One of the services we provide at the Applied Bioinformatics Laboratories is RNA sequencing (RNA-seq). RNA-seq uses next-generation sequencing methods to reveal the presence and abundance of RNA in a sample at a specific moment in time. This methodology can investigate different populations of RNA such as mRNA, total RNA, and various small RNAs. RNA-seq analysis enables the researcher to look at differences in gene expression, alternatively spliced transcripts, post-transcriptional modifications, gene fusions, and mutation or single nucleotide polymorphisms in different groups and treatments.

Request an RNA-Seq Service

To request this service from us, please provide the following:

• a sample sheet with the corresponding conditions for the samples
• the organism(s) of the particular study
• the link to the generated FASTQ data (obtained from NYU Langone’s Genome Technology Center or another sequencing facility)

You receive the following from us:

• a comprehensive report
• quality assessment: mapping quality, alignment statistics, and contamination analysis
• individual bigWig files for visualization using a genome browser
• a principal component analysis plot for assessment of sample similarity
• an annotated gene expression table containing normalized gene expression in each sample, logarithm of fold change across groups, statistics and gene description

Additional or Customized Analyses

We also provide the following analyses:

• gene-ontology and pathway enrichment analysis, including visualizations
• supervised or unsupervised clustering of differentially expressed genes
• Venn diagrams of gene list overlaps
• integration with other “-omics” datasets

Each of these may be subject to an additional charge.

Additional Resources

Below you can find links to the computational pipelines that we typically use for our analyses:

• Seq-N-Slide pipeline (RNA-star and RNA-star-groups-dge routes)  
• RNA-seq pipeline

 The following select publication has used our analyses:

• Cimmino L, Dolgalev I, Wang Y, Yoshimi A, Martin GH, Wang J, et al. Restoration of TET2 function blocks aberrant self-renewal and leukemia progression. Cell. 2017;170(6):1079–95.