Toolbox

MultiQC Toolbox

Highlight Samples

Regex mode off

Rename Samples

Click here for bulk input.

Paste two columns of a tab-delimited table here (eg. from Excel).

First column should be the old name, second column the new name.

Regex mode off

Show / Hide Samples

Regex mode off

Export Plots

Images
Data

Aspect ratio

Plot scaling

Download the raw data used to create the plots in this report below:

Format:

Note that additional data was saved in microRNAseq_sample_report_multiqc_report_data when this report was generated.

Choose Plots

If you use plots from MultiQC in a publication or presentation, please cite:

MultiQC: Summarize analysis results for multiple tools and samples in a single report
Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
Bioinformatics (2016)
doi: 10.1093/bioinformatics/btw354
PMID: 27312411

Save Settings

You can save the toolbox settings for this report to the browser.

Load Settings

Choose a saved report profile from the dropdown box below:

About MultiQC

This report was generated using MultiQC, version 1.9

You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/ewels/MultiQC

MultiQC is published in Bioinformatics:

MultiQC: Summarize analysis results for multiple tools and samples in a single report
Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
Bioinformatics (2016)
doi: 10.1093/bioinformatics/btw354
PMID: 27312411

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.

JavaScript Disabled

MultiQC reports use JavaScript for plots and toolbox functions. It looks like you have JavaScript disabled in your web browser. Please note that many of the report functions will not work as intended.

General Statistics

Showing ⁹/₉ rows and ⁴/₁₀ columns.

Sample Name	M Seqs	% Trimmed GC	% Reads PF	No. miRNA	% miRNA	% Dups	% GC	Length	% Failed	% BP Trimmed
CD4_S1	3.2	45.0%	82.2%	695	58.2%	91.5%	50%	51 bp	45%	54.2%
CD4_S2	2.5	47.0%	81.1%	569	31.5%	93.9%	51%	51 bp	36%	58.7%
CD4_S4	3.4	46.0%	81.8%	671	52.8%	92.0%	51%	51 bp	45%	52.6%
NK_S2	3.2	49.0%	45.3%	530	33.2%	95.4%	54%	51 bp	36%	75.4%
NK_S3	3.1	50.0%	81.5%	626	41.1%	93.0%	52%	51 bp	36%	57.8%
NK_S4	6.9	50.0%	69.7%	791	36.6%	93.7%	53%	51 bp	36%	59.0%
monocytes_S2	1.9	48.0%	77.8%	648	42.5%	92.0%	52%	51 bp	36%	59.0%
monocytes_S3	6.1	52.0%	54.2%	778	36.5%	93.3%	55%	51 bp	36%	70.4%
monocytes_S4	4.4	50.0%	85.4%	770	28.5%	92.1%	52%	51 bp	36%	51.4%

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order.

Sort	Group	Column	Description	ID	Scale
\|\|	FastQC	M Seqs	Total Sequences (millions)	`total_sequences`	read_count
\|\|	Trim_Galore	% Trimmed GC	% GC Content After Fastq Trimming by Trim Galore	`trimmed_gcperc`	None
\|\|	Trim_Galore	% Reads PF	% Reads pass various length and quality filters	`percent_pass_filter`	None
\|\|	miRTrace	No. miRNA	Number of different miRNA hairpins detected in each sample	`no_miRNA`	None
\|\|	miRTrace	% miRNA	Percentage of miRNA reads in reads passing filter	`perc_miRNA`	None
\|\|	FastQC	% Dups	% Duplicate Reads	`percent_duplicates`	None
\|\|	FastQC	% GC	Average % GC Content	`percent_gc`	None
\|\|	FastQC	Length	Average Sequence Length (bp)	`avg_sequence_length`	None
\|\|	FastQC	% Failed	Percentage of modules failed in FastQC report (includes those not plotted here)	`percent_fails`	None
\|\|	Trim_Galore	% BP Trimmed	% Total Base Pairs trimmed	`percent_trimmed`	None

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

All samples have sequences of a single length (51bp).

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.

Showing ³/₃ rows and ⁴/₄ columns.

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

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order.

