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llfsrnaseq

An R package which stores the code used to process Long Life Family Study RNA sequencing from fastq to analysis releases

https://github.com/cmatkhan/llfsrnaseq

Science Score: 54.0%

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    CITATION.cff file
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    Low similarity (13.6%) to scientific vocabulary

Keywords

genomics longevity rnaseq
Last synced: 11 months ago · JSON representation ·

Repository

An R package which stores the code used to process Long Life Family Study RNA sequencing from fastq to analysis releases

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genomics longevity rnaseq
Created about 3 years ago · Last pushed over 2 years ago
Metadata Files
Readme Changelog License Citation

README.md

R-CMD-check

Introduction

This repository documents how the Long Life Family Study RNA sequencing data is processed.

There is no data stored in this repository. If you feel like you need the data, and don't already have access, then you should talk to your lab and ask how to get access. Please see the Getting Started section of the documentation for an explanation of how this data is tracked in relation to the versioned software releases.

Wait -- this is different

I used to distribute this data as a tarred, zipped R project. There was a subdirectory called data which had both the DeseqDataSet gene and transcript objects (see Why Use DESeqDataSet Objects) and csv files.

That data directory is now what will be distributed through box and on the dsg cluster. This repository will store the versioned code which corresponds to a given data release, and the documentation.

Installation and Usage

You can use this in a couple different ways, but the starting point for all of those ways is the served documentation. I'd start with Getting Started, myself.

Why Use DESeqDataSetObjects

Even if you aren't going to do differential expression analysis using DESeq2, it is useful to use the DESeqDataSet object. DESeqDataSet objects inherit from the basebioconductor object SummarizedExperiment. And, SummarizedExperiment is a core component of Bioconductor's Scalable Genomics Toolset.

The LLFS dds object has the GRCh38 annotations stored in the rowRanges. The metadata rows also are forced to correspond to the count columns. So, you could choose a single gene in a single sample like this:

R dds['ENSG....', dds$library_id==2]

# Some final notes

if the R CMD Check CI is passing, that means that this package successfully builds on the latest Windows, latest Mac, and the two most current Ubuntu OS's. If you are using one of these operating systems, then this will install on your system. If you are using an older, or different, OS, then there are no promises. Go ahead and open a bug report if this is the case, and I will create a Docker and/or singularity container for you.

Owner

  • Name: Chase Mateusiak
  • Login: cmatKhan
  • Kind: user
  • Location: St Louis, MO
  • Company: Washington University

Bioinformatics Scientist in Michael Brent's lab at Washington University, St Louis

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Mateusiak"
  given-names: "Chase"
  orcid: "https://orcid.org/0000-0002-2890-4242"
title: "llfsRnaseq: Long Life Family Study RNAseq Data Processing"
version: 1.0.0
date-released: 2023-07-11
url: "https://github.com/cmatKhan/llfsRnaseq"

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