Presentation is loading. Please wait.

Presentation is loading. Please wait.

Cancer Genomics Core Lab

Similar presentations


Presentation on theme: "Cancer Genomics Core Lab"— Presentation transcript:

1 Cancer Genomics Core Lab
Update on CCC next generation sequencing capabilities and precision medicine testing Cancer Genomics Core Lab Co-directors: Lance Miller and Greg Hawkins

2 What is Next Generation DNA Sequencing?
Next Generation (also called Next-Gen) DNA sequencing (NGS) is a system of massive parallel DNA sequencing performed in silico (on chips or glass plates). Capability to sequence a complete human genome in 24 hrs The output from a single sequencing run >1 X 1012 bases

3 Network and pathway analyses
NGS Applications point mutations CNVs WGS exome targeted capture InDels Structural variations Functional effects Network and pathway analyses Integrative analyses Differential expression Transcriptomics RNA-Seq Gene fusions Clinical applications Alternative splicing RNA editing DNA methylation Epigenomics BS-sequencing ChIP-Seq Transcription Factor binding Histone modification Adapted from Shyr and Liu Biological Procedures Online 2013, 15:4

4 Illumina NextSeq 500 (Installed Jan 2015)
Up to 400 million reads (high throughput) Up to 130 million read (mid throughput) Data format: base-space fastq, fasta, BAM, VCF 1 base pair sequencing Run times (11-29 hours) Manual library construction Read lengths: single 1 X 50 to 1 X 150 bp paired up to 2 X 150 bp Capacity: High throughput 1 genome (20-30 X coverage) 8 RNAseq (up to 50 SE million reads) >9 exomes (>30X coverage) Capacity: Mid-throughput 3 exomes (>30X coverage) 3 RNAseq (up to 40 million reads) Data analysis BaseSpace (individual accounts) Off-line: GATK, BWA, Bowtie, Cufflinks Tophat, (lot’s of others)

5 Flow cell output Jan 2016 - v2 chemistry Q30 >90%
million clusters Gbases >150 million clusters >45 Gbases

6 NGS Library Preparation
NGS Workflow NGS Library Preparation Sequencing de-multiplexing of NGS libraries read trimming QC metrics/data filtering base calling BaseSpace (automated) Primary Analysis .fastq files (curated raw reads) Secondary Analysis sequence alignment to reference genome QC metrics/data filtering .bam files (aligned reads) variant calling and filtering (SNPs and InDels) variant annotation sequencing depth and coverage calculations final QC metrics User Implemented Tertiary Analysis .vcf files (variant report) RNAseq analysis ChIPseq analysis

7 BaseSpace Dashboard https://accounts.illumina.com
all users get 1 Tb cloud storage free free applications for data analysis

8 BaseSpace Run Metrics

9 BaseSpace Run Charts

10 BaseSpace Apps

11 Current CGC Applications for NGS
RNAseq whole transcriptome, targeted gene panels: mRNA/microRNA/lncRNA, splice variants, gene fusions, allele specific expression, genetic variants ChIPseq Microbiome 16s ribosomal RNA sequencing whole bacterial genome Exome Sequencing identification of coding variations human, mouse, primate (vervet) Targeted Sequencing custom single gene or panel of genes Methylation Sequencing whole genome (bisulfite) or methylation capture (Methyl binding protein) Whole Genome Sequencing Targeted Panels (MiSeq) predesigned (example: Cancer) custom designed

12 Illumina MiSeq DX (Summer 2016)
1-25 million reads (high throughput) Data format: base-space fastq, fasta, BAM, VCF 1 base pair sequencing Run times (5-24 hours) Manual library construction Read lengths: single 1 X 50 to 1 X 150 bp paired up to 2 X 150 bp Capacity: High throughput 8-28 samples per run (clinical) >96 samples research Type of Samples ChIP-seq Low throughput RNAseq Sequencing panels CLIA Approved Cystic Fibrosis Custom assay kit Data analysis BaseSpace (individual accounts) Off-line: GATK, BWA, Bowtie, Cufflinks Tophat, (lot’s of others)

13 Cancer Screening Panels Available for Clinical Diagnosis
(Next Generation DNA Sequencing) Not all screening panels have the same content Life Technologies Agilent Illumina

14 Sciclone G3 NGS Workstation – Perkin Elmer
480 libraries per week 192 exome captures per week Flexibility to run 8-96 samples per run Intuitive user interface Support for multiple protocols and kits Sequence capture, mRNA-Seq, ChIP-SeqSample indexing normalization NIH S10 or NCBC instrument grant (2016)

15 Contact Information Co-Directors: Lance Miller, Greg Hawkins Staff: Lou Craddock, Wei Cui, Jamie Haywood Analyst: Dr. Jeff Chou Location: Hanes 4026/4028, NRC 311/312 Contact Lab Phone Number:

16 Questions and Discussion


Download ppt "Cancer Genomics Core Lab"

Similar presentations


Ads by Google