LabSystem Gen, a tool for structuring and analyzing genetic data in histocompatibility laboratories.

Analysis of HLA data involves queries on web portals, whose search parameters are data stored in laboratories' databases. In order to automate these queries, one approach is to structure laboratory data into a database and to develop bioinformatic tools to perform the data mapping. In this context, we developed the LabSystem Gen tool that allows users to create a Laboratory Information System, without programming. Additionally we implemented a framework that provides bioinformatic tools, transparent access to public HLA (human leukocyte antigen) information resources. We demonstrated the LabSystemGen system by implementing BMDdb, which is a LIMS that manages data of recipients and donors of organ transplant.

EpHLA software: a timesaving and accurate tool for improving identification of acceptable mismatches for clinical purposes.

UNLABELLED: The HLAMatchmaker algorithm, which allows the identification of "safe" acceptable mismatches (AMMs) for recipients of solid organ and cell allografts, is rarely used in part due to the difficulty in using it in the current Excel format. The automation of this algorithm may universalize its use to benefit the allocation of allografts. Recently, we have developed a new software called EpHLA, which is the first computer program automating the use of the HLAMatchmaker algorithm. Herein, we present the experimental validation of the EpHLA program by showing the time efficiency and the quality of operation. The same results, obtained by a single antigen bead assay with sera from 10 sensitized patients waiting for kidney transplants, were analyzed either by conventional HLAMatchmaker or by automated EpHLA method. Users testing these two methods were asked to record: (i) time required for completion of the analysis (in minutes); (ii) number of eplets obtained for class I and class II HLA molecules; (iii) categorization of eplets as reactive or non-reactive based on the MFI cutoff value; and (iv) determination of AMMs based on eplets' reactivities. We showed that although both methods had similar accuracy, the automated EpHLA method was over 8 times faster in comparison to the conventional HLAMatchmaker method. In particular the EpHLA software was faster and more reliable but equally accurate as the conventional method to define AMMs for allografts. CONCLUSION: The EpHLA software is an accurate and quick method for the identification of AMMs and thus it may be a very useful tool in the decision-making process of organ allocation for highly sensitized patients as well as in many other applications.