Pairwise SNP distribution between genotypes identified in RAD dataset.

<p>The genotypes show high variation with the reference when compared to pairwise combination of genotypes, indicating missing SNPs (a characteristic of RADseq) that could be imputed. Overall the numbers of SNPs between genotypes were found to be in the range of 442 to 1151.</p

A snapshot on SNPs in four chickpea genotypes compared to the reference genome.

<p>The Venn diagram shows distribution of SNPs detected between four genotypes (Pistol, Hat Trick, Slasher and Genesis 90). The genotype CDC Frontier was used as a reference sequence. For instance, a total of 95,329 SNPs were found to be concordant between Pistol and Hat Trick genotypes. Similarly, amongst all the four genotypes 62,291 SNPs were found to be in common.</p

The work-flow of the ISMU pipeline.

<p>The work-flow of the ISMU pipeline is mainly divided into three steps: (A) Data import, quality pre-processing, (B) Sequence alignment and SNP discovery, and (C) Visualization and generation of input files for genotyping assay.</p

RNAseq dataset used for evaluation of the pipeline.

<p>Above mentioned RNA sequencing read data from two genotypes of peanut were included in this dataset. Raw reads were filtered and then aligned against the unigene sequences of peanut (<a href="ftp://ftp.ncbi.nih.gov/repository/UniGene/Arachis_hypogea/Ahy.seq.uniq.gz" target="_blank">ftp://ftp.ncbi.nih.gov/repository/UniGene/Arachis_hypogea/Ahy.seq.uniq.gz</a>) as reference. The pre-processing step of pipeline trimmed 90 bp reads into paired end reads of length 72 bp/74 bp.</p

Comparison of key features of the ISMU pipeline with similar pipelines.

<p>ISMU is one of the few tools that provide an easy to use graphical interface (GUI) packed with a wide choice of open source tools (alignment and variant calling) for handling NGS data. The information describing features of other pipelines is derived from Fisher et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0101754#pone.0101754-Fischer1" target="_blank">[60]</a> and compared. The symbols “Y” and “N” represent, presence and absence of the feature in the pipeline. Numbers (1. 5, 2) indicate number of tool included in the pipeline. “n.m” refers to feature not mentioned.</p

Run time profile of the ISMU pipeline with three datasets (WGRS, RAD and RNAseq).

<p>Three datasets (WGRS, RAD and RNAseq) were analysed independently with 18 processors on a 48 GB RAM Linux based machine. The disk-space used for analysis, peak memory used and the total time for the run were recorded. Analysis of RNAseq dataset was quicker than RAD/WGRS datasets owing to both small input size and smaller reference sequence pseudo-molecules/contigs. The disk space requirements were found to be proportionate to data size.</p

Source of marker data used for constructing the reference consensus genetic map.

<p>Source of marker data used for constructing the reference consensus genetic map.</p

Summary of number of loci common between genetic maps for different mapping populations.

<p>Summary of number of loci common between genetic maps for different mapping populations.</p

Features of the component and reference consensus genetic maps.

<p>Features of the component and reference consensus genetic maps.</p

A microsatellite consensus genetic map comprising 897 marker loci based on 11 mapping populations.

<p>Markers are shown on <i>right</i> side of the LG while map distances are shown on the <i>left</i> side. Each LG has been divided into 203 BINs of 20 cM each. The homoeologous loci between the corresponding LGs in the reference consensus map are indicated in red colour.</p