Genetics Tools

Program that reports identical fusion genes based on gene-name annotations.

Tool for single-species active module discovery.

Computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology.

Calls structural variants (SVs) and indels from mapped paired-end sequencing reads.

Scalable toolkit for analyzing single-cell gene expression data. It includes preprocessing, visualization, clustering, pseudotime and trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells.

Variant tool set that discovers short variants from Next Generation Sequencing data.

BAM Statistics, Feature Counting and Annotation

BAYEsian genome SCAN for outliers, aims at identifying candidate loci under natural selection from genetic data, using differences in allele frequencies between populations. It is based on the multinomial-Dirichlet model.

Differential expression analysis of RNA-seq expression profiles with biological replication. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi-likelihood tests. As well as RNA-seq, it be applied to differential signal analysis of other types of genomic data that produce counts, including ChIP-seq, SAGE and CAGE.

Data analysis, linear models and differential expression for microarray data.