9th Discussion-28 October 2010 - Revision history

149.155.96.6: /* Transcript of Minutes */

2010-11-19T14:05:51Z

Transcript of Minutes

149.155.96.5: /* Transcript of Minutes */

2010-11-19T13:59:56Z

Transcript of Minutes

Simon andrews: /* Illimina adaptor contamination */

2010-11-09T09:02:20Z

Illimina adaptor contamination

BaCh: /* GGCxG motif */

2010-10-28T15:27:02Z

GGCxG motif

BaCh: /* Sequencing bias towards lower GC */

2010-10-28T15:25:44Z

Sequencing bias towards lower GC

BaCh: Two other problems added: GGCxG motif and GC bias

2010-10-28T15:14:06Z

Two other problems added: GGCxG motif and GC bias

99.121.202.190: /* Which software packages are available */

2010-10-28T14:34:13Z

Which software packages are available

99.121.202.190: /* Poor Quality */

2010-10-28T14:29:41Z

Poor Quality

99.121.202.190: /* Illimina adaptor contamination */

2010-10-28T14:29:12Z

Illimina adaptor contamination

Igenomics at 04:36, 28 October 2010

2010-10-28T04:36:46Z

@@ Line 220: / Line 220: @@
 We moved on to discuss contaminating sequences.  A simple QC measure is to look for individual sequences which are overrepresented in the population and to try to match these to known sources of contamination.  Many people write their own scripts for removing these kinds of contaminants.
-One person asked if there was a good list of potential contaminants.  Since there is one included in FastQC it was suggested that this be posted to the wiki so people could see what was in there and add to it if they found their own.
+One person asked if there was a good list of potential contaminants.  Since there is one included in FastQC it was suggested that this be [[Sequence_Contaminant_List|posted to the wiki]] so people could see what was in there and add to it if they found their own.
 In terms of trimming sequences FastX has a trimming option.  SolexaQA can dynamically trim and can plot the results spatially over the area of a flowcell.

← Older revision		Revision as of 13:59, 19 November 2010
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	=Transcript of Minutes=		=Transcript of Minutes=
−	'''~~coming soon~~'''	+
		+	Attendees:
		+
		+	* Bastien Chevreux
		+	* Julie Zhu
		+	* Ben Davies
		+	* Noelia Conservitie
		+	* David Sexton
		+	* Brent Richter
		+	* ?? Hoffmann
		+	* Fran Lewitter
		+	* Joe Anderson
		+	* David LaPoint
		+	* Jeff Broady
		+	* Stuart Levine
		+	* Mirian ??
		+	* Tom Skelly
		+	* Simon Andrews
		+	* Dawei Lin
		+
		+	After an initial run through of the prepared notes for the session it appeared that lots of people had hit the same technical problems with their high throughput sequencing experiments. There seemed to be agreement that that monitoring the quality of raw sequence was important for spotting technical problems and also for evaluating downstream analyses. It was felt that the Bioinfo-core group was in a unique position to see a broad range of data and to get a perspective on quality that most groups would not be able to see.
		+
		+	With regards to the examples which had been posted in advance of the meeting it was felt that there weren't any major types of problem which had been omitted. One comment was that for the examples it would have been useful to tag them with the name of the technology used and the type of experiment to be able to put them in some context.
		+
		+	There was some discussion about whether a control lane was still necessary. Most people who commented said that they still felt it important to have a control on the flowcell, and most were still running a control lane. One group said that they now routinely run without a control lane, but that they occasionally have to rerun the base calling (Bustard) using a specified control lane if they get failed or biased samples on their flowcell. The new Illumina recommendation is to spike PhiX into each lane, and it was pointed out that whilst this provides a positive control for the sequencing it can't be used to construct the base matrices from which the base calls are made. For really biased libraries (above ~75% AT or GC) a dedicated, evenly biased, control is still needed.
		+
		+	One bias which some people have observed related to %GC. The observation was that a higher than expected proportion of reads came from sequences with a lower than average %GC. This didn't seem to be a universal problem so it wasn't clear whether this was a sequencing problem or something which occurred at the library construction stage.
		+
		+	A phenomenon which a few people had seen related to the calling of base positions which very low sequence diversity in the library. These seemed to be poorly handled by the Illumina platform, leading not only to a higher level of miscalls of the biased bases, but to a more general drop in base call quality for a few bases after the biased bases. The suspicion was that this was an artefact of the base calling algorithms rather than an inherent problem of the sequencing chemistry.
		+
		+	We then moved on to talk about the different software packages which people used for assessing the quality of their data. Most people are only running the QC which comes with the sequencing pipeline and don't add external QC verification. Lots of sites don't routinely return any QC data to the end user unless there has actually been an obvious problem. Where QC data is sent to the user it's normally the HTML summary report for the whole flowcell or the various set of plots (IVC, error rates etc) for the individual lanes.
		+
		+	Some groups are running external QC programs. The ones which were mentioned were:
		+
		+	* SolexaQA
		+	* FastX
		+	* ShortReadQA
		+	* FastQC
		+
		+	The question was asked that when people have poor sequence quality do they actually trim their data. The consensus seemed to be that whether or not to do this would depend on the nature of the experiment. Mapping might be improved by keeping as much data as possible and letting the aligners deal with the poor quality, but SNP calls might just get confusing with a large volume of poor data. Some types of experiment (eg bisulfite seq) are very sensitive to miscalls and should definitely be trimmed.
		+
		+	One question which arose was whether anyone has looked at the accuracy of assigned quality scores. If you are mapping against a known reference genome then you could calibrate the actual error rate against the assigned qualities to see if they matched up. A few people said they would be interested to see this, but noone has done if yet.
		+
		+	We moved on to discuss contaminating sequences. A simple QC measure is to look for individual sequences which are overrepresented in the population and to try to match these to known sources of contamination. Many people write their own scripts for removing these kinds of contaminants.
		+
		+	One person asked if there was a good list of potential contaminants. Since there is one included in FastQC it was suggested that this be posted to the wiki so people could see what was in there and add to it if they found their own.
		+
		+	In terms of trimming sequences FastX has a trimming option. SolexaQA can dynamically trim and can plot the results spatially over the area of a flowcell.
		+
		+	TagDust was suggested for trimming partial contaminant sequences from the end of reads.
		+
		+	One suggestion which was made was to look for the enrichment of Kmer sequences. This should spot overrepresented sequences whether or not they are aligned in the original reads. Looking at 5-7mers should give a good impression of any contamination.

