Denovo exercise - Revision history

Mick at 10:26, 8 January 2026

2026-01-08T10:26:24Z

← Older revision		Revision as of 12:26, 8 January 2026
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	<p>The left plot shows length-weighted coverage: long contigs contribute more to the histogram. The right plot shows the raw distribution of contig coverage. Typically, most of the assembly will cluster around the expected coverage (e.g. ~60–90×), and shorter contigs will have more variable coverage. The scaffold length plot shows that most of the assembled bases are in relatively long scaffolds.</p>		<p>The left plot shows length-weighted coverage: long contigs contribute more to the histogram. The right plot shows the raw distribution of contig coverage. Typically, most of the assembly will cluster around the expected coverage (e.g. ~60–90×), and shorter contigs will have more variable coverage. The scaffold length plot shows that most of the assembled bases are in relatively long scaffolds.</p>

	<p><b>Q7. Why might some short contigs have much <i>higher</i> coverage than the ~~main~~ assembly?</b></p>		<p><b>Q7. Why might some short contigs have much <i>higher</i> coverage than the rest of the assembly?</b></p>

	<p><b>Q8. Why might some short contigs have much <i>lower</i> coverage than the ~~main~~ assembly?</b></p>		<p><b>Q8. Why might some short contigs have much <i>lower</i> coverage than the rest of the assembly?</b></p>

	<hr>		<hr>

Mick at 10:20, 8 January 2026

2026-01-08T10:20:00Z

← Older revision		Revision as of 12:20, 8 January 2026
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	<h3>Annotation of a prokaryotic genome</h3>		<h3>Annotation of a prokaryotic genome</h3>

	<p>We will annotate genes in <code>ecoli_pacbio.contigs.fasta</code> using <b>prodigal</b>.</p>		<p>We will annotate genes in <code>/home/projects/22126_NGS/exercises/denovo/canu/ecoli_pacbio.contigs.fasta</code> using <b>prodigal</b>.</p>

	<p>Prodigal: [https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-119 prodigal]</p>		<p>Prodigal: [https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-119 prodigal]</p>
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	<pre>		<pre>
	prodigal \		/home/ctools/Prodigal/prodigal \
	-f gff \		-f gff \
	-i [input genome in fasta] \		-i [input genome in fasta] \

Mick at 09:12, 8 January 2026

2026-01-08T09:12:47Z

← Older revision		Revision as of 11:12, 8 January 2026
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	</pre>		</pre>

	<p>Compute assembly statistics using <code>QUAST</code>:</p>		<p>Compute assembly statistics using <code>QUAST</code> - note: quast does not consider contigs smaller than 500bp:</p>

	<pre>		<pre>

Mick at 13:43, 6 January 2026

2026-01-06T13:43:22Z

← Older revision		Revision as of 15:43, 6 January 2026
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	<pre>		<pre>
	scp stud0XX@pupilX.healthtech.dtu.dk:denovo~~/fastqc~~/Vchol-~~001_6_1_sequence_fastqc~~.~~html~~ .		scp stud0XX@pupilX.healthtech.dtu.dk:denovo/Vchol-001.histo.pdf .
	~~scp stud0XX@pupilX.healthtech.dtu.dk:denovo/fastqc/Vchol-001_6_2_sequence_fastqc.html~~ .
	</pre>		</pre>

Mick at 13:41, 6 January 2026

2026-01-06T13:41:40Z

@@ Line 135: / Line 135: @@
 dev.off()
 </pre>
 <p>The plot shows:</p>

Mick at 10:17, 6 January 2026

2026-01-06T10:17:04Z

← Older revision		Revision as of 12:17, 6 January 2026
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	<pre>		<pre>
	scp stud0XX@pupilX:denovo/fastqc/Vchol-001_6_1_sequence_fastqc.html .		scp stud0XX@pupilX.healthtech.dtu.dk:denovo/fastqc/Vchol-001_6_1_sequence_fastqc.html .
	scp stud0XX@pupilX:denovo/fastqc/Vchol-001_6_2_sequence_fastqc.html .		scp stud0XX@pupilX.healthtech.dtu.dk:denovo/fastqc/Vchol-001_6_2_sequence_fastqc.html .
	</pre>		</pre>

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	<pre>		<pre>
	scp stud0XX@pupilX:path/to/best.coverage.pdf .		scp stud0XX@pupilX.healthtech.dtu.dk:path/to/best.coverage.pdf .
	scp stud0XX@pupilX:path/to/scaffold.lengths.pdf .		scp stud0XX@pupilX.healthtech.dtu.dk:path/to/scaffold.lengths.pdf .
	</pre>		</pre>

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	<pre>		<pre>
	scp stud0XX@pupilX:denovo/quast_results/latest/report.html .		scp stud0XX@pupilX.healthtech.dtu.dk:denovo/quast_results/latest/report.html .
	</pre>		</pre>

Mick at 16:00, 5 January 2026

2026-01-05T16:00:51Z

← Older revision		Revision as of 18:00, 5 January 2026
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	<p>View the plots:</p>		<p>View the plots:</p>

			<p><b>Viewing the PDF files:</b></p>

			<p>If you are using <b>MobaXterm</b>, you can open the PDF files directly from the
			left-hand file panel.</p>

			<p>If you are using <b>macOS</b> (or a standard terminal), copy the PDF files to your
			local computer and open them with any PDF viewer. For example:</p>

	<pre>		<pre>
	~~evince~~ best.coverage.pdf &		scp stud0XX@pupilX:path/to/best.coverage.pdf .
	~~evince~~ scaffold.lengths.pdf &		scp stud0XX@pupilX:path/to/scaffold.lengths.pdf .
	</pre>		</pre>

