MultiQC Report

General Statistics

Showing ¹⁴⁴/₁₄₄ rows and ¹⁵/₁₉ columns.

Sample Name	M Reads	M Reads Mapped	dupInt	% Proper Pairs	Error rate	M Non-Primary	M Reads Mapped	% Mapped	% Proper Pairs	% MapQ 0 Reads	M Total seqs	% Aligned	M Aligned	% BP Trimmed	% Dups	% GC	Length	% Failed	M Seqs
SRR24685698	76.7	76.7	0.00%	84.5%	0.26%	8.1	68.6	100.0%	100.0%	0.5%	68.6	93.5%	32.4
SRR24685698_1														3.7%	90.5%	41%	145 bp	20%	34.7
SRR24685698_2														3.7%	88.5%	41%	144 bp	20%	34.7
SRR24685699	89.5	89.5	0.00%	82.0%	0.31%	11.3	78.2	100.0%	100.0%	0.9%	78.2	92.8%	36.7
SRR24685699_1														3.5%	90.1%	41%	145 bp	20%	39.6
SRR24685699_2														3.5%	88.1%	41%	145 bp	20%	39.6
SRR24685700	77.1	77.1	0.00%	82.6%	0.29%	9.4	67.7	100.0%	100.0%	0.9%	67.7	92.8%	31.9
SRR24685700_1														3.0%	90.5%	41%	146 bp	20%	34.3
SRR24685700_2														3.0%	87.4%	40%	145 bp	20%	34.3
SRR24685701	93.5	93.5	0.00%	84.1%	0.29%	10.2	83.4	100.0%	100.0%	0.6%	83.4	93.1%	39.4
SRR24685701_1														3.1%	91.2%	41%	145 bp	20%	42.3
SRR24685701_2														3.1%	87.8%	41%	145 bp	20%	42.3
SRR24685702	77.8	77.8	0.00%	81.6%	0.27%	10.0	67.8	100.0%	100.0%	0.9%	67.8	92.4%	31.8
SRR24685702_1														3.2%	90.6%	41%	145 bp	20%	34.4
SRR24685702_2														3.2%	87.8%	40%	145 bp	20%	34.4
SRR24685703	87.3	87.3	0.00%	73.0%	0.29%	19.5	67.9	100.0%	100.0%	3.1%	67.9	92.0%	31.9
SRR24685703_1														3.1%	80.0%	43%	145 bp	20%	34.7
SRR24685703_2														3.0%	76.8%	43%	145 bp	20%	34.7
SRR24685704	83.1	83.1	0.00%	76.8%	0.25%	15.7	67.3	100.0%	100.0%	2.5%	67.3	93.1%	31.9
SRR24685704_1														3.1%	81.2%	43%	145 bp	20%	34.3
SRR24685704_2														3.0%	79.4%	43%	145 bp	20%	34.3
SRR24685705	101.9	101.9	0.00%	73.4%	0.29%	22.5	79.4	100.0%	100.0%	3.1%	79.4	92.3%	37.4
SRR24685705_1														2.7%	81.4%	43%	146 bp	20%	40.5
SRR24685705_2														2.7%	78.0%	43%	146 bp	20%	40.5
SRR24685706	81.9	81.9	0.00%	73.9%	0.29%	17.7	64.2	100.0%	100.0%	2.8%	64.2	91.8%	30.3
SRR24685706_1														2.9%	77.6%	43%	145 bp	20%	33.0
SRR24685706_2														3.0%	74.0%	43%	145 bp	20%	33.0
SRR24685707	151.0	151.0	0.00%	78.8%	0.29%	25.9	125.0	100.0%	100.0%	2.1%	125.0	93.1%	59.5
SRR24685707_1														3.0%	81.4%	42%	145 bp	20%	64.0
SRR24685707_2														3.0%	76.6%	43%	145 bp	20%	64.0
SRR24685708	97.1	97.1	0.00%	75.7%	0.26%	19.5	77.6	100.0%	100.0%	2.6%	77.6	92.5%	36.7
SRR24685708_1														3.3%	78.6%	42%	145 bp	20%	39.7
SRR24685708_2														3.4%	75.7%	43%	145 bp	20%	39.7
