RAMICS: trainable, high-speed and biologically relevant alignment of high-throughput sequencing reads to coding DNA

Abstract

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.

Cooperation between Strain-Specific and Broadly Neutralizing Responses Limited Viral Escape and Prolonged the Exposure of the Broadly Neutralizing Epitope

“…Sequences with a primer ID that was represented in fewer than three reads were discarded, along with those containing degenerate bases. The remaining sequences from each time point were aligned with MAFFT, Muscle, or RAMICS ( 60 ). Phylogenetic trees were drawn with FastTree v2.1 ( 61 ) and visualized using the python library ete3 ( 62 ).…”

Viral variants that initiate and drive maturation of V1V2-directed HIV-1 broadly neutralizing antibodies

“…A custom python script was used to bin all reads containing an identical Primer ID tag, align the reads within each bin using MAFFT 32 and produce a consensus sequence based on a majority rule. Sequences with just one Primer ID representative, as well as consensus sequences derived from less than three reads and those containing degenerate bases, were excluded and the remaining sequences from each time point aligned with MAFFT, Muscle 33 or RAMICS 34 . The calculation of amino acid frequencies and hamming distances (for each sequence relative to the consensus sequence from the first time point –inferred PI virus), were performed using custom python scripts.…”

Virome Assembly and Annotation: A Surprise in the Namib Desert

“…PhiX reads not removed by the Illumina MiSeq reporter software (version 3) or through duplicate removal were filtered by mapping all reads to PhiX-174 using RAMICS (Wright and Travers, 2014). Similarly, reads matching the human genome (Hg19; http://tinyurl.com/jay436s) were filtered using consecutively Bowtie2 and RAMICS.…”