			<p>Replace <code>stud0XX</code> with your student ID and <code>pupilX</code> with the
			compute node you are working on.</p>

	<p>The left plot shows length-weighted coverage: long contigs contribute more to the histogram. The right plot shows the raw distribution of contig coverage. Typically, most of the assembly will cluster around the expected coverage (e.g. ~60–90×), and shorter contigs will have more variable coverage. The scaffold length plot shows that most of the assembled bases are in relatively long scaffolds.</p>		<p>The left plot shows length-weighted coverage: long contigs contribute more to the histogram. The right plot shows the raw distribution of contig coverage. Typically, most of the assembly will cluster around the expected coverage (e.g. ~60–90×), and shorter contigs will have more variable coverage. The scaffold length plot shows that most of the assembled bases are in relatively long scaffolds.</p>

Mick at 14:30, 5 January 2026

2026-01-05T14:30:02Z

← Older revision		Revision as of 16:30, 5 January 2026
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	<pre>		<pre>
	dat = read.table("Vchol-001.histo")		dat <- read.table("Vchol-001.histo")

			pdf("Vchol-001.histo.pdf")
	barplot(dat[,2],		barplot(dat[,2],
	xlim=c(0,150),		xlim = c(0,150),
	ylim=c(0,5e5),		ylim = c(0,5e5),
	ylab="No of kmers",		ylab = "No of kmers",
	xlab="Counts of a k-mer",		xlab = "Counts of a k-mer",
	names.arg=dat[,1],		names.arg = dat[,1],
	cex.names=0.8)		cex.names = 0.8)
	dev.~~print~~(~~"Vchol-001.histo.pdf", device=pdf~~)		dev.off()
	</pre>		</pre>

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	<pre>		<pre>
	jellyfish stats Vchol-001		/home/ctools/jellyfish-2.3.1/bin/jellyfish stats Vchol-001
	</pre>		</pre>

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	<pre>		<pre>
	library(plotrix)		library(plotrix)
	dat = read.table("default_finalt.cov", sep="\t")		dat <- read.table("default_finalt.cov", sep = "\t")

			## ---- Coverage plots (2 panels) ----
			pdf("best.coverage.pdf", width = 10, height = 5)
			par(mfrow = c(1, 2))

	~~par(mfrow=c(1,2))~~
	weighted.hist(w = dat[,2],		weighted.hist(w = dat[,2],
	x = dat[,1],		x = dat[,1],
	breaks = seq(0,100,1),		breaks = seq(0, 100, 1),
	main = "Weighted coverage",		main = "Weighted coverage",
	xlab = "Contig coverage")		xlab = "Contig coverage")

	hist(dat[,1],		hist(dat[,1],
	xlim = c(0,100),		xlim = c(0, 100),
	breaks = seq(0,1000,1),		breaks = seq(0, 1000, 1),
	main = "Raw coverage",		main = "Raw coverage",
	xlab = "Contig coverage")		xlab = "Contig coverage")
	~~dev.print("best.coverage.pdf", device=pdf)~~

	# Scaffold lengths		dev.off()
	par(mfrow=c(1,1))
			## ---- Scaffold lengths (1 panel) ----
			pdf("scaffold.lengths.pdf", width = 7, height = 5)
			par(mfrow = c(1, 1))

	barplot(rev(sort(dat[,2])),		barplot(rev(sort(dat[,2])),
	xlab = "# Scaffold",		xlab = "# Scaffold",
	ylab = "Length",		ylab = "Length",
	main = "Scaffold Lengths")		main = "Scaffold Lengths")
	dev.~~print("scaffold.lengths.pdf", device=pdf)~~
	q(~~save="no"~~)		dev.off()
	</pre>		</pre>

Mick at 14:06, 5 January 2026

2026-01-05T14:06:12Z

← Older revision		Revision as of 16:06, 5 January 2026
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	<h3>Genome size estimation</h3>		<h3>Genome size estimation</h3>

	<p>We will count k-mers in the data. A k-mer is simply a DNA word of length k. We use <b>jellyfish</b> to count 15-mers. We combine counts from forward and reverse-complement strands and then create a histogram. (This may take some time to run)</p>		<p>We will count k-mers in the data. A k-mer is simply a DNA word of length k. We use <b>jellyfish</b> to count 15-mers. We combine counts from forward and reverse-complement strands and then create a histogram. (This may take some time to run so could be good time to practice using "screen")</p>

	<p>Manual: [http://www.cbcb.umd.edu/software/jellyfish/jellyfish-manual.html jellyfish]</p>		<p>Manual: [http://www.cbcb.umd.edu/software/jellyfish/jellyfish-manual.html jellyfish]</p>

Mick at 13:46, 5 January 2026

2026-01-05T13:46:18Z

← Older revision		Revision as of 15:46, 5 January 2026
Line 103:		Line 103:
	<h3>Genome size estimation</h3>		<h3>Genome size estimation</h3>

	<p>We will count k-mers in the data. A k-mer is simply a DNA word of length k. We use <b>jellyfish</b> to count 15-mers. We combine counts from forward and reverse-complement strands and then create a histogram.</p>		<p>We will count k-mers in the data. A k-mer is simply a DNA word of length k. We use <b>jellyfish</b> to count 15-mers. We combine counts from forward and reverse-complement strands and then create a histogram. (This may take some time to run)</p>

	<p>Manual: [http://www.cbcb.umd.edu/software/jellyfish/jellyfish-manual.html jellyfish]</p>		<p>Manual: [http://www.cbcb.umd.edu/software/jellyfish/jellyfish-manual.html jellyfish]</p>