Sort	Column	Description	ID	Scale
\|\|	Higher in group 1	Numbers of differentially expressed miRNAs with higher expression in group 1	`up_deg`	None
\|\|	Higher in group 2	Numbers of differentially expressed miRNAs with higher expression in group 2	`down_deg`	None
\|\|	Not differentially expressed	Numbers of miRNAs that were not differentially expressed between groups 1 and 2	`not_deg`	None
\|\|	Did not pass filter	Numbers of miRNAs that failed to pass filtering because low expression level or outliers	`filtered`	None

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.

Showing ⁵⁰/₅₀ rows and ⁴/₄ columns.

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

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order.

Sort	Column	Description	ID	Scale
\|\|	Gene name	Gene name	`gene_link`	None
\|\|	Mean normalized counts	Mean normalized read counts in both conditions	`baseMean`	None
\|\|	Log2 Fold change	Log2 Fold change	`log2FoldChange`	None
\|\|	False discovery rate	False discovery rate	`padj`	None

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.

Showing ⁵⁰/₅₀ rows and ⁴/₄ columns.

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

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order.

Sort	Column	Description	ID	Scale
\|\|	Gene name	Gene name	`gene_link`	None
\|\|	Mean normalized counts	Mean normalized read counts in both conditions	`baseMean`	None
\|\|	Log2 Fold change	Log2 Fold change	`log2FoldChange`	None
\|\|	False discovery rate	False discovery rate	`padj`	None

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.

Showing ⁵⁰/₅₀ rows and ⁴/₄ columns.

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

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order.

Sort	Column	Description	ID	Scale
\|\|	Gene name	Gene name	`gene_link`	None
\|\|	Mean normalized counts	Mean normalized read counts in both conditions	`baseMean`	None
\|\|	Log2 Fold change	Log2 Fold change	`log2FoldChange`	None
\|\|	False discovery rate	False discovery rate	`padj`	None

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):

Comparison level files

Showing ³/₃ rows and ³/₃ columns.

Comparison(group1_vs_group2)	miRNA DE comparison results	miRNA MA plot	miRNA Scatter plot
CD4_vs_NK	XLSX	JPG	JPG
CD4_vs_monocytes	XLSX	JPG	JPG
monocytes_vs_NK	XLSX	JPG	JPG

Uncheck the tick box to hide columns. Click and drag the handle on the left to change order.

Sort	Group	Column	Description	ID	Scale
\|\|	isomiRs	miRNA DE comparison results	Differential miRNA gene expression results generated by isomiRs	`comparison_isomiRs_results`	None
\|\|	isomiRs	miRNA MA plot	MA plot showing distribution of miRNA expression patterns	`MA_isomiRs_plot`	None
\|\|	isomiRs	miRNA Scatter plot	Scatter plot showing expression levels of miRNAs between two groups	`scatter_isomiRs_plot`	None

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) or Powershell.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.

Toggle navigation Powered by v1.9

microRNAseq_sample_report

MultiQC Toolbox

Apply Highlight Samples

Apply Rename Samples

Apply Show / Hide Samples

Export Plots

Choose Plots

Save Settings

Load Settings

About MultiQC

microRNAseq_sample_report

General Statistics

General Statistics: Columns

FastQC

Sequence Quality Histograms Help

Per Sequence Quality Scores Help

Per Base N Content Help

Sequence Length Distribution

Adapter Content Help

Trim Galore

Filtered Reads

Trimmed Sequence Lengths Help

miRTrace

Read Length Distribution

Contamination Check

miRNA Complexity

miRNA Type Counts

miRNA sample similarities

Similarity matrix of samples

Multidimensional scaling analysis of samples

miRNA heatmap

miRNA Differential Expression

Summary table of miRNAs differential expression

Differential Expression Table: Columns

Scatter plot

MA plot

Top differentially expressed miRNAs in comparison CD4 vs. NK

Top Degs Cd4 Vs Nk: Columns

Top differentially expressed miRNAs in comparison CD4 vs. monocytes

Top Degs Cd4 Vs Monocytes: Columns

Top differentially expressed miRNAs in comparison monocytes vs. NK

Top Degs Monocytes Vs Nk: Columns

Download data

Files concerning all samples

Comparison level files

Comparison Level Files Table: Columns

Instructions to download all files

Software Versions

Workflow Summary

Powered by

v1.9

Highlight Samples

Rename Samples

Show / Hide Samples

Sequence Quality Histograms

Per Sequence Quality Scores

Per Base N Content

Adapter Content

Trimmed Sequence Lengths