microRNAseq_sample_report
This report includes summaries of data quality, data processing, and snapshots of results for your small RNAseq study. This report should assist you to get a general picture of the study, to spot any irregularities in the sample or data, and to explore the most significant results in differential gene expression. Please consult our small RNAseq report documentation on how to use this report.
If you have any question regarding this report, please contact the Zymo representative who sent you this report.
General Statistics
Showing 9/9 rows and 4/10 columns.Sample Name | M Seqs | % Trimmed GC | % Reads PF | No. miRNA |
---|---|---|---|---|
CD4_S1 | 3.2 | 45.0% | 82.2% | 695 |
CD4_S2 | 2.5 | 47.0% | 81.1% | 569 |
CD4_S4 | 3.4 | 46.0% | 81.8% | 671 |
NK_S2 | 3.2 | 49.0% | 45.3% | 530 |
NK_S3 | 3.1 | 50.0% | 81.5% | 626 |
NK_S4 | 6.9 | 50.0% | 69.7% | 791 |
monocytes_S2 | 1.9 | 48.0% | 77.8% | 648 |
monocytes_S3 | 6.1 | 52.0% | 54.2% | 778 |
monocytes_S4 | 4.4 | 50.0% | 85.4% | 770 |
FastQC
FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.
Sequence Quality Histograms
The mean quality value across each base position in the read.
To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).
Taken from the FastQC help:
The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.
Per Sequence Quality Scores
The number of reads with average quality scores. Shows if a subset of reads has poor quality.
From the FastQC help:
The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.
Per Base N Content
The percentage of base calls at each position for which an N
was called.
From the FastQC help:
If a sequencer is unable to make a base call with sufficient confidence then it will
normally substitute an N
rather than a conventional base call. This graph shows the
percentage of base calls at each position for which an N
was called.
It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.
Sequence Length Distribution
Adapter Content
The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.
Note that only samples with ≥ 0.1% adapter contamination are shown.
There may be several lines per sample, as one is shown for each adapter detected in the file.
From the FastQC Help:
The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.
Trim Galore
Trim Galore is a wrapper around Cutadapt and FastQC to consistently apply adpater and quality trimming to FastQ files.
Filtered Reads
This plot shows the number of reads (SE) / pairs (PE) removed by Trim Galore.
Read filtering criteria such as minimum and maximum read length can be found in Workflow Summary section.
Trimmed Sequence Lengths
This plot shows the number of reads with certain lengths of adapter trimmed. Quality trimmed and hard trimmed sequences are not included.
Obs/Exp shows the raw counts divided by the number expected due to sequencing errors. A defined peak may be related to adapter length. See the cutadapt documentation for more information on how these numbers are generated.
miRTrace
miRTrace is a quality control software for small RNA sequencing data developed by Friedländer lab (KTH, Sweden).
Read Length Distribution
Contamination Check
miRNA Complexity
miRNA Type Counts
The following bargraph provides an estimate of miRNA content in each sample. Reads were mapped to RNA reference sequences with Bowtie, and subsequent quantification was completed with miRTop and isomiRs.
miRNA sample similarities
The following sample similarities plots were generated from only miRNA transcript data using isomiRs.
Similarity matrix of samples
The similarities (Pearson correlation coefficient) between samples are visualized here in the form of heatmap. Larger values indicate higher similarity between samples. The similarities were calculated using Log2 values of normalized read counts of all mature miRNAs using isomiRs.
Multidimensional scaling analysis of samples
Multidimensional scaling was conducted to visualize the distance/similarity between samples.
miRNA heatmap
The following heatmap was generated from only miRNA data using isomiRs.
Normalized read counts of top miRNAs with highest variance, calculated using isomiRs. Values plotted in Log2 scale after centering per miRNA. A static version of this figure can be download in the Download data section.
miRNA Differential Expression
isomiRs The following differential expression analysis was generated using only miRNA data with isomiRs.
Summary table of miRNAs differential expression
General statistics of differentially expressed miRNAs in pairwise comparisons. miRNAs with adjusted p-values smaller than 0.05 were considered differentially expressed.
Comparison(group1_vs_group2) | Higher in group 1 | Higher in group 2 | Not differentially expressed | Did not pass filter |
---|---|---|---|---|
CD4_vs_NK | 43 | 27 | 344 | 238 |
CD4_vs_monocytes | 73 | 71 | 270 | 238 |
monocytes_vs_NK | 51 | 50 | 339 | 212 |
Scatter plot
Scatter plot is a simple and straightforward way to visualize differential gene expression results. Expression levels of miRNAs in one group are shown on X-axis while those in other are shown on Y-axis.