SRR24685709	83.1	83.1	0.00%	81.6%	0.26%	12.3	70.8	100.0%	100.0%	1.7%	70.8	93.9%	33.9
SRR24685709_1														2.6%	81.1%	42%	146 bp	20%	36.1
SRR24685709_2														2.7%	78.4%	43%	146 bp	20%	36.1
SRR24685710	67.5	67.5	0.00%	80.6%	0.28%	10.5	56.9	100.0%	100.0%	1.9%	56.9	93.5%	27.2
SRR24685710_1														3.4%	79.9%	42%	145 bp	20%	29.1
SRR24685710_2														3.5%	76.5%	43%	144 bp	20%	29.1
SRR24685711	96.5	96.5	0.00%	83.1%	0.22%	11.1	85.3	100.0%	100.0%	0.7%	85.3	92.9%	40.1
SRR24685711_1														3.1%	92.2%	41%	145 bp	20%	43.1
SRR24685711_2														3.1%	90.1%	40%	145 bp	20%	43.1
SRR24685712	105.3	105.3	0.00%	83.5%	0.30%	13.8	91.5	100.0%	100.0%	1.5%	91.5	94.2%	44.0
SRR24685712_1														2.8%	82.7%	42%	145 bp	20%	46.7
SRR24685712_2														2.9%	77.9%	43%	145 bp	20%	46.7
SRR24685713	101.6	101.6	0.00%	81.8%	0.21%	15.1	86.6	100.0%	100.0%	1.6%	86.6	94.1%	41.6
SRR24685713_1														3.9%	79.0%	43%	144 bp	20%	44.2
SRR24685713_2														3.9%	77.2%	43%	144 bp	20%	44.2
SRR24685714	96.4	96.4	0.00%	78.6%	0.26%	16.9	79.5	100.0%	100.0%	2.1%	79.5	93.1%	37.9
SRR24685714_1														2.8%	80.4%	43%	146 bp	20%	40.7
SRR24685714_2														2.8%	76.2%	43%	145 bp	20%	40.7
SRR24685715	95.9	95.9	0.00%	79.9%	0.27%	15.8	80.1	100.0%	100.0%	1.9%	80.1	93.5%	38.3
SRR24685715_1														2.9%	79.3%	43%	146 bp	20%	41.0
SRR24685715_2														2.8%	75.4%	43%	145 bp	20%	41.0
SRR24685716	160.7	160.7	0.00%	77.9%	0.25%	28.8	132.0	100.0%	100.0%	2.2%	132.0	92.9%	62.6
SRR24685716_1														3.2%	85.3%	42%	145 bp	20%	67.4
SRR24685716_2														3.2%	81.7%	43%	145 bp	20%	67.4
SRR24685717	94.1	94.1	0.00%	76.3%	0.28%	18.3	75.8	100.0%	100.0%	2.4%	75.8	92.4%	35.9
SRR24685717_1														3.2%	83.0%	42%	145 bp	20%	38.9
SRR24685717_2														3.3%	78.6%	43%	145 bp	20%	38.9
SRR24685718	92.5	92.5	0.00%	77.4%	0.27%	17.1	75.4	100.0%	100.0%	2.3%	75.4	92.9%	35.8
SRR24685718_1														3.2%	82.6%	42%	145 bp	20%	38.5
SRR24685718_2														3.2%	78.9%	43%	145 bp	20%	38.5
SRR24685719	99.5	99.5	0.00%	76.7%	0.25%	19.0	80.5	100.0%	100.0%	2.4%	80.5	92.5%	38.2
SRR24685719_1														3.4%	79.0%	43%	145 bp	20%	41.3
SRR24685719_2														3.4%	76.1%	43%	145 bp	20%	41.3
SRR24685720	77.9	77.9	0.00%	79.1%	0.27%	13.3	64.6	100.0%	100.0%	2.1%	64.6	93.1%	30.8
SRR24685720_1														2.8%	75.7%	43%	146 bp	20%	33.1
SRR24685720_2														2.8%	73.0%	43%	146 bp	20%	33.1
SRR24685721	86.1	86.1	0.00%	76.4%	0.24%	16.6	69.6	100.0%	99.9%	2.4%	69.6	91.7%	33.0
