Bacterial comparative transcriptome analysis like Assembly, Histogram, Heat map, Pearson correlation between treated and non treated sequence?
Dear
you can see this link
https://omictools.com/transcriptome-assembly-category
May be this will help you.
I used Tuxedo pipeline along with edgeR package for differential expression analysis. This works perfect for HTS-RNA-seq data obtained from Illumina platforms. I am working with human data, but I think that it can be useful for bacterial profiles as well. The pipeline is the following:
1) For raw data quality statistics - FastX-Toolkit, Rseq, FastQC.
2) For alignment to the reference genome - TopHat (I used iGenome for reference genome).
3) Transcriptome assemblies - Cufflinks.
4) Read counts - HTSeq.
5) Differential expression (DE) analysis - edgeR.
The other option for DE analysis can be Cuffdiff after Cufflinks with following visualization in CummeRbund. edgeR and CummeRbund are R packages with plenty functions for data plotting and data visualizing.
What kind of bacterial genome you are looking for? Does it well annotated? If not, may be you need searching for tools that allow de novo assemblies, such as Trinity.
If You interested in more details, I can send You my protocol for transcriptome analysis.
If you are using microarray data, use something like LIMMA, if it's RNA-seq data then you will want to use FastQC or SolexaQA for quality analysis with Trimmomatic to remove sequencing primers and poor quality reads. Followed by Bowtie2 alignment of reads to reference gene models (cDNA) from your reference organism and count reads aligned to each gene (mpcox.github.io/mapcount). You will need to do some data exploration to figure out a filtering strategy to eliminate noise and unreliable data before differential expression analysis with edgeR or DESeq2.
EDIT: I don't like self-referencing, but there is a more complete explanation in the M&M of my thesis:
http://mro.massey.ac.nz/xmlui/bitstream/handle/10179/7515/02_whole.pdf?sequence=2&isAllowed=y
However, I do encourage you to take a thorough look through the forums on seqanswers.com because it was an immensely helpful resource during my doctorate.
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