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CLIA ID: 31D2038676

miRNA-seq QC Report — Demo-Project

Mouse miRNA expression profiling · 27 samples · 6 groups · 7 DE comparisons
Project IDDemo-Project
SpeciesMus musculus (GRCm39)
Samples27
GroupsA, B, C, D, E, F
DE Comparisons7
Report Date2026-03-11

1. Project Overview

Total Samples
27
across 6 groups (A–F)
Total Raw Reads
~236M
across all samples
Avg Reads/Sample
~8.7M
trimmed R1 reads
Avg Mapping Rate
91.5%
reads mapping to miRNAs
Avg Detected miRNAs
604
per sample
DE Comparisons
7
with GO & KEGG enrichment
Study Design: Mouse miRNA expression profiling across six treatment groups — Group A (n=4), Group B (n=4), Group C (n=4), Group D (n=6), Group E (n=5), and Group F (n=4). Seven pairwise differential expression comparisons were performed, followed by Gene Ontology (GO) and KEGG pathway enrichment analysis on predicted target genes of significant DE miRNAs.

Analysis Pipeline

StepTool / MethodOutput Folder
Adapter trimmingmiRDeep2 (mapper.pl)00.TrimData/
Read QCFastQC + MultiQC01.FastqQualityCheck/
Read collapsing & genome mappingmapper.pl (miRDeep2) + Bowtie02.mapping/
miRNA quantificationmiRDeep2.pl (miRBase v22, GRCm39)03.mirdeep2/
Count & CPM matrix generationCustom R script04.Counts/
Differential expression + GO & KEGG enrichment on target genesDESeq2 + clusterProfiler (R)05.DE-GO-KEGG/

2. Sample Information

This project comprises 27 mouse (Mus musculus) samples divided into six treatment groups (A–F): Group A (n=4, Sample-01–04), Group B (n=4, Sample-05–08), Group C (n=4, Sample-09–12), Group D (n=6, Sample-13–18), Group E (n=5, Sample-19–23), and Group F (n=4, Sample-24–27). Libraries were prepared using the Qiagen Small RNA Kit and sequenced on an Illumina platform.

3. Read Quality (FastQC)

FastQC was run on trimmed R1 reads. Very high duplication rates are expected for miRNA-seq due to the limited number of distinct miRNA species. All samples pass basic sequence quality checks.

Full interactive report: 01.FastqQualityCheck/multiqc_report.html

4. Mapping Statistics (miRDeep2 mapper.pl + Bowtie)

Trimmed R1 reads were collapsed and aligned to the mouse genome (GRCm39) using mapper.pl (miRDeep2) with Bowtie. Mapping rates of 60–85% are typical for miRNA-seq to the genome; filtered mapping rates reflect the fraction of reads mapping among adapter-trimmed reads. Full statistics are in mapping.statistics.
SampleGroup Total Reads (M) Filtered Reads (M) Filter Rate Mapped Reads (M) Overall Mapping Rate Filtered Mapping Rate Detected miRNAs
Sample-01Group A 9.528.69
91.2%
 6.99
73.4%
 80.53%622
Sample-02Group A 10.099.25
91.7%
 7.02
69.6%
 75.88%626
Sample-03Group A 7.616.98
91.6%
 5.49
72.2%
 78.77%632
Sample-04Group A 8.407.95
94.7%
 6.62
78.8%
 83.22%579
Sample-05Group B 9.058.14
90.0%
 6.65
73.5%
 81.70%627
Sample-06Group B 9.638.99
93.3%
 7.39
76.7%
 82.20%613
Sample-07Group B 6.726.14
91.4%
 4.70
70.0%
 76.56%570
Sample-08Group B 7.156.66
93.1%
 5.50
76.9%
 82.60%606
Sample-09Group C 10.059.14
90.9%
 7.58
75.4%
 82.95%607
Sample-10Group C 10.469.63
92.1%
 7.59
72.6%
 78.78%595
Sample-11Group C 8.758.11
92.8%
 6.41
73.3%
 79.00%607
Sample-12Group C 11.4210.52
92.1%
 8.34
73.0%
 79.29%597
Sample-13Group D 8.488.01
94.5%
 6.74
79.5%
 84.15%601
Sample-14Group D 9.729.16
94.2%
 7.68
79.0%
 83.81%614
Sample-15Group D 8.558.08
94.5%
 6.73
78.7%
 83.27%611
Sample-16Group D 9.679.17
94.8%
 7.77
80.4%
 84.79%606
Sample-17Group D 9.318.70
93.4%
 7.35
79.0%
 84.55%630
Sample-18Group D 7.536.84
90.9%
 5.82
77.3%
 85.04%580
Sample-19Group E 8.877.17
80.9%
 5.30
59.8%
 73.88%589
Sample-20Group E 7.536.24
82.9%
 4.68
62.1%
 74.91%598
Sample-21Group E 10.078.77
87.0%
 6.41
63.6%
 73.13%618
Sample-22Group E 7.486.68
89.4%
 5.41
72.4%
 80.98%596
Sample-23Group E 9.578.94
93.4%
 7.29
76.1%
 81.53%634
Sample-24Group F 8.077.58
93.9%
 6.31
78.2%
 83.25%628
Sample-25Group F 8.367.74
92.6%
 6.50
77.7%
 83.94%588
Sample-26Group F 6.345.60
88.3%
 4.64
73.1%
 82.78%561
Sample-27Group F 8.227.74
94.1%
 6.45
78.4%
 83.36%563

