Transcriptomics
The Single-Cell Omics Platform offers traditional transcriptomic services, which are listed below. SCOP provides basic bioinformatic support which includes data processing, QC, mapping and differential gene expression analysis. Scripts for Gene Ontology Analysis and visualization can be provided.
Services
Messenger RNA Sequencing
mRNAseq, Profiling of the protein-coded mRNA transcriptome.
Small RNA Sequencing
Small RNAseq: Transcriptomic analysis of small RNAs.
Guidelines
Please read through our guidelines below.
RNA extraction is the responsibility of the user. The extraction protocol must include a DNase treatment to prevent genomic DNA contamination.
For small RNAseq applications, ensure that the extraction method preserves small RNA. If you are unsure whether your workflow is suitable, please contact SCOP for guidance.
The quality of the RNA will reflect the downstream process – poor quality may lead to compromised data. A RIN> 7 is strongly recommended.
Please contact SCOP for more information.
Please prepare samples for SCOP as follows:
- Randomize samples (please take the experimental setup into consideration upon randomization)
- Prepared RNA tubes for both library construction and QC must be delivered at a specific concentration depending on the assay type.
In general, SCOP recommends:
mRNAseq: >5ng/µl
total RNAseq: >25 ng/µl
small RNAseq: >20 ng/µl
- RNA QC (optionable)
- Library preparation, QC and normalization
- Pooling and Sequencing on NovaSeq X Plus
- FASTQ files
- Data processing and QC using NF core pipeline
- Differential Gene Expression analysis
- Data report
Alignment and gene expression quantification are performed by the nf-core RNA-seq pipeline. This pipeline performs extensive quality control, allowing for robust detection of low-quality samples. The decision to include or exclude samples will, in most cases, be made in collaboration with the user. In clear-cut cases however, the decision may be taken by the SCOP bioinformatician.
Differential expression is performed using the edgeR framework, with results being delivered as tables of differential expression statistics. We support one-way and two-way designs, as well as repeated-measures ANOVA-like setups, and the inclusion of batch-effect variables.
Contrasts of interest are defined in collaboration with the user. Where appropriate, SCOP will attempt to detect missing batch variables and will contact the user if their inclusion is suspected to be necessary.
The price for services depends on the technique, number of samples, and sequencing depth. The sequencing price per sample usually becomes cheaper as the number of samples increases. If you would like us to provide a cost estimate, please contact SCOP with information about the number of samples and techniques you are interested in.
Please recognize and acknowledge SCOP’s contributions to the scientific improvements in your project. Being acknowledged in publications is very important as it serves as documentation for the SCOPS's value and performance.
Workflow
Please click the image below to view a larger version in your browser.
