Background: High-throughput "omics" based data analysis play emerging
roles in life sciences and molecular diagnostics. This emphasizes the urgent need for
user-friendly windows-based software interfaces that could process the diversity of
large tab-delimited raw data files generated by these methods. Depending on the
study, dozens to ... read morehundreds of these data tables are generated. Before the actual
statistical or cluster analysis, these data tables have to be combined and merged to
expression matrices (e.g., in case of gene expression analysis). Gene annotations as
well as information concerning the samples analyzed may be appended, renewed or
extended. Often additional data values shall be computed or certain features must be
filtered out.
Schwager, Christian, Ute Wirkner, Amir Abdollahi, and Peter E.
Huber. "TableButler - a Windows based tool for processing large data tables generated
with high-throughput methods." BMC Bioinformatics 10, no. 1 (12, 2009):
1-9.