5. miRNA Quantification (miRDeep2)

miRNA expression was quantified using miRDeep2.pl with the mouse miRBase reference (GRCm39). miRDeep2 scores both known miRNAs and novel miRNA candidates, reporting expression in raw read counts and RPM-normalised values. Per-sample result HTML files and PDF visualisations of miRNA hairpin structures are available in 03.mirdeep2/.

Below is a representative miRDeep2 hairpin structure visualisation for mmu-let-7b (Sample-08, Group C).

Representative miRDeep2 Figure — mmu-let-7b (Sample-08, Group C)

mmu-let-7b hairpin structure — miRDeep2 visualisation showing the read alignment to the predicted hairpin precursor. The 5p and 3p arms are indicated with mapped reads stacked above the secondary structure. Source: 03.mirdeep2/pdfs_*/mmu-let-7b.pdf

Output Files

File / FolderDescription
expression_*.htmlPer-sample miRDeep2 expression visualisation (interactive HTML)
result_*.htmlPer-sample miRDeep2 result summary including novel miRNA candidates
pdfs_*/PDF hairpin structure plots for detected miRNAs

6. miRNA Count Matrices

Raw read counts and RPM-normalised values were extracted from miRDeep2 output and merged across all 27 samples. Count and CPM matrices are available in 04.Counts/.
MatrixFileDescription
Raw counts04.Counts/rawCount/rawCount--matrix_with_all_samples.txtRaw miRNA read counts from miRDeep2
Normalised CPM04.Counts/normalizedCount/normalizedCount--matrix_with_all_samples.txtRPM-normalised values from miRDeep2
Per-sample raw04.Counts/rawCount/*_count.txtIndividual sample raw count files
Per-sample CPM04.Counts/normalizedCount/*_normalizedCount.txtIndividual sample normalised count files

Detected miRNAs per Sample — Summary Statistics

Across all 27 samples, the number of detected miRNAs (raw count > 0) was highly consistent, reflecting uniform library quality. Summary statistics are shown below.

StatisticValue
Number of samples27
Mean603.6
Median606.0
Standard deviation20.9
Minimum561
Q1 (25th percentile)589
Q3 (75th percentile)622
Maximum634
IQR33

7. Differential Expression Analysis

DE analysis was performed using DESeq2 (p-value < 0.05, |log₂FC| > 0) for 7 pairwise comparisons. Significant miRNAs were further analysed for GO (Gene Ontology) and KEGG pathway enrichment on predicted target genes. Results are in 05.DE-GO-KEGG/.

Note: The format of each comparison is Test_group vs Control_group (e.g., A vs D means Group A is the test, Group D is the reference/control).

DE Summary — All Comparisons

ComparisonTotal Significant miRNAsUp-regulatedDown-regulated
Group A vs D96↑ 47↓ 49
Group B vs A201↑ 113↓ 88
Group B vs E151↑ 96↓ 55
Group C vs A275↑ 141↓ 134
Group C vs F112↑ 67↓ 45
Group E vs D178↑ 62↓ 116
Group F vs D208↑ 106↓ 102

Representative Figures — A vs D (Group A vs Group D)

The following figures are from the A_vs_D_DE comparison (Group A as test, Group D as reference). This comparison identified 96 significant DE miRNAs (47 up-regulated, 49 down-regulated; p < 0.05, |log₂FC| > 0).

