Eukaryotic RNA-seq

Technical Specifications

TECHNICAL SPECIFICATIONS

Item	Details
Library Prep	Oligo(dT) bead-based mRNA enrichment
Read Alignment	STAR aligns cleaned reads to the reference genome; sequencing and library quality assessed by mapping rate, insert size and coverage uniformity
Quantification	Gene/transcript quantification against the annotation, outputting Count, FPKM, TPM and log2TPM
DE Thresholds	Read-count normalization (depth correction) → statistical modeling for P values → BH adjustment (padj); default \|log2(FoldChange)\| > 1 and padj < 0.05
Standard Delivery	Raw data + analysis report

Analysis Workflow

ANALYSIS WORKFLOW

Data QC

Adapter trimming · rRNA assessment

Read Alignment

STAR · reference genome

Quantification

Count / FPKM / TPM

Expression QC

Correlation · PCA

Differential Analysis

Volcano · clustering

GO Enrichment

BP / CC / MF

KEGG Enrichment

Pathways · bubble plots

GSEA

GO / KEGG gene sets

Bioinformatics Analyses

BIOINFORMATIC MODULES

Module	Core Methods & Metrics	Key Outputs
Sequencing Statistics	Base-quality and content distributions of raw fastq (R1/R2); 3′/5′ adapter trimming; filtering reads with mean quality < 20 or length < 50 bp and reads containing N; rRNA contamination rate assessment	Raw and cleaned data statistics tables, base-quality and content distribution plots
Alignment QC	STAR aligns cleaned reads to the reference genome; sequencing and library quality assessed at checkpoints including mapping rate, insert size and coverage uniformity	Mapping-rate statistics tables, per-sample alignment detail plots
mRNA Quantification	Gene/transcript quantification against the annotation with Count, FPKM, TPM and log2TPM outputs; Top-10 highly expressed transcripts summarized	Expression matrices, Top-10 expression tables
Expression Distribution & QC	Expression density distributions; per-sample violin/box plots; inter-sample Pearson correlation heatmaps (ideal within-group R² > 0.9) and PCA	Density plots, violin/box plots, correlation heatmaps, PCA plots
Differential Analysis	Read-count normalization (depth correction) → statistical modeling for P values → BH multiple-testing adjustment (padj); default \|log2(FoldChange)\| > 1 and padj < 0.05	Differential analysis result tables, volcano plots
DE Patterns	Expression-pattern clustering of differential genes; shared and unique DEG statistics across multiple comparisons	Pattern-clustering heatmaps, shared-DEG diagrams
GO Functional Enrichment	GO enrichment of DEGs (BP / CC / MF), reporting GeneRatio / BgRatio, enrichment factor and adjusted p-values	GO enrichment bubble and bar plots
KEGG & GSEA	KEGG pathway enrichment of DEGs; GSEA based on GO and KEGG gene sets, reporting ES, NES and adjusted p-values	KEGG enrichment plots, GSEA enrichment plots and dot plots

Example Results

SELECTED FIGURES FROM ACTUAL REPORTS

Gene Expression Density

log2(TPM) density curves per sample, assessing consistency of expression distributions.

Expression Violin / Box Plots

Distribution and probability density of gene-expression values per sample; boxes show medians and quartiles.

Inter-Sample Correlation Heatmap

Pairwise Pearson correlations and hierarchical clustering of samples, assessing biological-replicate consistency.

Inter-Sample PCA

Sample distribution after dimensionality reduction, showing intergroup separation and within-group clustering.

Differential Expression Volcano Plot

Dual thresholds of log2(FoldChange) and −log10(P) mark up/down-regulated genes, with key genes labeled.

DEG Expression-Pattern Clustering

Expression patterns of DEGs across samples (log10 TPM), with two-way clustering of genes and samples.

GO Functional Enrichment (Excerpt)

Enrichment results and significance of GO terms (BP / CC / MF) for DEGs; top terms shown.

GO-based GSEA Enrichment Plot

Enrichment-score curves with ranked-gene positions, annotated with NES and adjusted p-values.

KEGG-based GSEA Dot Plot

Gene ratios and significance of KEGG pathway enrichment; dot size indicates enriched gene counts.

FAQ

How long does a Eukaryotic RNA-seq project take?

From sample QC approval, standard timelines are 3-6 weeks (library prep, sequencing and bioinformatics included); large cohorts or deep custom analyses follow the confirmed study plan.

What if my samples fail QC?

Failed QC is reported immediately with reasons, and we discuss resampling or plan adjustments with you — sequencing never proceeds without qualification.

What bioinformatics is included? Can I add custom analyses?

Standard delivery covers QC, mapping/assembly, quantification, differential and functional enrichment analyses. Custom deep-dive and multi-omics integrative analyses are supported on request.

What samples do you need for Eukaryotic RNA-seq?

Total RNA ≥1 μg with RIN ≥7 (snap-frozen, dry ice); microbial and faecal samples ≥200 mg (sterile, −80 °C); whole blood for WGS ≥500 μL (EDTA only, never heparin). RNA integrity matters more than concentration. See Technical Resources → Sample Guide.