PerM is a software package which was designed to perform highly efficient genome scale alignments for hundreds of millions of short reads produced by the ABI SOLiD and Illumina sequencing platforms. Today PerM is capable of providing full sensitivity for alignments within 4 mismatches for 50bp SOLID reads and 9 mismatches for 100bp Illumina reads.
BitSeq is an application for inferring expression levels of individual transcripts from sequencing (RNA-Seq) data and estimating differential expression (DE) between conditions. An advantage of this approach is the ability to account for both technical uncertainty and intrinsic biological variance in order to avoid false DE calls. The technical contribution to the uncertainty comes both from finite read-depth and the possibly ambiguous mapping of reads to multiple transcripts.
HARSH (HAplotype inference using Reference and Sequencing tecHnology) is a method to infer the haplotype using haplotype reference panel and high throughput sequencing data. It is based on a novel probabilistic model and Gibbs sampler method.
SVDetect is a application for the isolation and the type prediction of intra- and inter-chromosomal rearrangements from paired-end/mate-pair sequencing data provided by the high-throughput sequencing technologies.
npSeq is an R package for the significance analysis of sequencing data. The statistic used by npSeq is exactly the same as that in SAM 4.0. The only difference is that npSeq uses symmetric cutoffs, while SAM uses asymmetric cutoffs. Therefore, for some datasets, all significant genes obtained by SAM are either all up-regulated or all down-regulated, but npSeq almost always gives significant genes that include both up-regulated genes and down-regulated genes.
fineSTRUCTURE is a fast and powerful algorithm for identifying population structure using dense sequencing data. By using the output of ChromoPainter as a (nearly) sufficient summary statistic, it is able to perform model-based Bayesian clustering on large datasets, including full resequencing data, and can handle up to 1000s of individuals.
CAGEr is an R implementation of novel methods for the analysis of differential TSS usage and promoter dynamics, integrated with CAGE data processing and promoterome mining into a first comprehensive CAGE toolbox on a common analysis platform.