Red dots represent differentially expressed miRNAs (adjusted p-values<0.05). Grey dots represent non-differentially expressed miRNAs.
MA plot
MA plot is a type of visualization of differential gene expression results often used in publications. Mean expression levels are shown on X-axis while Log2 of fold changes are shown on Y-axis.
Red dots represent differentially expressed miRNAs (adjusted p-values<0.05). Grey dots represent non-differentially expressed miRNAs. Shrinkage of effect size was carried out using the 'ashr' method in DESeq2
Top differentially expressed miRNAs in comparison CD4 vs. NK
Top 50 differentially expressed miRNAs, ranked by FDR, in comparison CD4 vs. NK. Full isomiRs results can be downloaded in the Download data section.
miRNAs with positive Log2 fold changes have higher expression in CD4. miRNAs with negative Log2 fold changes have higher expression in NK.
Rank | Gene name | Mean normalized counts | Log2 Fold change | False discovery rate |
---|---|---|---|---|
1 | hsa-miR-125a-5p | 1733 | 6.85 | 1.7e-42 |
2 | hsa-miR-99b-5p | 234 | 5.38 | 1.0e-20 |
3 | hsa-miR-181a-2-3p | 2718 | -4.08 | 2.0e-20 |
4 | hsa-miR-152-3p | 132 | -3.96 | 2.4e-17 |
5 | hsa-miR-4772-5p | 74 | -5.39 | 1.7e-15 |
6 | hsa-miR-99a-5p | 70 | 5.63 | 1.3e-13 |
7 | hsa-miR-125b-5p | 114 | 5.45 | 1.4e-12 |
8 | hsa-miR-338-3p | 277 | -3.66 | 5.8e-12 |
9 | hsa-miR-181b-5p | 4918 | -2.72 | 8.1e-12 |
10 | hsa-miR-92b-3p | 168 | 3.56 | 9.9e-12 |
11 | hsa-miR-21-3p | 2182 | 2.65 | 1.4e-11 |
12 | hsa-miR-148a-3p | 2843 | 2.94 | 2.1e-08 |
13 | hsa-let-7e-5p | 62 | 3.67 | 8.8e-08 |
14 | hsa-miR-151a-3p | 692 | 2.31 | 3.5e-07 |
15 | hsa-miR-335-3p | 32 | 3.48 | 7.7e-07 |
16 | hsa-miR-150-3p | 225 | 2.26 | 1.1e-06 |
17 | hsa-miR-151b | 39 | 3.36 | 1.3e-06 |
18 | hsa-miR-4772-3p | 36 | -5.26 | 1.3e-06 |
19 | hsa-miR-29a-3p | 7279 | 2.41 | 1.3e-06 |
20 | hsa-miR-181a-5p | 145539 | -2.33 | 1.7e-06 |
21 | hsa-miR-873-3p | 28 | -7.55 | 1.7e-06 |
22 | hsa-miR-17-3p | 100 | 2.05 | 3.7e-06 |
23 | hsa-miR-101-3p | 10578 | 2.30 | 9.9e-06 |
24 | hsa-miR-340-5p | 1762 | -1.72 | 1.0e-05 |
25 | hsa-miR-486-5p | 656 | 3.62 | 2.2e-05 |
26 | hsa-miR-335-5p | 77 | 2.96 | 2.8e-05 |
27 | hsa-miR-361-3p | 1187 | 1.62 | 3.6e-05 |
28 | hsa-miR-92a-3p | 70835 | 2.12 | 5.1e-05 |
29 | hsa-miR-125b-2-3p | 19 | 7.02 | 9.0e-05 |
30 | hsa-let-7c-5p | 93 | 3.11 | 1.1e-04 |
31 | hsa-miR-132-3p | 114 | -2.30 | 1.3e-04 |
32 | hsa-miR-20a-5p | 457 | 1.56 | 1.4e-04 |
33 | hsa-miR-26a-5p | 88387 | 1.68 | 1.4e-04 |
34 | hsa-miR-29c-3p | 2107 | 2.24 | 1.6e-04 |
35 | hsa-let-7g-5p | 26334 | 1.48 | 2.1e-04 |
36 | hsa-miR-193b-3p | 12 | 5.19 | 2.1e-04 |
37 | hsa-miR-150-5p | 51634 | 2.37 | 3.0e-04 |
38 | hsa-miR-21-5p | 54255 | 1.66 | 4.9e-04 |
