each sample.

What types of post-alignment RNA-seq analysis options are available?

By using ArrayStar for your RNA-seq data analysis, you can combine gene expression data, isoform info, detected variants, annotations and ontology in a single project. You can compare gene expression values between experiments using scatter plots, heat maps, and line graphs. In addition, you can identify genes, isoforms and variants of interest through simple or advanced filtering based on signal, annotation values or many other options.

Can Lasergene Genomics analyze differential gene expression values for miRNA data as well as RNA-Seq data?

Yes. When setting up your miRNA project in SeqMan NGen, select RNA-seq/Transcriptomics>miRNA as your workflow. Then proceed through the wizard following the same steps you would for an RNA-Seq project: input your reference sequence(s) and reads, name and group your replicates, and define a control.

Can I quantitate miRNA expression levels across multiple samples?

Yes. If you have a control, our software will align the miRNA .fastq data for each sample and calculate differential expression using either DESEQ2 or EdgeR (BioConductor).

What reference sequence should I use for my miRNA assembly?

For an miRNA project, you can use either full length annotated genomes (that often have miRNA genes annotated) or a set of miRNA sequences from your organism.

Can I discover novel miRNAs?

Yes, you can do this by performing a de novo miRNA assembly or by assembling your miRNA data to an unannotated genome where new miRNA genes can be discovered via alignment.

Benchmarks

Lasergene Genomics Reference-Guided Genome Alignment Benchmarks
Data Set	Sequence Technology	Coverage	Assembly Time
Yeast Genome (ERX009559)*	Illumina	22X	2 Minutes
Yeast Genome (srx1484451)*	Ion Torrent	22X	3 Minutes
Drosophila Genome (SRX1961013)*	Illumina	23X	23 Minutes
Human Exome (SRR701474)*	Illumina	81X	53 Minutes
Mouse Rna-seq (SRX2013345)*	Ion Torrent Proton	NA	1.3 Hours
Human Rna-seq (SEQC-UHRR & Brain)	Illumina	NA	1.6 Hours
Rice Genome (Srx179262)*	Illumina	34X	1.6 Hours
Human Exome (SRX1873412)*	Ion Torrent Proton	162X	3.9 Hours
Human Genome (SRP000239)*	Illumina	36X	23 Hours

Citations

A transcriptome software comparison for the analyses of treatments expected to give subtle gene expression responses
Thawng, C.N., Smith, G.B. (2022). BMC Genomics 23, 452. https://doi.org/10.1186/s12864-022-08673-8.

Genome, host genome integration, and gene expression in Diadegma fenestrale ichnovirus from the perspective of coevolutionary hosts
Kim J, Rahman M-M, Kim A-Y, Ramasamy S, Kwon M and Kim Y (2023). Front. Microbiol. 14:1035669. https://doi.org/10.3389/fmicb.2023.1035669.

Targeting prolyl-tRNA synthetase via a series of ATP-mimetics to accelerate drug discovery against toxoplasmosis
Yogavel M, Bougdour A, Mishra S, Malhotra N, Chhibber-Goel J, Bellini V, et al. (2023). PLoS Pathog 19(2): e1011124. https://doi.org/10.1371/journal.ppat.1011124.

MyD88 dimerization inhibitor ST2825 targets the aggressiveness of synovial fibroblasts in rheumatoid arthritis patients
Ramirez-Perez, S., Vekariya, R., Gautam, S. et al. (2023). Arthritis Res Ther 25, 180. https://doi.org/10.1186/s13075-023-03145-0.

Cstf2t regulates expression of histones and histone‐like proteins in male germ cells
Grozdanov, P. N., Li, J. , Yu, P. , Yan, W. and MacDonald, C. C. (2018), Andrology, 6: 605-615. https://doi.org/10.1111/andr.12488.

Clubroot resistance gene Rcr6 in Brassica nigra resides in a genomic region homologous to chromosome A08 in B. rapa
Chang, A., Lamara, M., Wei, Y. et al. (2019). BMC Plant Biol 19, 224. doi:10.1186/s12870-019-1844-5.

CD63, MHC class 1, and CD47 identify subsets of extracellular vesicles containing distinct populations of noncoding RNAs
Kaur, S., Elkahloun, A.G., Arakelyan, A. et al. (2018). Sci Rep 8, 2577. https://doi.org/10.1038/s41598-018-20936-7

Apicidin attenuates MRSA virulence through quorum-sensing inhibition and enhanced host defense
Parlet, Corey P. et al. (2018). Cell Reports, Volume 27, Issue 1, 187 – 198.e6. https://doi.org/10.1016/j.celrep.2019.03.018.

Low-phosphate-selected Auxenochlorella protothecoides redirects phosphate to essential pathways while producing more biomass
Park S-H, Kyndt J, Chougule K, Park J-J, Brown JK (2018). PLoS ONE 13(6): e0198953. https://doi.org/10.1371/journal.pone.0198953.

In-frame indel mutations in the genome of the blind Mexican cavefish, Astyanax mexicanus
Daniel Berning, Hannah Adams, Heidi Luc, Joshua B Gross. Genome Biology and Evolution, Volume 11, Issue 9, September 2019, Pages 2563–2573. https://doi.org/10.1093/gbe/evz180.

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