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Biotech / Medical : Ciphergen Biosystems(CIPH): -- Ignore unavailable to you. Want to Upgrade?

To: tuck who wrote (199)	2/3/2004 6:12:06 PM
From: Biomaven	Read Replies (2) \| Respond to of 510

Thanks, tuck. From that site: An important new recent development we have announced publicly is that specifically for our clinical trial-based applications, we have switched our analysis to utilize a higher resolution mass spectrometer for all of our pattern generation. We now employ an ABI Hybrid Pulsar QqTOF instrument (Q-Star) fitted with a Ciphergen SELDI source such that we can use the same protein chip configuration as before. This decision was made after months of thorough evaluation. We based our decision on the following: a. The current configuration of the Ciphergen PBSII and PBCIIc has too low mass resolution and too high mass drift for our specific needs. In our hands, even after extensive external calibration and controls day-to-day, week-to-week and machine-to-machine variance was uncontrolled. In short, we could not run the same sample on the same machine at a later date and have the spectra align correctly. We realize that in the future, this problem may be obviated by newer instrumentation, but at this time, the performance of the Ciphergen PBSII and PBSIIc is unacceptable for routine clinical analysis and testing in our hands. Of course, it is very important to realize that the Ciphergen instrument was originally designed for research use only and not claimed as a clinical diagnostic platform, and we continue to support it and applaud it as a very useful and enabling proteomic discovery tool. b. The tremendous increase in resolution of the Q-Star ( >9000 at m/z 1500) compared to the Ciphergen instrument (~100 to 200) and increase in mass accuracy of the Q-Star (10 ppm) vs. the Ciphergen instrument (1000 ppm) has given us the opportunity to bin data such that the same intensities fall into the same "bucket" every day, every week and every machine. The goal is REPRODUCIBILITY. Peter (no current CIPH position)

To: tuck who wrote (199)	2/29/2004 4:59:33 PM
From: tuck	Read Replies (1) \| Respond to of 510

More from Baggerly's group regarding reproducibility: >>Proteomics. 2003 Sep;3(9):1667-72. A comprehensive approach to the analysis of matrix-assisted laser desorption/ionization-time of flight proteomics spectra from serum samples. Baggerly KA, Morris JS, Wang J, Gold D, Xiao LC, Coombes KR. Department of Biostatistics, UT M.D. Anderson Cancer Center, Houston, TX 77030, USA. kabagg@mdanderson.org For our analysis of the data from the First Annual Proteomics Data Mining Conference, we attempted to discriminate between 24 disease spectra (group A) and 17 normal spectra (group B). First, we processed the raw spectra by (i) correcting for additive sinusoidal noise (periodic on the time scale) affecting most spectra, (ii) correcting for the overall baseline level, (iii) normalizing, (iv) recombining fractions, and (v) using variable-width windows for data reduction. Also, we identified a set of polymeric peaks (at multiples of 180.6 Da) that is present in several normal spectra (B1-B8). After data processing, we found the intensities at the following mass to charge (m/z) values to be useful discriminators: 3077, 12 886 and 74 263. Using these values, we were able to achieve an overall classification accuracy of 38/41 (92.6%). Perfect classification could be achieved by adding two additional peaks, at 2476 and 6955. We identified these values by applying a genetic algorithm to a filtered list of m/z values using Mahalanobis distance between the group means as a fitness function.<< >>Clin Chem. 2003 Oct;49(10):1615-23. Quality control and peak finding for proteomics data collected from nipple aspirate fluid by surface-enhanced laser desorption and ionization. Coombes KR, Fritsche HA Jr, Clarke C, Chen JN, Baggerly KA, Morris JS, Xiao LC, Hung MC, Kuerer HM. Department of Biostatistics, University of Texas M. D. Anderson Cancer Center, 1515 Holcombe Blvd., Box 447, Houston TX 77030, USA. krc@odin.mdacc.tmc.edu BACKGROUND: Recently, researchers have been using mass spectroscopy to study cancer. For use of proteomics spectra in a clinical setting, stringent quality-control procedures will be needed. METHODS: We pooled samples of nipple aspirate fluid from healthy breasts and breasts with cancer to prepare a control sample. Aliquots of the control sample were used on two spots on each of three IMAC ProteinChip arrays (Ciphergen Biosystems, Inc.) on 4 successive days to generate 24 SELDI spectra. In 36 subsequent experiments, the control sample was applied to two spots of each ProteinChip array, and the resulting spectra were analyzed to determine how closely they agreed with the original 24 spectra. RESULTS: We describe novel algorithms that (a) locate peaks in unprocessed proteomics spectra and (b) iteratively combine peak detection with baseline correction. These algorithms detected approximately 200 peaks per spectrum, 68 of which are detected in all 24 original spectra. The peaks were highly correlated across samples. Moreover, we could explain 80% of the variance, using only six principal components. Using a criterion that rejects a chip if the Mahalanobis distance from both control spectra to the center of the six-dimensional principal component space exceeds the 95% confidence limit threshold, we rejected 5 of the 36 chips. CONCLUSIONS: Mahalanobis distance in principal component space provides a method for assessing the reproducibility of proteomics spectra that is robust, effective, easily computed, and statistically sound.<< Cheers, Tuck