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GINDEL
An approach for calling genotypes of both insertions and deletions from sequence reads. GINDEL uses a machine learning approach which combines multiple features extracted from next generation sequencing data. It performs well for insertion genotyping on both simulated and real data. GINDEL can not only call genotypes of insertions and deletions (both short and long) for high and low coverage population sequence data, but also is more accurate and efficient than other approaches.
AMF / AgroMarker Finder
A GUI software for providing graphical user interface (GUI) to facilitate the recently developed restriction-site associated DNA (RAD) sequencing data analysis in rice. AMF integrates sophisticated tools with self-developed algorithms that can help users finish data analysis with simple operation. It consists of five independent modules: FilterAndMapping, BamConvert, NPInDel, DetectionAndAnnotation, SomaticDetection and VariantLocation. Based on this software, large volumes of polymorphism data have been discovered and analyzed, which will be meaningful for further application, such as genetic mapping, genetic map construction, evolutionary studies and marker-assisted seletion.
ReviSeq
Revises a genome sequence of a prokaryotic sample. ReviSeq uses a hybrid method comprised of iterative remapping and local assembly upon a bacterial sequence backbone. This method was applied to six Brucella suis field isolates compared to the newly revised Brucella suis 1330 reference genome identified on average 13, 15, 19 and 9 more variants. Using this iterative approach, the method identified on average 87 variants including single-nucleotide variants (SNVs), short insertions and deletions (INDELs) and long INDELs per strain when compared to the reference.
Vindel
Detects redundant indels. Vindel, a simple yet effective computational pipeline, can be used to check whether a set of indels are redundant with respect to those already in the database of interest such as NCBI inverted question marks dbSNP. Of the approximately 5.9 million indels we examined, nearly 0.6 million are redundant, revealing a serious limitation in the current indel annotation. Statistics results prove the consistency of the pipeline on indel redundancy detection for all 22 chromosomes. Apart from the standalone Vindel pipeline, the indel redundancy check algorithm is also implemented in the web server.
UPS-indel / Universal Positioning System of indels
Creates a universal positioning system for insertions/deletions (indels) and allows to compare indel calling results produced by different tools. UPS-indel is a universal positioning system for indels, whereby every indel variant is represented by a range of positions within which all equivalent indels can occur. This representation is added to the VCF file resulting in a UVCF file containing not only the original indel calling results, but also the complete representation of all equivalent indels.
BBCAnalyzer
Allows the visualization of the relative or absolute number of bases, deletions and insertions at defined positions in sequence alignment data available as bam files in comparison to the reference bases. BBCAnalyzer consists of different steps that are highly dependent on each others output, which is why it is necessary to run the function analyzeBases, performing the whole process of analyzing the data and visualizing the results, at first. The runtime of the tool depends on the number of samples and the number of positions that get analyzed.
SomaticIndelDetector
The Somatic Indel Detector can be run in two modes: single sample and paired sample. In the former mode, exactly one input bam file should be given, and indels in that sample are called. In the paired mode, the calls are made in the tumor sample, but in addition to that the differential signal is sought between the two samples (e.g. somatic indels present in tumor cell DNA but not in the normal tissue DNA). In the paired mode, the genotyper makes an initial call in the tumor sample in the same way as it would in the single sample mode; the call, however, is then compared to the normal sample.
SV-AUTOPILOT / Structural Variation AUTOmated PIpeLine Optimization Tool
Obsolete
Standardizes the Structural Variation (SV) detection pipeline. SV-AUTOPILOT is a pipeline that can be used on existing computing infrastructure in the form of a Virtual Machine (VM) Image. It provides a “meta-tool” platform for using multiple SV-tools, to standardize benchmarking of tools, and to provide an easy, out-of-the-box SV detection program. In addition, the user can choose which of several alignment algorithms is used in their analysis.
GVC / Genomic Variant Caller
Obsolete
Detects various genomic variants including single nucleotide variant (SNV), single insertion/deletion (sINDEL) and structural variation (SV) from personal and normal-cancer paired whole-genome/exome sequencing data. GVC is an all-round genomic variant caller. This resource (i) aligns paired-end FASTQ files to the human GRCh37 reference genome with BWA-MEM and (ii) extracts feature information from Binary Alignment Map (BAM) file to assemble feature vector space.
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