The Solexa machine is a high-throughput machine for genomic sequencing. During a single run of the machine, several lanes are filled with samples that are to be sequenced as part of an experiment. To optimize the use of the hardware, it is best to have all of the lanes used even if the samples in the lanes come from different experiments. Solexa-LIMS is designed to help people allocate experimental samples to different lanes in order maximize the value of each run without incurring additional costs.
When an experimenter logs in to the Solexa LIMS, he sees his experiments, the associated samples, and their status in the data-processing pipeline. Samples may be added to experiments at any time. When a sample is added, it is assigned a sample-identification number from the LIMS system that the experimenter should affix to it prior to handing it off to the lab technician.
The lab technician will either place the sample in temporary storage, or immediately prepare for a run of the Solexa machine. When preparing for a run, the technician will assign samples to the lanes within the LIMS, and then physically do the same in the Solexa machine.
Once the run of the machine is complete, the Solexa data begins flowing through the steps of the data processing pipeline. The LIMS is kept apprised of the status of each processing step the lane goes through. The individual pieces of processing software are controlled by the solexa-pipeline scripts which insert descriptive step metadata into the LIMS as the data is processed.
NOTE: Some provisions exist in the LIMS for tagging samples so that the sequence data may be post-processed/analyzed differently, (even as part of samples from separate experiments), though this feature has not yet been designed/implemented and may be part of a future enhancement to the LIMS and solexa-pipeline.
Use Case illustrating its limitations: Graduate student submits an experiment, gets data from processing of experiment. Billing (see below) should go to the external lab the graduate student belongs to, not the graduate student. Also, when the graduate student leaves the lab, ownership of the experiment and data needs to revert to the lab, or at least be inherited by the lab.