1. 11 Overview Paracel GeneMatcher2

2. 22 GeneMatcher2 The GeneMatcher system comprises of hardware and software components that significantly accelerate a number of computationally intensive sequence similarity search algorithms. There are two hardware components: –GeneMatcher accelerator –Post-Processor (Blastmachine) Two client intefaces: –Unix command line –Web-based GUI (BioView Workbench)

3. 33 GeneMatcher2 Architecture GeneMatcher2 Blast machine Switch CPU 1CPU 2 CPU 6912... Query #1 (agaggt..) a ga Query #n... Web interface

4. 44 GeneMatcher2 System Massively Parallel Bioinformatics supercomputer Array of ASIC (Application Specific Integrated Circuit) chips combined with state-of-the-art Linux cluster technology Accelerates dynamic programming search algorithms 3,000 to 220,000 processors Thousands of times faster than general purpose computers

5. 55 3 Processor units (6,142 processors per unit) Up to 4 disk drives For database storage ULTRASparc computer GeneMatcher2 Components

6. 66 GeneMatcher2 Algorithms HMM and HMM-Frame –Searches protein or DNA sequence data with domain models –HMM-Frame aligns protein models to DNA with frame shift and optional intron tolerance Profile and Profile-Frame –Position-specific scoring with profile models –Frame shift tolerant protein profile searches against DNA sequence data GeneWise –Aligns protein sequences or HMM against genomic data –Tolerates introns and frame shifts

7. 77 GeneMatcher2 Algorithms cont, Smith-Waterman –Comparison of DNA-DNA, Protein-Protein, Protein-DNA or DNA-DNA through protein –Frame algorithms tolerate frame shifts, unlike BLAST counterparts –Optional intron tolerance for searches of genomic data –Highly sensitive search capacity finds hits BLAST potentially misses –NCBI Blast

8. 88 Blast is an approximation of Smith-Waterman So is FastA, but it's better and has protein fragment searches Approx. may not yield correct results in some situations: –Data with many ambiguities or frameshifts, such as raw ESTs and unfinished genomic sequence –Distantly related sequences –When global alignments are desired –Protein alignment of Sequences with introns (not penalized on GeneMatcher) What about Blast?

9. 99 Comparison of sensitivity and selectivity of various sequence search methods Sensitivity: What proportion of the real hits are reported? (More sensitive means more real hits) Selectivity: What proportion of the reported hits are real? (More selective means less false positives) Why GeneMatcher2 Less False positives More true positives

10. 10 GeneMatcher2 Performance Time-to-completion comparison of original methods and methods on GeneMatcher2 TBLASTX improvement is 20-fold Other methods at least 100-fold improvement Source: Genome Canada Bioinformatics Platform Project NCBI TBLASTX Paracel TBLASTX Decypher TBLASTX WUSTL HMM cluster Decypher HMM FASTA Smith-Waterman GeneMatcher2 SW EBI GeneWise Paracel GeneWIse 376 14 0.1 161316 270 1000 Runtime for an average query Method 0 200 400 600 800 1000 Seconds * * *

11. 11 Load a sequence (or set of sequences) as a query set if it will be used several times Select the appropriate search depending on the query type and database type (only suitable candidates will be displayed on the search forms) Check your form options! Watch the search queue (can raise priority of small jobs if machine is busy) Select a result format Running a search

12. 12 While you can load your own databases, disk space on the post-processor is not infinite! Ask us about maintaining public databases that are not currently available. If you upload a private database. Special files need to be created to use translated database searches such as rframe. You can create private data sets to search against (e.g. Unigene-mouse and Unigene-rat in a data set called Unigene-rodent). These don’t take up any space. Databases

13. 13 Hidden Markov Models THE LAST FAST CAT +++ ++++ ++++ +++ all matches “AST” from LAST “V” from VERY } Multiple sequence alignment (Clustalw or T-coffee) THE LAST FAT CAT THE FAST CAT THE VERY FAST CAT THE FAT CAT Seq 1 Seq 2 Seq 3 Seq 4 Positive examples THE LAST FA T CAT THE FAST CAT THE VERY FAST CAT THE FA T CAT THE LAST FAST CAT orororor or VERY gap gapgapgap Position specific Positive examples THE VAST FAST CAT Query HMM Build Hidden Markov Model GeneMatcher2 THE VAST VERY FAST CAT Query Only nothing, “LAST” or “VERY” in that position

14. 14 Predict introns and exons based on conserved protein domains (e.g Pfam database) Uses HMMs, reverse query/data set relationship holds Unlike genscan or fgenes, you can believe these hits, though they may not be complete where exons don’t contain conserved domains. GeneWise