SRR24685721_1														6.0%	78.3%	43%	143 bp	20%	36.0
SRR24685721_2														4.5%	76.0%	44%	143 bp	20%	36.0
SRR24685722	98.6	98.6	0.00%	84.1%	0.25%	10.5	88.1	100.0%	100.0%	0.5%	88.1	92.9%	41.5
SRR24685722_1														3.0%	91.8%	41%	145 bp	20%	44.7
SRR24685722_2														3.0%	88.4%	40%	145 bp	20%	44.7
SRR24685723	80.0	80.0	0.00%	78.8%	0.23%	13.9	66.1	100.0%	100.0%	2.2%	66.1	93.8%	31.5
SRR24685723_1														2.9%	79.3%	42%	145 bp	20%	33.6
SRR24685723_2														2.9%	77.5%	43%	145 bp	20%	33.6
SRR24685724	87.5	87.5	0.00%	81.0%	0.25%	13.4	74.1	100.0%	100.0%	1.8%	74.1	93.4%	35.4
SRR24685724_1														2.8%	80.4%	42%	145 bp	20%	38.0
SRR24685724_2														2.9%	76.7%	43%	145 bp	20%	38.0
SRR24685725	85.3	85.3	0.00%	77.7%	0.25%	15.6	69.7	100.0%	100.0%	2.3%	69.7	92.6%	33.1
SRR24685725_1														2.4%	80.0%	42%	146 bp	20%	35.8
SRR24685725_2														2.5%	78.1%	43%	146 bp	20%	35.8
SRR24685726	82.4	82.4	0.00%	77.0%	0.30%	15.6	66.8	100.0%	100.0%	2.4%	66.8	93.2%	31.7
SRR24685726_1														3.0%	74.6%	42%	145 bp	20%	34.0
SRR24685726_2														3.1%	72.2%	43%	145 bp	20%	34.0
SRR24685727	150.6	150.6	0.00%	79.4%	0.33%	25.3	125.4	100.0%	100.0%	1.9%	125.4	92.9%	59.8
SRR24685727_1														2.6%	80.1%	42%	146 bp	20%	64.4
SRR24685727_2														2.7%	72.2%	43%	146 bp	20%	64.4
SRR24685728	101.4	101.4	0.00%	77.2%	0.29%	19.1	82.3	100.0%	100.0%	2.3%	82.3	93.2%	39.1
SRR24685728_1														3.1%	76.4%	42%	145 bp	20%	42.0
SRR24685728_2														3.1%	74.8%	43%	145 bp	20%	42.0
SRR24685729	79.7	79.7	0.00%	78.4%	0.53%	12.4	67.4	100.0%	100.0%	1.2%	67.4	91.5%	31.3
SRR24685729_1														4.3%	88.0%	40%	143 bp	20%	34.2
SRR24685729_2														4.3%	85.8%	40%	143 bp	20%	34.2
SRR24685730	83.1	83.1	0.00%	81.9%	0.37%	10.3	72.9	100.0%	100.0%	0.7%	72.9	92.3%	34.0
SRR24685730_1														3.5%	89.2%	41%	145 bp	20%	36.9
SRR24685730_2														3.5%	87.1%	41%	144 bp	20%	36.9
SRR24685731	95.5	95.5	0.00%	83.5%	0.32%	10.6	84.8	100.0%	100.0%	0.6%	84.8	92.9%	39.9
SRR24685731_1														2.9%	91.3%	41%	146 bp	20%	42.9
SRR24685731_2														2.9%	87.9%	40%	145 bp	20%	42.9
SRR24685732	101.2	101.2	0.00%	67.6%	0.26%	26.1	75.1	100.0%	100.0%	3.4%	75.1	90.3%	34.2
SRR24685732_1														3.5%	90.7%	42%	145 bp	20%	37.9
SRR24685732_2														3.5%	89.0%	41%	145 bp	20%	37.9
SRR24685733	114.1	114.1	0.00%	81.9%	0.31%	14.2	99.9	100.0%	100.0%	0.8%	99.9	92.3%	46.7
SRR24685733_1														3.4%	91.8%	40%	145 bp	20%	50.6
