RNA-seq analysis

From FASTQ-files to insights

RNA-seq - a de facto standard in transcriptional analysis

RNA-seq has come a long way since its introduction in 2008. Longer reads, higher throughput, and more efficient computational tools means that RNA-seq is here to stay. We analyze your RNA-seq data using the latest computational techniques in our established analytical pipelines. Each step in our pipeline utilizes open-source software components, which makes it easy for you to reproduce our results. We generate elegant and informative graphics using common visualization libraries (ggplot2, pandas, and NumPy). Our graphics is produced in Portable Document Format so that files can be easily opened in Adobe Illustrator or Inkscape. We provide you with code and tables so results can be consistently reproduced.

Cloud-based transfer of your data

Most transcriptome analysis is conducted using Illumina's HiSeq instrument, because the throughout is sufficient to enable rapid transcriptome characterization when high sequencing depth is needed. Our customers often have a large number of compressed FASTQ files, which is most of the time the starting point of our analysis. The FASTQ format is relatively simple, and it contains both the sequence and quality information about each sequenced base. The quality information in the FASTQ format is analyzed, and sequences of low quality are discarded. RNA-seq has a good signal to noise ratio, however, it's still important to eliminate parts of the data contributing to noise.

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Transcriptomics (e.g. RNA-seq, microarray)
Epigenomics (e.g. ChIP-seq)
Genomics (e.g. genome assembly and annotation)
Metagenomics (e.g. 16S rRNA)
Proteomics (e.g. Mass spectrometry)

Bioinformatics/Big data consulting
Statistical consulting
My research project