39 | hsa-miR-153-3p | 13 | 6.44 | 5.2e-04 |
40 | hsa-miR-31-5p | 387 | 3.33 | 5.2e-04 |
41 | hsa-miR-223-3p | 3529 | -2.53 | 6.4e-04 |
42 | hsa-miR-16-2-3p | 249 | 1.54 | 9.4e-04 |
43 | hsa-miR-22-3p | 27319 | -1.76 | 1.3e-03 |
44 | hsa-miR-155-5p | 1072 | 1.56 | 1.7e-03 |
45 | hsa-miR-23b-3p | 109 | -2.23 | 1.8e-03 |
46 | hsa-miR-101-5p | 34 | 2.23 | 1.8e-03 |
47 | hsa-miR-338-5p | 14 | -5.59 | 1.9e-03 |
48 | hsa-miR-20b-5p | 64 | -2.11 | 4.2e-03 |
49 | hsa-miR-29b-3p | 320 | 2.05 | 4.2e-03 |
50 | hsa-miR-148b-3p | 928 | -1.45 | 6.6e-03 |
Top differentially expressed miRNAs in comparison CD4 vs. monocytes
Top 50 differentially expressed miRNAs, ranked by FDR, in comparison CD4 vs. monocytes. Full isomiRs results can be downloaded in the Download data section.
miRNAs with positive Log2 fold changes have higher expression in CD4. miRNAs with negative Log2 fold changes have higher expression in monocytes.
Rank | Gene name | Mean normalized counts | Log2 Fold change | False discovery rate |
---|---|---|---|---|
1 | hsa-miR-361-3p | 1187 | 5.90 | 1.8e-106 |
2 | hsa-miR-150-5p | 51634 | 10.04 | 4.3e-105 |
3 | hsa-miR-192-5p | 4454 | 4.82 | 1.9e-72 |
4 | hsa-miR-340-5p | 1762 | -4.48 | 9.3e-66 |
5 | hsa-miR-342-5p | 301 | 5.91 | 1.3e-60 |
6 | hsa-miR-125a-5p | 1733 | 8.08 | 1.3e-60 |
7 | hsa-miR-29a-3p | 7279 | 5.57 | 1.9e-47 |
8 | hsa-miR-146b-3p | 611 | 6.23 | 1.2e-45 |
9 | hsa-miR-150-3p | 225 | 8.52 | 7.8e-36 |
10 | hsa-miR-141-3p | 407 | 5.26 | 6.3e-35 |
11 | hsa-miR-223-3p | 3529 | -6.50 | 1.5e-32 |
12 | hsa-miR-146b-5p | 28609 | 5.03 | 4.8e-32 |
13 | hsa-miR-99b-5p | 234 | 6.16 | 1.7e-29 |
14 | hsa-miR-194-5p | 215 | 4.77 | 1.4e-27 |
15 | hsa-let-7g-5p | 26334 | 2.68 | 2.2e-22 |
16 | hsa-miR-342-3p | 4870 | 4.32 | 1.1e-20 |
17 | hsa-miR-10a-5p | 4887 | 4.11 | 2.3e-20 |
18 | hsa-miR-31-5p | 387 | 10.53 | 3.6e-20 |
19 | hsa-miR-874-3p | 77 | 5.03 | 9.7e-20 |
20 | hsa-miR-29c-3p | 2107 | 4.11 | 3.9e-19 |
21 | hsa-miR-92b-3p | 168 | 4.29 | 8.2e-19 |
22 | hsa-miR-301a-3p | 370 | -3.06 | 2.4e-17 |
23 | hsa-miR-99a-5p | 70 | 5.54 | 3.8e-17 |
24 | hsa-miR-16-2-3p | 249 | 2.69 | 2.3e-16 |
25 | hsa-miR-582-3p | 88 | -5.30 | 1.3e-15 |
26 | hsa-miR-142-5p | 87345 | 3.18 | 4.5e-14 |
27 | hsa-miR-29b-3p | 320 | 3.75 | 1.1e-12 |
28 | hsa-miR-125b-5p | 114 | 4.93 | 1.3e-12 |
29 | hsa-miR-155-5p | 1072 | 2.50 | 2.8e-12 |
30 | hsa-miR-148b-3p | 928 | -2.46 | 4.4e-12 |
31 | hsa-miR-151b | 39 | 7.38 | 5.7e-12 |
32 | hsa-let-7e-5p | 62 | 4.21 | 1.0e-11 |
33 | hsa-miR-146a-5p | 4025 | 2.86 | 1.3e-11 |
34 | hsa-miR-326 | 106 | -3.80 | 2.8e-11 |
35 | hsa-miR-32-5p | 527 | 4.19 | 3.3e-11 |
36 | hsa-miR-582-5p | 69 | -5.01 | 5.7e-11 |
37 | hsa-miR-26a-5p | 88387 | 2.29 | 6.5e-11 |
38 | hsa-miR-500a-3p | 327 | -4.02 | 7.4e-11 |