SRR24685733_2														3.5%	88.7%	40%	144 bp	20%	50.6
SRR24685734	105.5	105.5	0.00%	81.1%	0.33%	13.7	91.8	100.0%	100.0%	0.8%	91.8	92.1%	42.8
SRR24685734_1														3.9%	90.5%	41%	144 bp	20%	46.5
SRR24685734_2														3.9%	88.6%	41%	144 bp	20%	46.5
SRR24685735	88.1	88.1	0.00%	83.0%	0.30%	10.3	77.8	100.0%	100.0%	0.7%	77.8	92.9%	36.6
SRR24685735_1														3.1%	90.8%	41%	145 bp	20%	39.4
SRR24685735_2														3.2%	87.8%	41%	145 bp	20%	39.4
SRR24685736	88.4	88.4	0.00%	83.4%	0.25%	10.2	78.1	100.0%	100.0%	0.7%	78.1	93.5%	36.8
SRR24685736_1														3.4%	91.5%	41%	145 bp	20%	39.4
SRR24685736_2														3.4%	89.5%	41%	145 bp	20%	39.4
SRR24685737	94.3	94.3	0.00%	80.5%	0.58%	12.8	81.5	100.0%	100.0%	0.9%	81.5	92.0%	38.0
SRR24685737_1														5.4%	88.1%	40%	142 bp	20%	41.3
SRR24685737_2														5.4%	87.1%	40%	142 bp	20%	41.3
SRR24685738	104.8	104.8	0.00%	82.8%	0.34%	12.4	92.4	100.0%	100.0%	0.7%	92.4	92.6%	43.4
SRR24685738_1														3.0%	91.1%	41%	145 bp	20%	46.9
SRR24685738_2														3.0%	87.4%	40%	145 bp	20%	46.9
SRR24685739	141.8	141.8	0.00%	84.6%	0.26%	14.7	127.1	100.0%	100.0%	0.5%	127.1	93.3%	60.0
SRR24685739_1														3.4%	92.4%	41%	145 bp	20%	64.3
SRR24685739_2														3.4%	89.6%	41%	145 bp	20%	64.3
SRR24685740	98.4	98.4	0.00%	81.6%	0.34%	12.7	85.7	100.0%	100.0%	0.9%	85.7	92.4%	40.1
SRR24685740_1														3.5%	91.1%	41%	145 bp	20%	43.4
SRR24685740_2														3.5%	87.6%	41%	145 bp	20%	43.4
SRR24685741	81.2	81.2	0.00%	82.8%	0.35%	9.6	71.6	100.0%	100.0%	0.7%	71.6	92.7%	33.6
SRR24685741_1														4.2%	90.0%	41%	144 bp	20%	36.3
SRR24685741_2														4.1%	87.8%	41%	144 bp	20%	36.3
SRR24685742	87.2	87.2	0.00%	84.7%	0.29%	9.0	78.3	100.0%	100.0%	0.5%	78.3	93.1%	37.0
SRR24685742_1														3.0%	91.2%	41%	145 bp	20%	39.7
SRR24685742_2														3.1%	87.6%	40%	145 bp	20%	39.7
SRR24685743	108.9	108.9	0.00%	82.2%	0.33%	13.4	95.6	100.0%	100.0%	0.8%	95.6	92.4%	44.8
SRR24685743_1														3.0%	91.1%	41%	145 bp	20%	48.5
SRR24685743_2														3.0%	88.2%	40%	145 bp	20%	48.5
SRR24685744	96.3	96.3	0.00%	82.4%	0.32%	11.8	84.5	100.0%	100.0%	0.9%	84.5	92.5%	39.7
SRR24685744_1														2.9%	91.2%	41%	146 bp	20%	42.9
SRR24685744_2														2.9%	85.9%	40%	145 bp	20%	42.9
SRR24685745	108.3	108.3	0.00%	84.3%	0.26%	11.5	96.9	100.0%	100.0%	0.5%	96.9	93.0%	45.7
SRR24685745_1														3.4%	91.2%	41%	145 bp	20%	49.1
SRR24685745_2														3.4%	88.1%	41%	145 bp	20%	49.1

