International Mammalian Genome Society

The 16th International Mouse Genome Conference (2002)

Plenary Presentations * Oral Presentations *
Poster Presentations: Complex Genetics and Disease Modifiers * Developmental Genetics * Functional Genomics * Gene Discovery * Genetic Manipulations to Alter Gene Function * Mouse Models: Human Disease and Pharmacogenetics * Sequence Annotation and Comparative Analysis of Genomes *
Attendees * Sponsors * Table of Contents * Photographs * Awards

POSTER 64 - LIMaS, A JAVA-BASED EXPERIMENTAL TRACKING SYSTEM FOR MICROARRAYS

JM Hancock
MRC UK Mouse Genome Centre and Mammalian Genetics Unit

1) Webb SC, 1) Pilicheva K, 2) Attwood A, 2) Gardner P, 2) Brooks T, 1) Pritchard C, 1) Tymowska-Lalanne Z, 1) Underhill P, 1) Strivens MA, 2) Williams D, 2) Freeman T, 1) Greenfield A, 2) Campbell D & 1) Brown SDM
1) Informatics Group, MGU/MGC, MRC Harwell, 2) MRC, HGMP-RC

Microarray analysis enables scientists to detect thousands of genes in a small sample simultaneously and to analyze the expression (upregulated or downregulated) of those genes. One of the problems with microarrays is the huge volume of information produced (typically thousands of data points per array).The development of LIMaS (Laboratory Information Management System for arrays) through a collaborative project between MRC Harwell and the UK Human Genome Mapping Project (HGMP-RC) aims to facilitate efficient storage and retrieval of information at every stage of array production, not just result set acquisition. This is achieved by having a system that tracks the laboratory process and allows users to write and save protocols and parameters for each experiment. For each experiment the user can visualise their array and query by spot. LIMaS has been developed with continual feedback from the laboratory, to ensure the system meets the users’ expectations and requirements.LIMaS is flexible enough to be able to cope with different arrayers and array patterns (cDNA, oligo and Affymetrix). Data from LIMaS can be easily downloaded into other gene expression data repositories such as Array Express and MAXdb from the HGMP. As such, LIMaS is MIAME supportive. Data can be imported into LIMaS through a data import sheet, allowing the user flexibility in data storage and selection of data columns they feel are more important.For more information on LIMaS please visit our website http://www.mgu.har.mrc.ac.uk/ microarray