Indel identification software tools | Pool sequencing data analysis
Pooled-DNA sequencing strategies enable fast, accurate, and cost-effect detection of rare variants, but current approaches are not able to accurately identify short insertions and deletions (indels), despite their pivotal role in genetic disease. Furthermore, the sensitivity and specificity of these methods depend on arbitrary, user-selected significance thresholds, whose optimal values change from experiment to experiment.
Implements methods for the analysis of pooled sequencing data generation. Syzygy is a variant calling method allowing: (i) single nucleotide polymorphism (SNP) calling on pooled data, (ii) estimation of allele frequencies of discovered variants, (iii) application of single-marker association test in pooled setting, (iv) group wise testing of rare and low frequency variants discovered, (v) power evaluation and quality control (QC) summary, as well as (vi) annotation of variants discovered in regions from primary sequencing data in BAM/SAM format.
A platform-independent mutation caller for targeted, exome, and whole-genome resequencing data generated on Illumina, SOLiD, Life/PGM, Roche/454, and similar instruments. The newest version, VarScan 2, is written in Java, so it runs on most operating systems. It can be used to detect different types of variation: 1) germline variants (SNPs and indels) in individual samples or pools of samples, 2) multi-sample variants (shared or private) in multi-sample datasets (with mpileup), 3) somatic mutations, LOH events, and germline variants in tumor-normal pairs and 4) somatic copy number alterations (CNAs) in tumor-normal exome data.
Detects and quantifies short indels and substitutions in large pools. SPLINTER allows accurate detection and quantification of short insertions, deletions, and substitutions by integrating information from the synthetic DNA library to tune SPLINTER and quantify specificity and sensitivity for every experiment in order to accurately detect and quantify indels and substitutions.
A Bayesian method to call indels from short-read sequence data in individuals and populations by realigning reads to candidate haplotypes that represent alternative sequence to the reference. The candidate haplotypes are formed by combining candidate indels and SNVs identified by the read mapper, while allowing for known sequence variants or candidates from other methods to be included. In our probabilistic realignment model we account for base-calling errors, mapping errors, and also, importantly, for increased sequencing error indel rates in long homopolymer runs.
Consists of a haplotype-based variant caller. Octopus uses a polymorphic Bayesian genotyping model that can model sequencing data from a range of experimental designs within a unified haplotype-aware framework. The software performs detection of genetic variation from high-throughput sequencing data (reads) relative to a reference sequence. It is able to call a wide range of indels. This program can serve for identifying and classifying germline, somatic, or de novo mutations across multiple samples.
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