Quality Control, Mapping and Reads Count for RNA-Seq Analysis
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Updated
Mar 29, 2022 - R
Quality Control, Mapping and Reads Count for RNA-Seq Analysis
RNA-seq analyses.
SPEAQeasy: portable LIBD RNA-seq pipeline using Nextflow. Check http://research.libd.org/SPEAQeasy-example/ for an example on how to use this pipeline and analyze the resulting output files.
This repository houses the pipeline I coded to perform differential analysis of transcriptomes from two oyster species, C. gigas and C. virginica and isolate genes in the apoptosis pathway.
These are tutorials on a subset of tools available for processing raw RNAseq data. This if for HISAT2_SAMtools_Stringtie_gffcompare_ballgown pipeline or HISAT2_SAMtools_Stringtie_PrepDEanalysis.py_DESeq2 pipeline
Build Docker container for HISAT2 and (optionally) convert to Apptainer/Singularity.
A front-end GUI to map NGS DNA sequencing data using HISAT backend tool. This software offers robust seamless queueing of the mapping operations along with parameter memory for quick and easy customization.
Scripts to index and align Bovine genome with HISAT2
snakemake files of the tuxedo v2 pipeline from Pertea et al 2016
Independent project I undertook to perform a full ChIP-Seq analysis of the transcription factor Nanog in Zebrafish embryos.
Investigating unmapped reads within next generation sequencing data will provide additional information regarding the source of the trace microbial reads.
This project uses an workflow pipeline to generate map and assemble RNAseq reads to a reference genome. Furthermore, we generate counts data and identify differentially expressed genes from 2 conditions.
Proof of concept of a RNA-Seq pipeline from reads to count matrix (including quality control) with Nextflow and additional example RNA-Seq analysis in R
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