39 | hsa-miR-301b-3p | 65 | -4.17 | 1.4e-10 |
40 | hsa-miR-186-5p | 11826 | 1.60 | 1.1e-09 |
41 | hsa-miR-199b-5p | 119 | -5.28 | 1.6e-09 |
42 | hsa-miR-363-3p | 1831 | 2.31 | 3.5e-09 |
43 | hsa-miR-101-3p | 10578 | 2.69 | 7.8e-09 |
44 | hsa-miR-1249-3p | 27 | -8.33 | 8.3e-09 |
45 | hsa-miR-6503-3p | 30 | -8.58 | 1.2e-08 |
46 | hsa-miR-143-3p | 286 | -5.05 | 4.6e-08 |
47 | hsa-miR-23b-3p | 109 | -3.12 | 4.9e-08 |
48 | hsa-miR-424-5p | 73 | -5.15 | 5.5e-08 |
49 | hsa-miR-215-5p | 25 | 4.41 | 6.4e-08 |
50 | hsa-miR-223-5p | 95 | -5.51 | 1.5e-07 |
Top differentially expressed miRNAs in comparison monocytes vs. NK
Top 50 differentially expressed miRNAs, ranked by FDR, in comparison monocytes vs. NK. Full isomiRs results can be downloaded in the Download data section.
miRNAs with positive Log2 fold changes have higher expression in monocytes. miRNAs with negative Log2 fold changes have higher expression in NK.
Rank | Gene name | Mean normalized counts | Log2 Fold change | False discovery rate |
---|---|---|---|---|
1 | hsa-miR-150-5p | 51634 | -7.67 | 1.7e-58 |
2 | hsa-miR-361-3p | 1187 | -4.28 | 1.1e-50 |
3 | hsa-miR-181a-2-3p | 2718 | -5.34 | 4.6e-38 |
4 | hsa-miR-342-5p | 301 | -4.78 | 7.7e-37 |
5 | hsa-miR-21-3p | 2182 | 4.22 | 6.9e-36 |
6 | hsa-miR-146b-3p | 611 | -5.52 | 1.3e-34 |
7 | hsa-miR-192-5p | 4454 | -3.47 | 1.1e-33 |
8 | hsa-miR-10a-5p | 4887 | -5.10 | 4.8e-33 |
9 | hsa-miR-146b-5p | 28609 | -4.78 | 2.2e-28 |
10 | hsa-miR-363-3p | 1831 | -3.65 | 2.0e-27 |
11 | hsa-miR-340-5p | 1762 | 2.76 | 3.9e-22 |
12 | hsa-miR-150-3p | 225 | -6.26 | 4.2e-18 |
13 | hsa-miR-582-3p | 88 | 6.93 | 1.4e-16 |
14 | hsa-miR-301a-3p | 370 | 3.02 | 1.4e-16 |
15 | hsa-miR-342-3p | 4870 | -3.89 | 3.3e-16 |
16 | hsa-miR-181b-5p | 4918 | -2.97 | 4.4e-15 |
17 | hsa-miR-181a-5p | 145539 | -3.22 | 1.1e-14 |
18 | hsa-miR-152-3p | 132 | -3.25 | 6.5e-14 |
19 | hsa-miR-141-3p | 407 | -3.54 | 6.5e-14 |
20 | hsa-miR-29a-3p | 7279 | -3.16 | 5.7e-13 |
21 | hsa-miR-582-5p | 69 | 6.36 | 6.8e-13 |
22 | hsa-miR-194-5p | 215 | -3.41 | 1.9e-12 |
23 | hsa-miR-4772-5p | 74 | -9.81 | 2.0e-12 |
24 | hsa-miR-21-5p | 54255 | 2.50 | 5.6e-12 |
25 | hsa-miR-223-3p | 3529 | 3.96 | 2.8e-11 |
26 | hsa-miR-199b-5p | 119 | 5.88 | 6.6e-11 |
27 | hsa-miR-31-5p | 387 | -7.20 | 4.5e-09 |
28 | hsa-miR-301b-3p | 65 | 3.74 | 6.2e-09 |
29 | hsa-miR-424-5p | 73 | 5.54 | 1.2e-08 |
30 | hsa-miR-4772-3p | 36 | -8.77 | 1.7e-08 |
31 | hsa-miR-873-3p | 28 | -8.47 | 1.8e-08 |
32 | hsa-miR-345-5p | 287 | 3.42 | 2.0e-08 |
33 | hsa-miR-874-3p | 77 | -3.45 | 4.1e-08 |
34 | hsa-miR-6503-3p | 30 | 5.92 | 9.2e-08 |
35 | hsa-miR-27a-5p | 104 | 3.31 | 5.2e-07 |
36 | hsa-miR-146a-5p | 4025 | -2.31 | 7.7e-07 |
37 | hsa-miR-1249-3p | 27 | 3.80 | 7.8e-07 |
