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Concept: MIT License

6

Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing data sets. However, as these methods typically require in-depth expertise in Hadoop and Java, they are still out of reach of many bioinformaticians. In order to solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing data sets in a scalable and simple manner. SeqPig scripts use the Hadoop-based distributed scripting engine Apache Pig, which automatically parallelizes and distributes data processing tasks. We demonstrate SeqPig’s scalability over many computing nodes and illustrate its use with example scripts.Availability and Implementation: Available under the open source MIT license at http://sourceforge.net/projects/seqpig/ CONTACT: andre.schumacher@yahoo.com SUPPLEMENTARY INFORMATION: Instructions and examples for SeqPig.

Concepts: PHP, JavaScript, Web server, Python, Scripting language, Lua, MIT License, JQuery

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Amplicon-based next-generation sequencing (NGS) has been widely adopted for genetic variation detection in human and other organisms. Conventional data analysis paradigm includes primer trimming before read mapping. Here we introduce BAMClipper that removes primer sequences after mapping original sequencing reads by soft-clipping SAM/BAM alignments. Mutation detection accuracy was affected by the choice of primer handling approach based on real NGS datasets of 7 human peripheral blood or breast cancer tissue samples with known BRCA1/BRCA2 mutations and >130000 simulated NGS datasets with unique mutations. BAMClipper approach detected a BRCA1 deletion (c.1620_1636del) that was otherwise missed due to edge effect. Simulation showed high false-negative rate when primers were perfectly trimmed as in conventional practice. Among the other 6 samples, variant allele frequencies of 5 BRCA1/BRCA2 mutations (indel or single-nucleotide variants) were diluted by apparently wild-type primer sequences from an overlapping amplicon (17 to 82% under-estimation). BAMClipper was robust in both situations and all 7 mutations were detected. When compared with Cutadapt, BAMClipper was faster and maintained equally high primer removal effectiveness. BAMClipper is implemented in Perl and is available under an open source MIT license at https://github.com/tommyau/bamclipper.

Concepts: DNA, Gene, Genetics, Cancer, Mutation, Evolution, Genetic drift, MIT License