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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

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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

A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

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Report generated on 2021-02-15, 11:21 based on data in: /hps/research1/birney/users/adrien/indigene/analyses/indigene_nanopore_DNA/brain_run2/DNA_analysis/results

General Statistics

Showing ³¹/₃₁ rows and ⁹/₁₅ columns.

Sample Name	M Reads	M Reads Mapped	Error rate	M Non-Primary	M Reads Mapped	% Mapped	% Proper Pairs	% MapQ 0 Reads	M Total seqs	Read Length - Pass (bp)	Read Length - All (bp)	K Reads - Pass	K Reads - All	Mb Bases - Pass	Mb Bases - All
11-1_A3_pycoqc										5815	5805	2343.7	2399.4	14351.1	14666.3
11-1_A3_samtools_flagstat	6.1	6.1
11-1_A3_samtools_stats			15.31%	2.4	2.4	98.7%	0.0%	0.9%	2.4
117-2_C4_pycoqc										5797	5785	3691.9	3772.7	22779.2	23225.0
117-2_C4_samtools_flagstat	9.8	9.7
117-2_C4_samtools_stats			14.41%	3.8	3.7	98.8%	0.0%	0.9%	3.8
131-1_F4_pycoqc										5584	5567	4527.2	4657.1	26951.6	27628.5
131-1_F4_samtools_flagstat	12.7	12.7
134-1_H4_pycoqc										5877	5864	2890.3	2957.5	18300.0	18680.1
134-1_H4_samtools_flagstat	7.8	7.8
134-2_A5_pycoqc										5657	5644	4799.3	4922.5	29866.3	30552.2
134-2_A5_samtools_flagstat	13.5	13.5
4-1_B2_pycoqc										5582	5574	3192.7	3275.2	18834.4	19288.4
4-1_B2_samtools_flagstat	8.3	8.3
4-1_B2_samtools_stats			14.76%	3.3	3.2	98.6%	0.0%	0.9%	3.3
4-2_C2_pycoqc										5819	5808	3737.5	3836.3	22892.4	23449.1
4-2_C2_samtools_flagstat	9.8	9.7
69-1_F3_pycoqc										5456	5442	3000.4	3090.9	17348.5	17823.7
69-1_F3_samtools_flagstat	7.8	7.7
69-1_F3_samtools_stats			15.35%	3.1	3.0	98.6%	0.0%	0.9%	3.1
7-1_E2_pycoqc										5805	5798	3108.8	3178.4	19149.3	19552.8
7-1_E2_samtools_flagstat	8.2	8.1
7-1_E2_samtools_stats			14.76%	3.2	3.1	98.8%	0.0%	0.9%	3.2
7-2_F2_pycoqc										5365	5356	3650.2	3749.6	20538.1	21058.8
7-2_F2_samtools_flagstat	9.4	9.3
7-2_F2_samtools_stats			14.70%	3.7	3.7	98.7%	0.0%	0.9%	3.7
79-2_G3_pycoqc										5600	5582	3284.5	3408.3	19401.5	20060.9
79-2_G3_samtools_flagstat	8.7	8.7
80-1_H3_pycoqc										5389	5376	2285.3	2357.6	13049.7	13428.4
80-1_H3_samtools_flagstat	5.9	5.9
80-1_H3_samtools_stats			15.38%	2.3	2.3	98.7%	0.0%	0.9%	2.4

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Sort	Group	Column	Description	ID	Scale
\|\|	Samtools	M Reads	Total reads in the bam file (millions)	`flagstat_total`	read_count
\|\|	Samtools	M Reads Mapped	Reads Mapped in the bam file (millions)	`mapped_passed`	read_count
\|\|	Samtools	Error rate	Error rate: mismatches (NM) / bases mapped (CIGAR)	`error_rate`	None
\|\|	Samtools	M Non-Primary	Non-primary alignments (millions)	`non-primary_alignments`	read_count
\|\|	Samtools	M Reads Mapped	Reads Mapped in the bam file (millions)	`reads_mapped`	read_count
\|\|	Samtools	% Mapped	% Mapped Reads	`reads_mapped_percent`	None
\|\|	Samtools	% Proper Pairs	% Properly Paired Reads	`reads_properly_paired_percent`	None
\|\|	Samtools	% MapQ 0 Reads	% of Reads that are Ambiguously Placed (MapQ=0)	`reads_MQ0_percent`	None
\|\|	Samtools	M Total seqs	Total sequences in the bam file (millions)	`raw_total_sequences`	read_count
\|\|	pycoQC	Read Length - Pass (bp)	Median Read Length - passing reads (base pairs)	`passed_median_read_length`	median_read_len
\|\|	pycoQC	Read Length - All (bp)	Median Read Length - all reads (base pairs)	`all_median_read_length`	median_read_len
\|\|	pycoQC	K Reads - Pass	Number of reads - passing reads (thousands)	`passed_reads`	long_read_count
\|\|	pycoQC	K Reads - All	Number of reads - all reads (thousands)	`all_reads`	long_read_count
\|\|	pycoQC	Mb Bases - Pass	Number of bases - passing reads (millions of base pairs)	`passed_bases`	base_count
\|\|	pycoQC	Mb Bases - All	Number of bases - all reads (millions of base pairs)	`all_bases`	base_count

