Custom bioinformatics applications for analysis and interpretation of experimental data

Almost every lab is different with its own goals. In-house analyses and workflows may qualify for automation to deal with existing pain points such as consistency, reproducibility, processing time and labor cost. We recently developed two tailor-made tools, described below, to eliminate manual steps to a minimum when analyzing a specific type of experimental data.
Donor stem cell transplantation is used for treatment of patients suffering from a life-threatening disease e.g. leukemia. Chimerism testing is used for monitoring stem cell transplantation and determines the percentage of donor cells in a blood or bone marrow sample. Several commercial kits are available to amplify short tandem repeat (STR) sequences in a multiplex PCR followed by capillary electrophoresis. Many laboratories performing the STR based chimerism test calculate donor chimerism manually in MS Excel or even by using a simple calculator, which is very labor intensive and error-prone. QuickChim (https://www.bioinformatica.be/quickchim/v1.0/) is a PHP-based web application that calculates the % donor chimerism from STR analysis data from a posttransplant sample, reference donor and pre-transplant patient sample.
MS-PEP data analyzer (https://bioit.shinyapps.io/PARs/) is a simple and user-friendly R-based (Shiny) web application, based on the MALDIquant and mzR packages, to analyze mass spectrometry data. The tool automatically detects peaks in a spectrum based on an uploaded peak list file and calculates the theoretical fragmentation of a given peptide sequence. Next it matches automatically the detected peaks to the theoretically calculated fragments. Relative intensities of peptide fragments are calculated and can be visualized or exported as an Excel report. The tool is currently used to study peptide cleavage patterns as an approach to investigate serine protease activity as an approach to profile serine protease activities in biological samples.

Authors

Cedric Hermans(1), Mattias Vermeersch(1), Jasper Decuyper(1), Michelle De bruyn(2), Ingrid De Meester(2), Friedel Nollet(3), Paco Hulpiau(1)

Organisations

Bioinformatics Knowledge Center (BiKC), Howest University of Applied Sciences (Hogeschool West-Vlaanderen), Bruges, Belgium (1), Laboratory of Medical Biochemistry, Department of Pharmaceutical Sciences, University of Antwerp, Belgium (2), Laboratoriumgeneeskunde, AZ St-Jan Brugge, Bruges, Belgium (3)

Presenting author

Paco Hulpiau, Lecturer and research coordinator bioinformatics, Howest University of Applied Sciences
paco.hulpiau@howest.be
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