1. __________________________________________________________________________________________________ Fall 2015GCBA 815 __________________________________________________________________________________________________ Fall 2015GCBA 815 Tools and Algorithms in Bioinformatics GCBA815, Fall 2015 Week15: CLC Genomics Matthew Cserhati, Ph.D. Bioinformatics Programmer (Guda lab) Department of Genetics, Cell Biology and Anatomy University of Nebraska Medical Center __________________________________________________________________________________________________ Fall 2015GCBA 815

2. __________________________________________________________________________________________________ Fall 2015GCBA 815 Introduction A comprehensive and user-friendly analysis package for analyzing, comparing, and visualizing next generation sequencing data Website: http://www.clcbio.com/products/clc- genomics-workbench/http://www.clcbio.com/products/clc- genomics-workbench/ Latest version 8.5.1. Also available campus wide via INBREweb in Virtual Machine  Which we will test in this class

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4. __________________________________________________________________________________________________ Fall 2015GCBA 815 Types of tools Classical Sequence Analysis Tools  Alignments, sequence shuffling, motif search, nucleotide and protein analysis Molecular Biology Tools  Primer design, restriction analysis BLAST  Download databases, BLAST at NCBI, create database NGS Core Tools  QC report, trim reads, read mapping, consensus sequence extraction De Novo sequencing And much, much more! …

5. __________________________________________________________________________________________________ Fall 2015GCBA 815 Description of test files Paired end fastq files  X5: 3.4M reads  X8: 16.6M reads Derived from whole genome Belonging to strains of the same microbial species Goal is whole genome assembly from these fastq files

6. __________________________________________________________________________________________________ Fall 2015GCBA 815 Exercises Import data  Open read data  Reference genomes Quality checks  QC report  trimming Guided assembly De novo assembly Remove duplicate reads ORF prediction Extra: runs with Example data  mRNA secondary structure  Motif search

7. __________________________________________________________________________________________________ Fall 2015GCBA 815 Guided vs. de novo genome assembly Guided  Aligning reads in fastq sequence files to a genome from a relative species  More efficient and precise than de novo alignment  Faster  Variant analysis possible only with guided assembly De novo  Done if lacking a relative species  Results in contigs which must be joined  Can be combined with mapping contigs to genome from relative species  Much slower Similar to putting together jigsaw puzzle with/without similar puzzle template

8. __________________________________________________________________________________________________ Fall 2015GCBA 815 Variant analysis Basic  Germline and somatic variants  Detects any variants observed in reads Fixed ploidy  Germline variants  For known ploidy (microbe => 1)  Discards variants which are due to sequencing error or mapping artefacts Low frequency  Germline and somatic variants  For unknown/mixed ploidy  Discards variants which are due to sequencing error

9. __________________________________________________________________________________________________ Fall 2015GCBA 815 Sample outputs

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13. __________________________________________________________________________________________________ Fall 2015GCBA 815 Thanks for your attention!