AptaPLEX - A dedicated, multithreaded demultiplexer for HT-SELEX data.

Aptamers, short and synthetic RNA/DNA molecules binding distinct targets with high affinity and specificity, are identified via Systematic Evolution of Ligands by Exponential Enrichment (SELEX), an in vitro procedure that, starting from a pool of random ssDNA/RNA sequences, selects sequences by amplifying target-affine species through a series of selection cycles. This versatile protocol has recently been combined with high throughput sequencing, allowing arbitrary stages of the selection to be sequenced and analyzed in silico. As a prerequisite, these data require extensive preprocessing by means of quality controls, error correction and demultiplexing, all while taking into account the specific design of aptamers. Existing solutions addressing this task are currently present only as integrated components in larger pipelines, limiting their applicability in independent software solutions. Here we present AptaPLEX, a standalone and platform independent demultiplexer specifically designed for HT-SELEX data. Given the multiplexed data from one or multiple HT-SELEX experiments, AptaPLEX extracts and restores aptamers into the original selection cycles by identifying the barcode and primer regions in each read. AptaPLEX is capable of fuzzy matching for both the barcode and primers, and automatically corrects mismatches between forward and reverse reads for paired-end data. Our software provides a rich set of additional features and can easily be integrated into existing analysis automation pipelines on multiple platforms ranging from desktop machines to cloud based solutions.

[1]  Peng Jiang,et al.  MPBind: a Meta-motif-based statistical framework and pipeline to Predict Binding potential of SELEX-derived aptamers , 2014, Bioinform..

[2]  Phuong Dao,et al.  Large scale analysis of the mutational landscape in HT-SELEX improves aptamer discovery , 2015, Nucleic acids research.

[3]  Teresa M. Przytycka,et al.  Identification of sequence-structure RNA binding motifs for SELEX-derived aptamers , 2012, Bioinform..

[4]  A. Kouzani,et al.  Nucleic Acid Aptamer-Guided Cancer Therapeutics and Diagnostics: the Next Generation of Cancer Medicine , 2015, Theranostics.

[5]  Phuong Dao,et al.  AptaGUI—A Graphical User Interface for the Efficient Analysis of HT-SELEX Data , 2015, Molecular therapy. Nucleic acids.

[6]  Teresa M. Przytycka,et al.  AptaCluster - A Method to Cluster HT-SELEX Aptamer Pools and Lessons from Its Application , 2014, RECOMB.

[7]  Tao Li,et al.  Bayexer: an accurate and fast Bayesian demultiplexer for Illumina sequences , 2015, Bioinform..

[8]  Khalid K. Alam,et al.  FASTAptamer: A Bioinformatic Toolkit for High-throughput Sequence Analysis of Combinatorial Selections , 2015, Molecular therapy. Nucleic acids.

[9]  Janet Kelso,et al.  deML: robust demultiplexing of Illumina sequences using a likelihood-based approach , 2014, Bioinform..

[10]  Boris Schling The Boost C++ Libraries , 2011 .

[11]  William H. Thiel,et al.  Analyzing HT-SELEX data with the Galaxy Project tools--A web based bioinformatics platform for biomedical research. , 2016, Methods.

[12]  Vladimir I. Levenshtein,et al.  Binary codes capable of correcting deletions, insertions, and reversals , 1965 .

[13]  Zuben E. Sauna,et al.  Aptamers as a Sensitive Tool to Detect Subtle Modifications in Therapeutic Proteins , 2012, PloS one.