Samtools

Samtools is a suite of programs for interacting with high-throughput sequencing data.

Percent Mapped

Alignment metrics from samtools stats; mapped vs. unmapped reads.

For a set of samples that have come from the same multiplexed library, similar numbers of reads for each sample are expected. Large differences in numbers might indicate issues during the library preparation process. Whilst large differences in read numbers may be controlled for in downstream processings (e.g. read count normalisation), you may wish to consider whether the read depths achieved have fallen below recommended levels depending on the applications.

Low alignment rates could indicate contamination of samples (e.g. adapter sequences), low sequencing quality or other artefacts. These can be further investigated in the sequence level QC (e.g. from FastQC).

Alignment metrics

This module parses the output from samtools stats. All numbers in millions.

Samtools Flagstat

This module parses the output from samtools flagstat. All numbers in millions.

Mapped reads per contig

The samtools idxstats tool counts the number of mapped reads per chromosome / contig. Chromosomes with < 0.1% of the total aligned reads are omitted from this plot.

pycoQC

pycoQC computes metrics and generates interactive QC plots for Oxford Nanopore technologies sequencing data

Statistics

Showing ¹²/₁₂ rows and ⁷/₇ columns.

Sample Name	N50 - Pass (bp)	N50 - All (bp)	Median read qual - Pass	Median read qual - All	Active Channels - Pass	Active Channels - All	Run duration (h)
11-1_A3_pycoqc	7481	7475	10.8	10.7	2679	2688	69.8
117-2_C4_pycoqc	7668	7662	11.3	11.3	2731	2737	71.0
131-1_F4_pycoqc	7310	7302	11.3	11.2	2731	2738	71.0
134-1_H4_pycoqc	7868	7862	11.3	11.3	2730	2734	71.0
134-2_A5_pycoqc	7636	7628	11.3	11.2	2732	2737	71.0
4-1_B2_pycoqc	7325	7319	11.1	11.0	2786	2794	70.9
4-2_C2_pycoqc	7731	7724	11.1	11.0	2789	2804	70.9
69-1_F3_pycoqc	7122	7113	10.7	10.7	2680	2694	69.8
7-1_E2_pycoqc	7761	7756	11.1	11.1	2784	2792	70.9
7-2_F2_pycoqc	7194	7187	11.1	11.0	2789	2797	70.9
79-2_G3_pycoqc	7277	7266	10.7	10.6	2681	2694	70.2
80-1_H3_pycoqc	7030	7021	10.7	10.7	2675	2693	69.8

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Sort	Group	Column	Description	ID	Scale
\|\|	pycoQC	N50 - Pass (bp)	N50 - passing reads (base pairs)	`passed_n50`	n50
\|\|	pycoQC	N50 - All (bp)	N50 - all reads (base pairs)	`all_n50`	n50
\|\|	pycoQC	Median read qual - Pass	Median PHRED quality score - passing reads	`passed_median_phred_score`	phred
\|\|	pycoQC	Median read qual - All	Median PHRED quality score - all reads	`all_median_phred_score`	phred
\|\|	pycoQC	Active Channels - Pass	Number of active channels - passing reads	`passed_channels`	channels
\|\|	pycoQC	Active Channels - All	Number of active channels - all reads	`all_channels`	channels
\|\|	pycoQC	Run duration (h)	Run duration (hours)	`all_run_duration`	None

Read / Base counts

Number of sequenced reads / bases passing and failing QC thresholds.

Read length

Distribution of read lengt for all / passed reads.

Quality scores

Distribution of quality scores for all / passed reads.

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General Statistics

General Statistics: Columns

Samtools

Percent Mapped Help

Alignment metrics

Samtools Flagstat

Mapped reads per contig

pycoQC

Statistics

Pycoqc Stats Table: Columns

Read / Base counts

Read length

Quality scores

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Percent Mapped