You can also assemble and quantify these
samples rather than just counting the genes and so here, this software
is basically going to try to actually take these reads and estimate what transcripts
actually exist in the sample rather than just counting the annotated genes.
And then once it does that,
it's going to try to estimate abundances for each of the different transcripts.
So, StringTie and
Cufflinks do this in the case where there's a reference genome that's known.
If there isn't a reference genome that's known you can use Trinity.
And RSEM will retake a transcriptome and
then calculate the abundance for each transcript.
Then the next step is you need to normalize the data just like in
any kind of genomic data, you do the normalization and preprocessing.
EDAseq and cqn are R packages, or
bioconductor packages that you can use to normalize for GC content.
DESeq2 and edgeR are actually differential expression packages that have some
normalization built in.
As do Ballgown and derfinder which are Ballgown is a backend for
the cufflinks and RSEM pipelines and
derfinder is a single base resolution differential expression analyst.
Both of these have their own built in normalization.
To remove batch effects you can use the SVA and SVA seek function.
Or RUVseg to remove batch effects in these RNA sequencing data.
Then you need to perform statistical tests and statistical modeling.
You can do that with edgeR and DESeq2, or this for
the case where you have count data.
In the case where you have transcript quantification, you can use the Ballgown
package as a back-end to RSEM or as a back-end to Cufflinks.
And then if you want to do single based resolution analysis,
you can use the derfinder package to perform statistical tests or
statistical modeling of the RNA sequencing data.
Finally, you need to do some sort of gene set enrichment analysis to identify
gene sets or categories that are enriched within the sets,
genes that are differentially expressed.
You can do that with the goseq or the SeqGSEA packages in bioconductor.
