Tweet
Hi all,
I have 100 bp single reads RNAseq data (4 conditions X 3 replicates). I have the 12 relevant bam files (using tophat) and I have merged the 3 bam files per condition, so I come with 4 merged bam files in order to load them in IGV and have an approximate visualization per condition. However, since those data is not normalized I could not compare them. I saw that you can use bamCoverage (deep tools) to converts a single BAM file into a bigWig file, enabling you to normalize for sequencing depth.
Just to say that using EdgeR I have calculated the Normalization factors for each of the 12 samples and I am wondering whether I can exploit also these factors to normalize the 4 merged bam files.
Again my main goal is to normalize these 4 merged bam files so that they are comparable in order to create BigWig files to display the RNA-seq normalized density histograms in IGV. I think that I can normalize them either by a scaling factor or by RPKM.
Can anyone suggest a way of doing that using deep tools (https://github.com/fidelram/deepTool...Normalizations) or something else?
Thanks very much!
I have 100 bp single reads RNAseq data (4 conditions X 3 replicates). I have the 12 relevant bam files (using tophat) and I have merged the 3 bam files per condition, so I come with 4 merged bam files in order to load them in IGV and have an approximate visualization per condition. However, since those data is not normalized I could not compare them. I saw that you can use bamCoverage (deep tools) to converts a single BAM file into a bigWig file, enabling you to normalize for sequencing depth.
Just to say that using EdgeR I have calculated the Normalization factors for each of the 12 samples and I am wondering whether I can exploit also these factors to normalize the 4 merged bam files.
Again my main goal is to normalize these 4 merged bam files so that they are comparable in order to create BigWig files to display the RNA-seq normalized density histograms in IGV. I think that I can normalize them either by a scaling factor or by RPKM.
Can anyone suggest a way of doing that using deep tools (https://github.com/fidelram/deepTool...Normalizations) or something else?
Thanks very much!