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

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
\|\|	DupRadar	dupInt	Intercept value from DupRadar	`dupRadar_intercept`	None
\|\|	RSeQC	% Proper Pairs	% Reads mapped in proper pairs	`proper_pairs_percent`	None
\|\|	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
\|\|	STAR	% Aligned	% Uniquely mapped reads	`uniquely_mapped_percent`	None
\|\|	STAR	M Aligned	Uniquely mapped reads (millions)	`uniquely_mapped`	read_count
\|\|	Cutadapt	% BP Trimmed	% Total Base Pairs trimmed	`percent_trimmed`	None
\|\|	FastQC (trimmed)	% Dups	% Duplicate Reads	`percent_duplicates`	None
\|\|	FastQC (trimmed)	% GC	Average % GC Content	`percent_gc`	None
\|\|	FastQC (trimmed)	Length	Average Sequence Length (bp)	`avg_sequence_length`	None
\|\|	FastQC (trimmed)	% Failed	Percentage of modules failed in FastQC report (includes those not plotted here)	`percent_fails`	None
\|\|	FastQC (trimmed)	M Seqs	Total Sequences (millions)	`total_sequences`	read_count

STAR_SALMON DESeq2 PCA plot

PCA plot between samples in the experiment. These values are calculated using DESeq2 in the deseq2_qc.r script.

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STAR_SALMON DESeq2 sample similarity

is generated from clustering by Euclidean distances between DESeq2 rlog values for each sample in the deseq2_qc.r script.

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DupRadar

provides duplication rate quality control for RNA-Seq datasets. Highly expressed genes can be expected to have a lot of duplicate reads, but high numbers of duplicates at low read counts can indicate low library complexity with technical duplication. This plot shows the general linear models - a summary of the gene duplication distributions.

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Preseq

Preseq estimates the complexity of a library, showing how many additional unique reads are sequenced for increasing total read count. A shallow curve indicates complexity saturation. The dashed line shows a perfectly complex library where total reads = unique reads.

Complexity curve

Note that the x axis is trimmed at the point where all the datasets show 80% of their maximum y-value, to avoid ridiculous scales.

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RSeQC

RSeQC package provides a number of useful modules that can comprehensively evaluate high throughput RNA-seq data.

Read Distribution

Read Distribution calculates how mapped reads are distributed over genome features.

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Inner Distance

Inner Distance calculates the inner distance (or insert size) between two paired RNA reads. Note that this can be negative if fragments overlap.

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Read Duplication

read_duplication.py calculates how many alignment positions have a certain number of exact duplicates. Note - plot truncated at 500 occurrences and binned.

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Junction Annotation

Junction annotation compares detected splice junctions to a reference gene model. An RNA read can be spliced 2 or more times, each time is called a splicing event.

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Junction Saturation

Junction Saturation counts the number of known splicing junctions that are observed in each dataset. If sequencing depth is sufficient, all (annotated) splice junctions should be rediscovered, resulting in a curve that reaches a plateau. Missing low abundance splice junctions can affect downstream analysis.

Click a line to see the data side by side (as in the original RSeQC plot).

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Infer experiment

Infer experiment counts the percentage of reads and read pairs that match the strandedness of overlapping transcripts. It can be used to infer whether RNA-seq library preps are stranded (sense or antisense).

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Bam Stat

All numbers reported in millions.

