Search Results for "miarma-seq"

COHCAP (City of Hope CpG Island Analysis Pipeline, pronounced "co-cap") is an algorithm to analyze single-nucleotide resolution methylation data (Illumina 450k methylation array, targeted BS-Seq, etc.). Please note: 1) The SourceForge version of COHCAP is no longer being updated. Please see the GitHub version: https://github.com/cwarden45/COHCAP This was the source repository for the Bioconductor version, with some changes after the decision to only provide the code through GitHub. 2) In addition to the original NAR paper, please see the following links: Benchmarks: http://www.nature.com/protocolexchange/protocols/2965#/introduction Protocol Exchange Files: http://sourceforge.net/projects/cohcap/files/Protocol_Exchange_Example.zip 3) Custom Annotation Files (including EPIC Array): https://sourceforge.net/projects/cohcap/files/additional_Bioconductor_annotations.zip/download

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

...Open chromatin regions allow regulatory elements such as transcription factors and polymerases to bind for gene expression while closed chromatin regions prevent the activity of transcriptional machinery. Recently, nucleosome occupancy and methylome sequencing (NOMe-seq) has been developed for simultaneously profiling of chromatin accessibility and DNA methylation on single molecules. However, there is no computational method for analyzing NOMe-seq data. Results: In this article, we present CAME, a seed-extension based approach that identifies chromatin accessibility from NOMe-seq. The efficiency and effectiveness of CAME were demonstrated through comparisons with other existing techniques on both simulated and real data, and the results show that our method not only can precisely identify chromatin accessibility but also outperforms other methods.

Use statistical methods to analyze time-course data (gene expression microarray and RNA-seq data in particular, but not limited to). Apply significance tests to filter out only significant genes or time series. Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R. The application is a cross-platform desktop app with a simple GUI and is fully functional currently. ...

This R package can be used to identify TRMs using experimental evidence from a single ChIP-seq experiment. It combines computational predicted transcription factor (TF) binding sites, gene expression and protein-protein interaction (PPI) data and use it to predict TRMs.

Simulation of allele-specific RNA-seq data

MOVED TO GITHUB: https://github.com/noporpoise/seq-align Global optimal sequence alignment using the Needleman-Wunsch algorithm. Aligns DNA, RNA, protein sequence and more! See our sister project local alignment using Smith-Waterman: http://sourceforge.net/projects/smithwaterman/

THIS IS NO LONGER THE HOME FOR SEURAT. PLEASE GO TO https://sites.google.com/site/seuratsomatic/ --- Seurat is an sequence analysis program for somatic mutation and allelic imbalance discovery in paired tumor and normal genome and transcriptome data.

A R based universal workflow for analysising miRNA sequencing data

MOVED TO GITHUB: https://github.com/noporpoise/seq-align An implementation of the Smith-Waterman local sequence alignment algorithm. See our sister project global alignment using Needleman-Wunsch: http://sourceforge.net/projects/needlemanwunsch/

Random Genome Sequence Downloader.