Assembly polishing software tools | De novo sequencing data analysis
The Pacific Biosciences RSII instrument is able to directly detect methylation from untreated DNA at both known and previously unrecognized motifs by analyzing polymerase kinetics in long sequence reads. For 5-mC, alterations in polymerase kinetics are subtle and spread over several bases, effectively precluding direct single-molecule detection.
Identifies DNA modifications in the case where 5-mC can be distinguished from cytosine by careful analysis of the electrical current signals. Nanopolish computes the log-likelihood ratio between an unmethylated version of a reference genome substring and a version that contained at least one ‘CG’ dinucleotide. It employs a signal-level hidden Markov model (HMM) method to work. This tool can increase the consensus accuracy around homopolymers.
Generates high quality consensus sequences with a single instruction multiple data (SIMD) accelerated. Racon is based on tests with PacBio and Oxford Nanopore datasets. It enables consensus genomes, and it depends on an input set of query-to-target mappings as well as quality values of the input reads to perform consensus calling.
Extracts statistics against genome positions based on sequence alignments. Pysamstats can identify read support for each base call and filter bases with low-coverage support. Performing base frequency allows to determine a polished consensus by taking the base call at any given position that is represented by sufficient coverage.
Maps PacBio reads to get consensus and variant calls. GenomicConsensus contains variantCaller, a main driver program which allows to apply two algorithms: Quiver that enables consensus accuracies on genome assemblies at accuracies approaching or exceeding Q60 and Arrow, an improved consensus model based on a hidden Markov model (HMM) approach.
Quantifies evidence for structural variation in genomic regions suspected of harboring rearrangements. SV-STAT extends existing methods by adjusting a chimeric read’s support of a structural variation by (i) the number of its soft-clipped bases and (ii) the quality of its alignment to the junction. SV-STAT is more accurate than alternative methods for determining base-pair resolved breakpoints. SV-STAT is a significant advance towards accurate detection and genotyping of genomic rearrangements from DNA sequencing data.