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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).

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Alignment metrics

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

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Samtools Flagstat

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

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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.

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STAR

STAR is an ultrafast universal RNA-seq aligner.

Alignment Scores

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Cutadapt

Cutadapt is a tool to find and remove adapter sequences, primers, poly-Atails and other types of unwanted sequence from your high-throughput sequencing reads.

Filtered Reads

This plot shows the number of reads (SE) / pairs (PE) removed by Cutadapt.

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Trimmed Sequence Lengths

This plot shows the number of reads with certain lengths of adapter trimmed.

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.

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FastQC (trimmed)

FastQC (trimmed) This section of the report shows FastQC results after adapter trimming.

Sequence Counts

Sequence counts for each sample. Duplicate read counts are an estimate only.

This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

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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.

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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.

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Per Base Sequence Content

The proportion of each base position for which each of the four normal DNA bases has been called.

To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

To see the data as a line plot, as in the original FastQC graph, click on a sample track.

From the FastQC help:

Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

Click a sample row to see a line plot for that dataset.

Rollover for sample name

Position: -

%T: -

%C: -

%A: -

%G: -

Per Sequence GC Content

The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

From the FastQC help:

This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

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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.

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Sequence Length Distribution

The distribution of fragment sizes (read lengths) found. See the FastQC help

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Sequence Duplication Levels

The relative level of duplication found for every sequence.

From the FastQC Help:

In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

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Overrepresented sequences

The total amount of overrepresented sequences found in each library.

FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as over represented.

Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

From the FastQC Help:

A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

FastQC lists all of the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

96 samples had less than 1% of reads made up of overrepresented sequences

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.

No samples found with any adapter contamination > 0.1%

Status Checks

Status for each FastQC section showing whether results seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

FastQC assigns a status for each section of the report. These give a quick evaluation of whether the results of the analysis seem entirely normal (green), slightly abnormal (orange) or very unusual (red).

It is important to stress that although the analysis results appear to give a pass/fail result, these evaluations must be taken in the context of what you expect from your library. A 'normal' sample as far as FastQC is concerned is random and diverse. Some experiments may be expected to produce libraries which are biased in particular ways. You should treat the summary evaluations therefore as pointers to where you should concentrate your attention and understand why your library may not look random and diverse.

Specific guidance on how to interpret the output of each module can be found in the relevant report section, or in the FastQC help.

In this heatmap, we summarise all of these into a single heatmap for a quick overview. Note that not all FastQC sections have plots in MultiQC reports, but all status checks are shown in this heatmap.

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nf-core/rnaseq Software Versions

are collected at run time from the software output.

Process Name	Software	Version
`CUSTOM_DUMPSOFTWAREVERSIONS`	`python`	`3.9.5`
	`yaml`	`5.4.1`
`DESEQ2_QC_STAR_SALMON`	`bioconductor-deseq2`	`1.28.0`
	`r-base`	`4.0.3`
`DUPRADAR`	`bioconductor-dupradar`	`1.18.0`
	`r-base`	`4.0.2`
`GET_CHROM_SIZES`	`samtools`	`1.1`
`GTF_GENE_FILTER`	`python`	`3.8.3`
`PRESEQ_LCEXTRAP`	`preseq`	`3.1.1`
`RSEM_PREPAREREFERENCE_TRANSCRIPTS`	`rsem`	`1.3.1`
	`star`	`2.7.6a`
`RSEQC_BAMSTAT`	`rseqc`	`3.0.1`
`RSEQC_INFEREXPERIMENT`	`rseqc`	`3.0.1`
`RSEQC_INNERDISTANCE`	`rseqc`	`3.0.1`
`RSEQC_JUNCTIONANNOTATION`	`rseqc`	`3.0.1`
`RSEQC_JUNCTIONSATURATION`	`rseqc`	`3.0.1`
`RSEQC_READDISTRIBUTION`	`rseqc`	`3.0.1`
`RSEQC_READDUPLICATION`	`rseqc`	`3.0.1`
`SALMON_QUANT`	`salmon`	`1.5.2`
`SALMON_SE_GENE`	`bioconductor-summarizedexperiment`	`1.20.0`
	`r-base`	`4.0.3`
`SALMON_TX2GENE`	`python`	`3.8.3`
`SALMON_TXIMPORT`	`bioconductor-tximeta`	`1.8.0`
	`r-base`	`4.0.3`
`SAMPLESHEET_CHECK`	`python`	`3.8.3`
`SAMTOOLS_FLAGSTAT`	`samtools`	`1.13`
`SAMTOOLS_IDXSTATS`	`samtools`	`1.13`
`SAMTOOLS_INDEX`	`samtools`	`1.13`
`SAMTOOLS_SORT`	`samtools`	`1.13`
`SAMTOOLS_STATS`	`samtools`	`1.13`
`STAR_ALIGN`	`star`	`2.6.1d`
`STAR_GENOMEGENERATE`	`star`	`2.6.1d`
`TRIMGALORE`	`cutadapt`	`3.4`
	`trimgalore`	`0.6.7`
`Workflow`	`Nextflow`	`21.04.0`
	`nf-core/rnaseq`	`3.4`

