Professor Alan Christoffels was awarded the Human Genome Organisation (HUGO)-Africa prize on 17th March 2015 in Kuala Lumpur, Malaysia at the International Human Genome Meeting. An international committee unanimously decided that Alan was to receive this prize in recognition for the scientific leadership and vision he has provided on the African continent. His research projects since returning to South Africa in 2007 has focused on diseases prevalent in Africa. For example, he has been part of the executive team that has led a tsetse genome project in Africa that culminated in the publication of the Tsetse genome in Science journal. Over the past three years he has contributed to the Human, heredity and health in Africa programme, first as a member of a working group to design a funding framework for genomics research in Africa, and subsequently his involvement in genomics projects such as computational tools for use in infectious disease research such as tuberculosis.
The South African National Bioinformatics Institute is partnering Bika Lab Systems in customising an Open Source Bika LIMS branch for genomic lab disciplines and biobanking, including the management of sample and data distribution. The current Bika branch for health care laboratories, Bika Health 3.1, which already fulfills clinical subject requirements, is the starting point for this venture.
RAMICS is a method developed at SANBI that undertakes fast and highly accurate mapping/alignment of coding sequence reads in a biologically relevant manner. It identifies, and accounts for, PCR and sequencing induced errors resulting in an alignment that maintains the correct reading frame thereby enabling SNPs to be distinguished from noise.
The challenge presented by high-throughput sequencing necessitates the development of novel tools for accurate alignment of reads to reference sequences. Current approaches focus on using heuristics to map reads quickly to large genomes, rather than generating highly accurate alignments in coding regions. Such approaches are, thus, unsuited for applications such as amplicon-based analysis and the realignment phase of exome sequencing and RNA-seq, where accurate and biologically relevant alignment of coding regions is critical. To facilitate such analyses, we have developed a novel tool, RAMICS, that is tailored to mapping large numbers of sequence reads to short lengths (<10 000 bp) of coding DNA. RAMICS utilizes profile hidden Markov models to discover the open reading frame of each sequence and aligns to the reference sequence in a biologically relevant manner, distinguishing between genuine codon-sized indels and frameshift mutations. This approach facilitates the generation of highly accurate alignments, accounting for the error biases of the sequencing machine used to generate reads, particularly at homopolymer regions. Performance improvements are gained through the use of graphics processing units, which increase the speed of mapping through parallelization. RAMICS substantially outperforms all other mapping approaches tested in terms of alignment quality while maintaining highly competitive speed performance.
Download from Nucleic Acids Research