Single Cell RNA-Seq Data Analysis

SC1: A web-based single cell RNA-seq analysis pipeline

LSImpute: Locality Sensitive Imputation for scRNA-Seq data

NGS Data Analysis

DGE-EM: Accurate Estimation of Gene Expression Levels from DGE Sequencing Data

GeneSeq: LD-based Genotype Calling from Shotgun Sequencing Reads

kGEM: k-Genotype Expectation Maximization algorithm for Reconstructing a Viral population from Single-Amplicon reads

IsoEM2: Inferring Alternative Splicing Isoform Frequencies from High-Throughput RNA-Seq Data

IsoDE2: Bootstrapping-based differential gene expression analysis for RNA-Seq data with and without replicates

MaLTA: transcriptome assembly and quantification from Ion Torrent RNA-Seq reads

NGSTools – Java tools for analysis of Next Generation Sequencing data

SMART2: Multi-Sample Statistical Mitogenome Assembly with Repeats

SILP2 – ILP-based Maximum Likelihood Genome Scaffolding

VirA – Viral Quasispecies Assembler from Amplicon Sequencing Reads

ViSpA – Viral Spectrum Assembler from Shotgun Sequencing Reads

SNP Data Analysis

ENT: Genotype Phasing by Entropy Minimization

GEDI: Genotype Error Detection and Imputation

GEDI-ADMX: Genotype Error Detection and Imputation for Admixed Populations

Immunogenomics

Epi-Seq: Bioinformatics pipeline for predicting tumor specific epitopes from RNA-Seq data

Metabolomics

BioSM: A cheminformatics tool for identifying endogenous mammalian biochemical structures

TrackSM: Metabolic pathway prediction based on molecular structure matching

Primer and Probe Selection

DNA-BAR: Distinguisher Selection for DNA Barcoding

G-POT: Multiplex-PCR Primer Set Selection

Primer Hunter: Primer Design for PCR-Based Virus Subtype Identification

DNA Array Design

DNA-CHIP: DNA Array Design

VLSI Routing

FastSteiner: Rectilinear and Octilinear Minimum Steiner Tree Algorithm

MCF: Multicommodity Flow Based Congestion- and Timing-Driven Global Routing and Buffer Insertion

RMST-Pack: Rectilinear Minimum Spanning Tree Algorithms

Acknowledgment and Disclaimer

These software packages are based upon work supported in part
by the National Science Foundation under Grants No. IIS-0546457, DBI-0543365, IIS-0916948, DBI-1564936, and CCF-1618347, and by the USDA National Institute of Food and Agriculture under award #2011-67016-30331. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding agencies.