Back-end R package for running anexvis web application
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Updated
Feb 25, 2018 - R
Back-end R package for running anexvis web application
MuSTA: Multi-Sample Transcriptome Assembly for long-read isoform sequencing
Escherichia coli Transcriptome Assembly from a Compendium of RNA-seq Data Sets
A snakemake workflow for performing de novo transcriptome assembly, quality assessment and transcript quantification.
get chloroplast and mitochondrial genes from contigs of genome-skimming or transcriptome data
Role of CXCL9/10/11, CXCL13 and XCL1 in recruitment and suppression of cytotoxic T cells in renal cell carcinoma
⏳ Online graphical interface to explore age-related gene expression alterations in 49 GTEx human tissues
Pipeline for low-level RNA-Seq data processing
SIMulator for Long read transcriptome Analysis with RNA DecaY model
Shiny app that recopilates all gene expression of zebra fish and informs about the tissue and developmental stage in which the gene is expressed.
An application for exploring and visualizing differential gene expression data created with DESeq2
Peptide Mapping in Genome and peptide Detection in Transcriptomes
Brivez is a bioinformatic tool thought as Quality of Life's improvement, providing high quantity of data in a snap, giving you a quick view on what you could find inside your transcriptome/sequences' list.
Select best protein codeing genes from models Generated from MAKER2, Cufflinks and any de novo assembling programs. Previously called MCOT, with this publication (http://www.sciencedirect.com/science/article/pii/S0965174815000144).
Code to model distribution of transcript abundances.
Transcriptome analytic tools for non-model organism
The web genome viewer is live at https://icemduru.github.io/listeria_ro15_transcript/
BLAST DataBase Manager
AnceTran2.0: R package for transcriptome evolution analysis based on RNA-seq expression data or ChIP-seq TF-binding data
Inferring Transcript Phylogenies from Transcript Ortholog Clusters
Add a description, image, and links to the transcriptome topic page so that developers can more easily learn about it.
To associate your repository with the transcriptome topic, visit your repo's landing page and select "manage topics."