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FFPE RNA-Seq

Service Overview
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This assay applies the power of next-generation sequencing (NGS) to gene expression profiling of typical clinical samples. Based on the TruSeq® RNA Access Library Prep Kit and Novogene’s in-house bioinformatics pipelines, it provides robust and comprehensive transcriptomic analysis of human RNA isolated from FFPE and other low-quality clinical samples.

The Novogene Advantage

  • Comprehensive validation from FFPE RNA isolation to library construction to sequencing.
  • Unsurpassed data quality with higher Q30 score, higher clean data percentage, higher mRNA mapping reads, and lower rRNA mapping reads than polyA+ RNA-seq.
  • Extensive experience with hundreds of clinical FFPE samples analyzed.
  • Comprehensive data analysis using widely accepted mainstream software and mature in-house pipelines. Our professional bioinformatics team offers standard, advanced, and customized analyses tailored to your needs.

FFPE RNA-Seq Service Overview

Sample Requirements

  • Approximately five 4-µm FFPE sections, each with tissue area ≥ 25 mm2 and tumor content ≥ 20%.

Sequencing Strategy

  • HiSeq X Ten or NovaSeq 6000, PE150

Data Quality Guarantee

  • We guarantee that ≥ 80% of bases have a sequencing quality score ≥ Q30, which exceeds Illumina’s official guarantee of ≥ 75%.

Recommended Sequencing Depth

  • 40 M reads

Turnaround Time

  • 20 calendar days from sample receipt to raw data delivery;
  • 7 calendar days for standard bioinformatics analysis.

FFPE RNA-Seq Bioinformatics Analyses Workflow

Interested in learning more about our FFPE RNA-Seq service? Click on the link below to fill out a short form and download our informational brochure.

View brochure & validation reports

RNA Input Requirement

Figure 1. RNA Input Requirement. DV200 is used to ascertain sample quality. Samples with DV200 > 70 are defined as high quality, samples with 50 < DV200 < 70 are defined as medium quality and samples with 30 < DV200 < 50 are defined as low quality. Samples with DV200 < 30 are not accepted for this analysis.

Unsurpassed Data Quality

Compared to polyA RNA-Seq, this workflow is superior in multiple aspects of data quality metrics with higher percentages of clean data, lower error rate, higher Q30 and lower percentage of rRNA reads.

Table 1. In-house results on the data quality metrics of this FFPE RNA-Seq assay.

Figure 2. Comparison of key data quality metrics parameters between polyA RNA-Seq (first row) and FFPE RNA-Seq (second row) on FFPE samples.

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