nf-core/rnaseq Workflow Summary

- this information is collected when the pipeline is started.

Core Nextflow options

runName: fabulous_lamarr
containerEngine: singularity
launchDir: /projects/tomato_genome/fnb/dataprocessing/SRP438952
workDir: /projects/tomato_genome/fnb/dataprocessing/SRP438952/work
projectDir: /projects/tomato_genome/fnb/dataprocessing/SRP438952/nf-core-rnaseq-3.4/workflow
userName: mdavi258
profile: singularity
configFiles: /projects/tomato_genome/fnb/dataprocessing/SRP438952/nf-core-rnaseq-3.4/workflow/nextflow.config, /projects/tomato_genome/fnb/dataprocessing/SRP438952/tomato.config

Input/output options

input: SRP438952.csv

Reference genome options

fasta: S_lycopersicum_Jun_2022.fa
gtf: S_lycopersicum_Jun_2022.gtf
gene_bed: S_lycopersicum_Jun_2022.bed

Read trimming options

save_trimmed: true

Alignment options

skip_markduplicates: true

Process skipping options

skip_bigwig: true
skip_stringtie: true
skip_fastqc: true
skip_qualimap: true
skip_biotype_qc: true

Institutional config options

custom_config_base: /projects/tomato_genome/fnb/dataprocessing/SRP438952/nf-core-rnaseq-3.4/workflow/../configs/

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MultiQC Toolbox

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About MultiQC

General Statistics

General Statistics: Columns

STAR_SALMON DESeq2 PCA plot

STAR_SALMON DESeq2 sample similarity

DupRadar

Preseq

Complexity curve

RSeQC

Read Distribution

Inner Distance

Read Duplication

Junction Annotation

Junction Saturation

Infer experiment

Bam Stat

Samtools

Percent Mapped Help

Alignment metrics

Samtools Flagstat

Mapped reads per contig

STAR

Alignment Scores

Cutadapt

Filtered Reads

Trimmed Sequence Lengths Help

FastQC (trimmed)

Sequence Counts Help

Sequence Quality Histograms Help

Per Sequence Quality Scores Help

Per Base Sequence Content Help

Rollover for sample name

Per Sequence GC Content Help

Per Base N Content Help

Sequence Length Distribution

Sequence Duplication Levels Help

Overrepresented sequences Help

Adapter Content Help

Status Checks Help

nf-core/rnaseq Software Versions

nf-core/rnaseq Workflow Summary

v1.10.1

Highlight Samples

Rename Samples

Show / Hide Samples

Percent Mapped

Trimmed Sequence Lengths

Sequence Counts

Sequence Quality Histograms

Per Sequence Quality Scores

Per Base Sequence Content

Per Sequence GC Content

Per Base N Content

Sequence Duplication Levels

Overrepresented sequences

Adapter Content

Status Checks