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Next-Gen Sequencing Bioinformatics Support GPCL-BAC Rick Jordan, Programmer/Analyst J. Lyons-Weiler, Sci. Director September 26, 2008.

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Presentation on theme: "Next-Gen Sequencing Bioinformatics Support GPCL-BAC Rick Jordan, Programmer/Analyst J. Lyons-Weiler, Sci. Director September 26, 2008."— Presentation transcript:

1 Next-Gen Sequencing Bioinformatics Support GPCL-BAC Rick Jordan, Programmer/Analyst J. Lyons-Weiler, Sci. Director September 26, 2008

2 Process GPCL-BAC Director & Analyst meet w/PI –Discuss Data Analysis Needs & Study Design PI Decides on Use of BAC or “Go it Alone” –“Go It Alone” -> data (.sff files) –“Use the BAC” data analysis $ estimate annotation, assembly, & analysis + data PI reviews Preliminary Research Report w/Analyst After final analysis, PI receives Report & Data Often the Analysis will be tailored to the application

3 de novo Analysis Flowchart Data/Reads exported to data rig 454 GS FLX Image files Sequences Sequence processing dataRunParams. parse Image processing analysisParams. parse Signal processing.sff files 454Runtime Metrics.csv 454QualityFilter Metrics.csv 454BaseCaller Metrics.csv Assembler Analysis & Annotation Assembler GS FLX System GS or Lasergene

4 Image processing

5 Lasergene SeqBuilder Reference sequence e.coli K12

6 Signal Processing

7 de novo Genome Assembly Two software packages currently used: –GS FLX Assembler (Newbler algorithm) Can be used for all experiments –Lasergene (SeqMan Pro) Single-end experiments only

8 GS de novo Assembler Input:.sff files and per-base quality scores Output: Consensus sequence, assembled de novo Main processing steps: –Identify pairwise overlaps between reads –Construct multiple alignments of contigs –Generate consensus basecalls of contigs –Output contig consensus sequences and quality scores, along with ACE file of multiple alignments and assembly metrics files From 454 Sequencing GS-FLX Data Analysis Software Manual, Dec 2007

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10 e.g. Graphic Figure of the Assembly (Lasergene 7.2)

11 GS Reference Mapper Generates the consensus DNA sequence by mapping, or alignment, of the reads to a reference sequence Provides a list of high-confidence mutations (individual bases or blocks of bases that differ between the consensus DNA sequence of the sample and the reference sequence) From 454 Sequencing GS-FLX Data Analysis Software Manual, Dec 2007

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13 Genome Annotation (sequence functional classes) Zuber et al. (2007)

14 Gene annotation with SeqManPro Project

15 e.g. Diagrams Smith et al. (2007)

16 Impacted Pathways # Input # Pat hw ay%Pathway PathwayImpact# GenesGenes corrected RankNameScoreIn Pathwayon Chip in Inputp-value 1Phosphatidylinositol signaling system10.508554467.2730.007995 2ECM-receptor interaction6.746624576.4520.016721 3Wnt signaling pathway6.7311136925.310.005133 4B cell receptor signaling pathway6594476.780.008623 5Melanogenesis5.765864634.6510.023291 6Gap junction5.422764635.2630.023291 7GnRH signaling pathway5.026844684.7620.029813 8Focal adhesion4.95416351403.0670.095078 9Long-term potentiation4.868623494.8390.052339 10Olfactory transduction4.673272217.4070.050233 11Calcium signaling pathway4.64416451313.0490.076528

17 e.g. Pathway view

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19 e.g. COGS table Smith et al. (2007)

20 e.g. Sequencing statistics table Marcy et al. (2007)

21 Base Caller Metrics

22 Quality Filter Metrics

23 Runtime Metrics

24 Quality measures by region TCAATG

25 Read lengths by region TCAATG

26 e.g. Blast results

27 e.g. Predicted nucleotide and protein alignment Raymond et al. (2007)

28 e.g. Predicted protein alignment Raymond et al. (2007)

29 Grant Text Next Generation Sequence Bioinformatics Analysis. The Bioinformatics Analysis Core is sufficiently endowed with software and human resources to conduct the analysis of data from resequencing and de novo sequencing studies. Software acquisitions include the default Genome Sequencer modules and the recently acquired specialized Lasergene 7.2 software by DNA*. One BAC staff member is dedicated to the analysis of long-read NextGen sequencing data and is responsible for generating research reports for each project. Genome Sequencer FLX System Software The FLX System Software includes modules for each stage in the analysis. All raw data are accessible, and the system also offers a variety of third party software packages for niche applications. Data QA/QC The Core uses a variety of data quality control measures including consensus accuracy and quality scores including per base (Q20+) and per genome (%Bases Q20+; the proportion of an assembled genome with base call accuracy of >99%). The Core has also acquired licenses required to execute the full suite of Lasergene applications to round out the core’s Genome Annotation capabilities. In addition to the sequence assembler/SNP discover algorithms in SeqMan Pro, and the visualization and sequence editing modules (SeqBuilder), the Lasergene suite adds the capacity for gene finding (GeneQuest) and protein structure analysis & prediction (Protean). The variety of file types that the core is expected to handle is greatly aided by Laser Genes’s EditSeq and by the much-improved interoperability of SeqMan Pro (which can import.sff,.fna,.fas and.qual files).

30 Research Report Components Tables –Base Call Metrics –Quality Filter Metrics –Run Time Metric Tables –Quality Score per base (Q40+) per genome (%Bases Q40+; the proportion of an assembled genome with base call accuracy of >99%). –Quality Measure Distributions (By region) –Read Length Measure Distributions –Overall Sequence Statistics Tables –Blast tables –COGs Table Figures –Assembly Figures –Alignment Diagrams –Gene Functional Categories Diagrams –Genome View Diagrams –Nucleotide Alignment Diagrams –Predicted Protein Alignment Diagrams –Gene Ontology Functional Class Diagrams/Charts –Pathway Views –COGs Figures Methods Text –Manuscripts –Proposals Letter of Support

31 Application Areas Ancient DNA ChIP-seq/Methylation/Epigenetics Eukaryotic Whole Genome Sequencing Expression tags Genetic variation detection HIV sequencing Metagenomics and Microbial Diversity Mitochondria/viruses/plastids/plasmids Prokaryotic Whole Genome Sequencing Sequence Capture/Target Region Resequencing Small RNAs Somatic variation detection Transcriptome Sequencing Roche 454/GS-FLX Web Site

32 de novo Analysis Flowchart Data/Reads exported to data rig 454 GS FLX Image files Sequences Sequence processing dataRunParams. parse Image processing analysisParams. parse Signal processing.sff files 454Runtime Metrics.csv 454QualityFilter Metrics.csv 454BaseCaller Metrics.csv Assembler Analysis & Annotation Assembler GS FLX System GS or Lasergene

33 Final Service Product Pre-analysis output files –dataRunParams.parse –454 BaseCallerMetrics.csv –454 QualityFilterMetrics.csv –454 RuntimeMetricsAll.csv Post-analysis output files –.sff files (for each region) –Research report (.ppt) –Additional text editing


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