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Designed to process individually barcoded Restriction-site associated DNA sequencing (RADseq) data (with double cut sites) into informative single nucleotide polymorphisms (SNPs)/Indels for population-level analyses. dDocent uses data reduction techniques and other stand-alone software packages to perform quality trimming and adapter removal, de novo assembly of RAD loci, read mapping, SNP and Indel calling, and baseline data filtering. Double-digest RAD data from population pairings of three different marine fishes were used to compare dDocent with Stacks, the first generally available, widely used pipeline for analysis of RADseq data. dDocent consistently identified more SNPs shared across greater numbers of individuals and with higher levels of coverage.

MAGERI / Molecular tAgged GEnome Re-sequencing pIpeline

Allows to obtain high-fidelity mutation profiles and call ultra-rare variants by handling caveats of Unique Molecular Identifier (UMI)-based analysis. MAGERI accounts for polymerase chain reaction (PCR) errors by using a variant quality scoring model. It can handle reads with high error load, indels and random offsets. The tool was able to detect circulating tumor DNA (ctDNA) in peripheral blood of cancer patients. It allows easy and efficient processing of high-throughput sequencing data generated.


Software tools for constructing watermark barcode sets and demultiplexing barcoded reads, together with example sets of barcodes and synthetic barcoded reads. expandAndWatermark takes an input file containing a set of outer codewords, expands them according to an inner codebook and imprints them with a watermark sequence to produce a set of barcodes, which are saved to an output file. watermarkDecoder decodes sequencing reads with embedded watermark barcodes.

GBS-SNP-CROP / GBS SNP Calling Reference Optional Pipeline

Discovers SNP and characterizes plant germplasm. GBS-SNP-CROP adopts a clustering strategy to build a population-tailored “Mock Reference” from the same GBS data used for downstream SNP calling and genotyping. It may be used to augment the results of alternative analyses, whether or not a reference is available. The tool may complement other reference-based pipelines by extracting more information per sequencing dollar spent. GBS-SNPCROP may be useful even in this case, able to detect large numbers of additional high-quality SNPs missed by the tag-based and read length-restricted approach of TASSEL-GBS.

RADIS / analysis of RAD-seq data for InterSpecific phylogeny

Automates and standardizes the analyses of RAD-seq data for phylogenetic inference. Users of RADIS can let their raw Illumina data be processed up to phylogenetic tree inference, or stop (and restart) the process at some point. Different values for key parameters can be explored in a single analysis (e.g. loci building, sample/loci selection), making possible a thorough exploration of data. RADIS relies on Stacks for demultiplexing of data, removing PCR duplicates and building individual and catalog loci. Scripts have been specifically written for trimming of reads and loci/sample selection. Finally, RAxML is used for phylogenetic inferences, though other software may be utilised.


A Genotyping-by-sequencing (GBS) bioinformatics pipeline designed to provide highly accurate genotyping. Fast-GBS is capable of handling data from different sequencing platforms and can detect different kinds of variants (Single Nucleotide Polymorphisms (SNPs), Multiple Nucleotide Polymorphisms (MNPs), and Indels). This pipeline was benchmarked based upon a large-scale, species-wide analysis of soybean, barley and potato. It is easy to use with various species, in different contexts, and provides an analysis platform that can be run with different types of sequencing data and modest computational resources.


A barcode demultiplexing and trimming tool for FastQ files. sabre will demultiplex barcoded reads into separate files. It will work on both single-end and paired-end data in fastq format. It simply compares the provided barcodes with each read and separates the read into its appropriate barcode file, after stripping the barcode from the read (and also stripping the quality values of the barcode bases). If a read does not have a recognized barcode, then it is put into the unknown file.