Biostar Beta. Not for public use.
(Modern, mid-2016) RNA-seq software pipeline
9
Entering edit mode
11 months ago
jp • 100

I am trying to follow the RNA-seq protocol described in (this excellent paper):

Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks (2012) http://www.nature.com/nprot/journal/v7/n3/full/nprot.2012.016.html

This was published three/four years ago, so not that much in terms of scientific timeline - but I noticed the tools described in the pipeline have not been updated in a while or have been replaced by other software. More specifically:

I know there are other software components which can replace some of the above (e.g. Star aligner instead of bowtie/tophat). I understand that the standard answer is "depends on what you want to do" (differential gene expression and variant analysis in my case - from human samples).

My question to the community is - what is a modern bioinformatics software pipeline to carry out RNAseq analysis?

Thanks for your suggestions or comments you may have,

ADD COMMENTlink
2
Entering edit mode
  • Use a splice-aware aligner if you are not using bacterial samples (STAR is popular but needs good bit of RAM, BBMap is simple to use).
  • Count using featureCounts (part of subread package, much faster than htseq-count, will automatically sort bam files). Make sure SAM tags are in v.1.3 format (most counting packages don't understand SAM v.1.4, the current format)
  • DE analysis with DESeq2 (or edgeR) or a comparable package.

Much the same advice is here Suggestions for RNA seq pipeline

ADD REPLYlink
0
Entering edit mode

This post also has more information, particularly re: pseudoalignment approaches

ADD REPLYlink
0
Entering edit mode

You might want to take a look at kallisto it's quantifies gene expression without alignment, making it very fast. https://pachterlab.github.io/kallisto/

ADD REPLYlink
4
Entering edit mode
9 months ago
ivivek_ngs ♦ 4.8k
Seattle,WA, USA

I would would suggest also to take a look at Salmon followed with DESeq2 /edgeR/ voom for Differential analysis , be it at transcript level or gene-level. You can also take a look at this link which has summarization of different RNA-Seq tools which have evolved over the years.

ADD COMMENTlink
4
Entering edit mode
12 months ago
amit.sinhaa • 40

An updated version of the TopHat-Cufflinks pipeline (Trapnell et al 2012), with all the updated tools has recently been published as: Pertea et al (2016) Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. www.nature.com/nprot/journal/v11/n9/full/nprot.2016.095.html Hope you find it useful

ADD COMMENTlink
0
Entering edit mode

This feels more appropriate for the OP as they have specifically said they want to do downstream variant analysis which implies at some point you're going to want to align the data, rather than rely on pseudoalignment approaches (awesome though they are)

ADD REPLYlink
1
Entering edit mode
9 months ago
Carlo Yague ♦ 4.5k
Belgium

There is the RNA-seq workflow at the gene level from bioconductor (2015). Its main focus is the differential expression analysis stage but it also briefly covers the read mapping and summarization.

ADD COMMENTlink
1
Entering edit mode
10 months ago
Ming Tang ♦ 2.5k
Houston/MD Anderson Cancer Center

I keep a note for RNA-seq here https://github.com/crazyhottommy/RNA-seq-analysis#normalization-quantification-and-differential-expression

ADD COMMENTlink

Login before adding your answer.

Similar Posts
Loading Similar Posts
Powered by the version 2.1