38 | hsa-miR-574-3p | 52 | 5.17 | 3.7e-06 |
39 | hsa-miR-450b-5p | 22 | 5.43 | 4.0e-06 |
40 | hsa-miR-18a-5p | 105 | 3.88 | 5.5e-06 |
41 | hsa-miR-873-5p | 210 | -11.35 | 1.3e-05 |
42 | hsa-miR-652-3p | 254 | 1.86 | 1.3e-05 |
43 | hsa-miR-28-5p | 1425 | -1.98 | 2.1e-05 |
44 | hsa-miR-142-5p | 87345 | -2.14 | 2.3e-05 |
45 | hsa-miR-132-3p | 114 | -2.35 | 2.5e-05 |
46 | hsa-miR-186-5p | 11826 | -1.33 | 2.6e-05 |
47 | hsa-miR-148a-3p | 2843 | 2.35 | 3.0e-05 |
48 | hsa-miR-20b-5p | 64 | -2.55 | 4.1e-05 |
49 | hsa-miR-450a-5p | 17 | 5.30 | 1.0e-04 |
50 | hsa-miR-1468-5p | 21 | -3.53 | 1.4e-04 |
Download data
This section contains links to download your original data, and data and/or images generated by various bioinformatics tools. There may be files for each sample, files for all samples, and files for group comparisons. To download individual files, click on the corresponding links. There are also instructions at the bottom of the this section if you want to download everything in batch.
Links in this section expire after 70 days. If you want to download files after that, please contact us.
Files concerning all samples
These files provide an overview of all samples (some of these are already displayed interactively for you in sections above):- Raw read counts of miRNAs
- Normalized read counts of miRNAs
- miRNA MDS plot of samples
- miRNA similarity matrix of samples
- Heatmap of expression of top miRNAs
Comparison level files
Instructions to download all files
- Download a script to download all files. We assume it is in your Downloads folder.
- Find and open Terminal(Mac/Linux) or Windows Powershell(Windows).
- Type
cd ~/Downloads
and Enter. (If your download folder is different, please change accordingly) - Copy and Paste
bash download_links.ps1
(Mac/Linux) orPowershell.exe -ExecutionPolicy Bypass -File .\download_links.ps1
(Windows) and Enter.
Software Versions
Software versions are collected at run time from the software output. This pipeline is adapted from nf-core smRNAseq pipeline.
- smrnaseq pipeline
- v2.2.0
- Nextflow
- v23.10.1
- R
- v4.0.5
- FastQC
- v0.11.9
- Trim Galore!
- v0.6.6
- Bowtie
- v1.3.0
- Samtools
- v1.16.1
- FASTX
- v0.0.14
- miRTrace
- v1.0.1
- rsem
- v1.2.28
- tximport
- v1.18.0
- mirtop
- v0.4.23
- isomiRs
- v1.18.1
- DESeq2
- v1.30.1
Workflow Summary
This section summarizes important parameters used in the pipeline. They were collected when the pipeline was started.
- Genome
- GRCh38
- Protocol
- zymo
- Downsampling cutoff
- None
- Min Trimmed Length
- 18
- Max Trimmed Length
- None
- isomiRs FDR cutoff
- 0.05
- isomiRs Log2FC cutoff
- 0.585
- Trim 5' R1
- 1
- Trim 3' R1
- 0
- 3' adapter
- TGGAATTCTCGGGTGCCAAGG
Report generated on 2025-09-29, 14:08.