Volcano Plots

Enhanced Volcano Plot — A vs D. Each point represents a miRNA. Red: up-regulated (FC > 0, p < 0.05); Blue: down-regulated (FC < 0, p < 0.05); Grey: not significant. Axes show log₂ fold-change (x) and –log₁₀ p-value (y). Source: A_vs_D_DE/output-enhancedVolcanoPlot.pdf
Interactive Volcano Plot — A vs D. Static preview of the interactive volcano plot. In the full interactive version (Volcano-Plot--A_vs_D--show-gene-names.html), hovering over each point displays the miRNA name, log₂ fold-change, and p-value. Source: A_vs_D_DE/Volcano-Plot--A_vs_D--show-gene-names.html

PCA & Sample Distance

PCA Plot — A vs D. Principal component analysis on variance-stabilised counts (VST). Samples are coloured by group. Source: A_vs_D_DE/output-PCA.pdf
Between-Sample Distance Heatmap — A vs D. Hierarchical clustering of samples based on Euclidean distances from VST data. Source: A_vs_D_DE/output-BetweenSampleDis.pdf

DE Heatmap — Top 50 Genes by Variance

Heatmap of Top 50 Most Variable miRNAs — A vs D. VST-normalised expression of the top 50 miRNAs ranked by expression variance across all samples in this comparison. Rows (miRNAs) and columns (samples) are hierarchically clustered. No p-value filter applied. Source: A_vs_D_DE/output-heatmap-50-top-genes--only-check-expression-variance-no-pvalue-filter-applied.pdf

GO & KEGG Enrichment — A vs D (All Significant miRNA Target Genes)

GO Biological Process Barplot — A vs D. Top enriched Biological Process GO terms for the target genes of all significant DE miRNAs. Bar length = gene count; colour = adjusted p-value. Source: A_vs_D_DE/GO-ALL-TargetGenes/output-BiologicalProcess-barplot.pdf
KEGG Pathway Barplot — A vs D. Top enriched KEGG pathways for target genes of all significant DE miRNAs. Source: A_vs_D_DE/GO-ALL-TargetGenes/output-kegg-barplot.pdf

Output Files per Comparison

FileDescription
output-AnalysisResult.csvFull DE table, all miRNAs, sorted by adjusted p-value
output-AnalysisResult-sig.csvSignificant DE miRNAs (p < 0.05, |log₂FC| > 0)
output-AnalysisResult-sig-upregulated.csvSignificant up-regulated miRNAs
output-AnalysisResult-sig-downregulated.csvSignificant down-regulated miRNAs
output-normalized-count.csvDESeq2 size-factor normalised counts
output-PCA.pdf / output-PCA-data.csvPCA on variance-stabilised data
output-heatmap*.pdfSample distance, gene-sample, and top-gene heatmaps
output-enhancedVolcanoPlot.pdf / Volcano-Plot-*.htmlStatic and interactive volcano plots
output-Pearson-correlation-of-top-2000-genes.pdfPearson correlation heatmap
output-BetweenSampleDis.pdfBetween-sample distance heatmap
GO-ALL-TargetGenes/ GO-UP-TargetGenes/ GO-DOWN-TargetGenes/GO & KEGG enrichment results (all, up-regulated, down-regulated)

8. Methods

8.1 Library Preparation

miRNA-seq libraries were prepared using the Qiagen Small RNA Library Kit. Single-end sequencing was performed on an Illumina platform. Only trimmed R1 reads were used for downstream miRNA analysis.

8.2 Adapter Trimming & Read QC

Adapter trimming was performed using miRDeep2 (mapper.pl). Read quality was assessed using FastQC and aggregated with MultiQC.

8.3 Read Collapsing & Genome Mapping

Trimmed R1 reads were processed with mapper.pl (miRDeep2), which removes reads with non-canonical nucleotides, collapses identical reads, and aligns them to the mouse genome (GRCm39) using Bowtie. Key parameters:

ParameterValueDescription
-e—Input is a FASTQ file
-j—Remove reads with non-canonical nucleotides
-l18Minimum read length after collapsing: 18 bp
-m—Collapse reads before mapping
-o4Maximum number of genomic mapping loci per read
-n—Retain read name information
-pGRCm39 Bowtie indexReference genome Bowtie index

8.4 miRNA Quantification (miRDeep2)

miRNA expression was quantified with miRDeep2.pl using mouse miRBase reference files (GRCm39 coordinates):

ReferenceDescription
Mature miRNAsMus musculus mature miRNA sequences (miRBase)
Close-species miRNAsMature sequences from related rodent species for homology-based detection
Hairpin precursorsMus musculus hairpin precursor sequences (miRBase)
Genome FASTAGRCm39 primary assembly

8.5 Count & CPM Matrix Generation

Raw read counts (column 2) and RPM-normalised values (column 6) were extracted from the miRDeep2 expression file for each sample and merged into cross-sample matrices using a custom R script via full outer join on miRNA ID, with missing values set to 0.

