Search Results for "linux malware detect"

dataMAPPs allows routine and efficient processing of data from immunogenicity studies applying the MAPPs peptidomics technology to detect potential MHCI- or MHC-II epitopes as presented by dendritic cells (DC). It features quality control of the raw data, across-sample/across-donor normalization and visualization of results in a heatmap style (heatMAPPs). dataMAPPs' core is a generic R library that can be tailored to specific projects via dedicated control scripts which also allow...

Detecting allelic biases from high-throughput sequencing data requires an approach that maximises sensitivity while minimizing false positives. Here we present Allelome.PRO, an automated userfriendly bioinformatics pipeline, which uses high-throughput sequencing data from reciprocal crosses of two genetically distinct mouse strains to detect allele-specific expression and chromatin modifications. Allelome.PRO extends approaches used in previous studies that exclusively...

EigenMS is a normalization method implemented in R (and older version in Matlab) available as a set of two functions that should be used in a sequence. Please download EigenMS.zip file (latest version). Latest version uploaded in October 2017 has a bugfix for single treatment group normalization. Rescaling has been omitted from 2015. EigenMS utilizes SVD to detect bias trends in the data and eliminates them. EigenMS eliminates effects from known and unknown factors and can be...

Ericscript is a computational framework to detect gene fusions from paired end RNA-seq data with high sensitity and specificity.

ncPRO-seq is a tool for annotation and profiling of ncRNAs from smallRNA sequencing data. It aims to interrogate and perform detailed analysis on small RNAs derived from annotated non-coding regions in miRBase, piRBase, Rfam and repeatMasker, and regions defined by users. The ncPRO pipeline also has a module to identify regions significantly enriched with short reads that can not be classified as known ncRNA families. ############# Docker version : download and run Dockerfile (go in...

EDDA is a tool for systematic assessment of the impact of experimental design and the statistical test used on the ability to detect differential abundance. EDDA can aid in the design of a range of common experiments such as RNA-seq, ChIP-seq, Nanostring assays, RIP-seq and Metagenomic sequencing, and enables researchers to comprehensively investigate the impact of experimental decisions on the ability to detect differential abundance. More details of EDDA can be found at Luo, Huaien et al....

R scripts and sequence data used in the paper "Multiple local maxima for likelihoods of phylogenetic trees constructed from biological data." by McComish BJ, Schliep KP and Penny D (submitted to Systematic Biology).