Heatmap from the RNAseq raw count data

Question

[basucsmcri]

In my RNAseq data, I have identified 60 DEGs which are shared amongst 6 conditions. I have a normalized raw count data of these 60 DEGs. Now I am looking to make heatmap of these 60 DEGs so that I can show differential expression of different genes in these 6 conditions.

After doing literature search, I found I have to convert normalized raw count data to matrix. I am a microbiologist so I don't have great expertise in programming. Can you please let me know which commands i can use in R to prepare the matrix or any other way by which I can prepare the heatmap.

I will really appreciate your kind help Thanks

Answer 1

[JC]

To load your data you just need to save it in CSV, TSV or similar format, R includes multiple ways to load data from files (read.table):

data_tsv <- read.table("path/to/file.tsv", header=TRUE, row.names=1)

The next step is just to use the heatmap.2 function to create your image.

[basucsmcri]

Thank you for your help. Appreciated

Answer 2

[demoraesdiogo2017]

use morpheus and never bother with any heatmap clusterization tool ever again. no coding required.

https://software.broadinstitute.org/morpheus/

[igor]

For some additional graphical options, see: https://github.com/igordot/genomics/blob/master/notes/heatmaps.md

Answer 3

[predeus]

You can use an online tool like Phantasus: http://genome.ifmo.ru/phantasus-dev/

there are normalization and other options, and you don't need to have any experience in programming. Tutorial is here: http://genome.ifmo.ru/phantasus-dev/phantasus-tutorial.html

[basucsmcri]

Thanks a lot. I really appreciate it. Only things which concerns me is that it is specific for human and my data is of bacterial transcriptome so I could not annotate my genes.

[predeus]

If you have a simple text file with your locus tag annotation, you can easily annotate all genes.