8.6 Differential Expression Analysis (DESeq2)

DE analysis was performed using DESeq2 (R/Bioconductor) with raw counts, design = ~condition. Size-factor normalisation and negative-binomial model fitting applied with DESeq().

Significance thresholds:

Variance-stabilising transformation (VST) was applied for all visualisations (PCA, heatmaps, sample correlation). Plots include volcano plots, heatmaps, PCA, sample distance maps, and p-value histograms.

8.7 GO & KEGG Enrichment Analysis

Significant DE miRNAs were converted to predicted target genes. GO and KEGG enrichment analysis was performed on target genes (full set, up-regulated, and down-regulated subsets) using clusterProfiler (R/Bioconductor). Results are in:

8.8 Software Summary

ToolVersionPurpose
miRDeep2 (mapper.pl)—Adapter trimming
FastQCv0.12.1Read quality control
MultiQCv1.28FastQC report aggregation
Bowtiev1.3.1Read alignment to GRCm39
mapper.pl (miRDeep2)—Read collapsing and genome mapping
miRDeep2.pl—miRNA quantification (known + novel)
R / DESeq2v1.46.0Differential expression analysis
R / clusterProfilerv4.14.4GO & KEGG enrichment analysis

9. Deliverable File Structure

Demo-Project-miRNA-analysis/
├── 00.TrimData/
│ └── 27 × *_trimmed.fq ← miRDeep2-trimmed R1 reads
├── 01.FastqQualityCheck/
│ ├── multiqc_report.html ← FastQC MultiQC report
│ ├── 27 × *_fastqc.html / .zip
│ └── multiqc_data/
├── 02.mapping/
│ ├── 27 × *_collapsed.fa ← collapsed unique reads (mapper.pl)
│ ├── 27 × *_collapsed_vs_genome.arf ← Bowtie alignment in ARF format
│ └── mapper_logs/ ← per-sample mapping logs
├── 02.mapping_logs/ ← per-sample mapping log files
├── 03.mirdeep2/
│ ├── 27 × expression_*.html ← miRDeep2 expression visualisations
│ ├── 27 × result_*.html ← miRDeep2 result summaries
│ ├── 27 × pdfs_*/ ← miRDeep2 hairpin structure PDFs per sample
│ └── 03.mirdeep2_logs/ ← per-sample miRDeep2 logs
├── 04.Counts/
│ ├── rawCount/
│ │ ├── 27 × *_count.txt
│ │ └── rawCount--matrix_with_all_samples.txt ← merged raw count matrix
│ └── normalizedCount/
│ ├── 27 × *_normalizedCount.txt
│ └── normalizedCount--matrix_with_all_samples.txt ← merged CPM matrix
├── 05.DE-GO-KEGG/
│ ├── sampleInfo.csv
│ ├── ReadMe--Demo-Project_DE_analysis_filter_condition.txt
│ ├── A_vs_D.txt / B_vs_A.txt / B_vs_E.txt / C_vs_A.txt / C_vs_F.txt / E_vs_D.txt / F_vs_D.txt
│ ├── A_vs_D_DE/ ← Group A vs Group D
│ │ ├── output-AnalysisResult.csv / -sig.csv / -sig-upregulated.csv / -sig-downregulated.csv
│ │ ├── output-normalized-count.csv, output-PCA*.pdf, output-VolcanoPlot*.pdf
│ │ ├── output-enhancedVolcanoPlot.pdf, output-heatmap*.pdf
│ │ ├── output-BetweenSampleDis.pdf, output-Pearson-correlation*.pdf
│ │ ├── Volcano-Plot--A_vs_D--show-gene-names.html
│ │ └── GO-ALL-TargetGenes/ GO-UP-TargetGenes/ GO-DOWN-TargetGenes/
│ ├── B_vs_A_DE/ ← same structure as above
│ ├── B_vs_E_DE/ ← same structure as above
│ ├── C_vs_A_DE/ ← same structure as above
│ ├── C_vs_F_DE/ ← same structure as above
│ ├── E_vs_D_DE/ ← same structure as above
│ └── F_vs_D_DE/ ← same structure as above
└── mapping.statistics ← per-sample mapping QC summary table
Demo-Project · miRNA-seq QC Report · Admera Health · Generated 2026-03-11