← Older revision		Revision as of 09:02, 9 November 2010
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	[[Image:adapterContamination.jpg]]		[[Image:adapterContamination.jpg]]
		+
		+	This kind of adapter contamination can be detected using an analysis of Kmer enrichment in your library. Kmers showing a rise towards the end of the library indicate progressive contamination with adapters.
		+
		+	[[Image:Kmer_profiles.png]]

	=== GGCxG motif ===		=== GGCxG motif ===

← Older revision		Revision as of 15:27, 28 October 2010
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	GGCxG or even GGC motif in the 5' to 3' direction of reads. Simply put: at some places, base calling after a GGCxG or GGC motif is particularly error prone, the number of reads without errors declines markedly. Repeated GGC motifs worsen the situation.		GGCxG or even GGC motif in the 5' to 3' direction of reads. Simply put: at some places, base calling after a GGCxG or GGC motif is particularly error prone, the number of reads without errors declines markedly. Repeated GGC motifs worsen the situation.

		+	See [http://mira-assembler.sourceforge.net/docs/DefinitiveGuideToMIRA.html#sect_sxa_lowlights_GGCxG_motif http://mira-assembler.sourceforge.net/docs/DefinitiveGuideToMIRA.html#sect_sxa_lowlights_GGCxG_motif]
		+
		+	(Will port images to Wiki later)

	=== Sequencing bias towards lower GC ===		=== Sequencing bias towards lower GC ===

@@ Line 163: / Line 163: @@
 === Sequencing bias towards lower GC ===
 =Transcript of Minutes=
 '''coming soon'''

@@ Line 88: / Line 88: @@
 * [http://www-huber.embl.de/users/anders/HTSeq/doc/qa.html HTSeq QC scripts]
 * [http://solexaqa.sourceforge.net/ SolexaQA]
 == Examples ==

@@ Line 97: / Line 97: @@
 [[Image:Gradual quality drop.png]]
-This plot shows a common problem, especially with longer runs, which is that as the run progresses the quality of the calls gradually drops.  Newer chemistry has improved this somewhat, but people are now doing even longer reads than ever.  We'd normally say than when the median quality is dropping to a phred score of ~20 that we'd consider trimming the sequence at that point, since sequence with lower quality than that is likely to cause more problems than it fixes.
+This plot shows a common problem, especially with longer runs, which is that as the run progresses the quality of the calls gradually drops.  Newer chemistry has improved this somewhat, but people are now doing even longer reads than ever.  We'd normally say that when the median quality is dropping to a phred score of ~20 that we'd consider trimming the sequence at that point, since sequence with lower quality than that is likely to cause more problems than it fixes.
 [[Image:Sudden quality drop.png]]

@@ Line 146: / Line 146: @@
 === Illimina adaptor contamination  ===
-Sometime the sequences from Illumina contain partial Illumina adapters' sequencing. If not trim them, they may affect significantly the assembly and mapping programs.
+Sometime the sequences from Illumina contain partial Illumina adapters' sequences. If not trimmed, they may affect significantly the assembly and mapping outcomes .
 Adapter Sequences:
@@ Line 154: / Line 154: @@
 [[Image:adapterContamination.jpg]]
 =Transcript of Minutes=
 '''coming soon'''

← Older revision		Revision as of 04:36, 28 October 2010
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	Sometime the sequences from Illumina contain partial Illumina adapters' sequencing. If not trim them, they may affect significantly the assembly and mapping programs.		Sometime the sequences from Illumina contain partial Illumina adapters' sequencing. If not trim them, they may affect significantly the assembly and mapping programs.
		+
		+	Adapter Sequences:
		+	5' AATGATACGGCGACCACCGA GATCTACACTCTTTCCCTAC ACGACGCTCTTCCGATCT (N) [[AGATCGGAAGAG]]CGGTTCAG CAGGAATGCCGAGACCGATC TCGTATGCCGTCTTCTGCTT G 3'
		+	3' TTACTATGCCGCTGGTGGCT CTAGATGTGAGAAAGGGATG TGCTGC[[GAGAAGGCTAGA]] (N) TCTAGCCTTCTCGCCAAGTC GTCCTTACGGCTCTGGCTAG AGCATACGGCAGAAGACGAA C 5'
		+

	[[Image:adapterContamination.jpg]]		[[Image:adapterContamination.jpg]]