add step to assess other RNA quality measures

[andrewejaffe]

• add cross-species alignment with 1M reads
• add ribosomal RNA contamination from RSeQC

[andrewejaffe]

note we can just take all annotated ribosomal genes and calculate the ratio of their counts to the total number of gene counts, instead of using RSeQC...i've done this in the past and it works well

[andrewejaffe]

In the gencode annotation, there is an rRNA category for gene_type - just add a line of code that adds an rRNA_rate to the alignment metric table, like colSums(geneCounts[which(geneMap$gene_type == "rRNA"),])/colSums(geneCounts))

[emilyburke]

Cool that rRNA_rate code worked, thanks. What do you mean in the first bullet point? "add cross-species alignment with 1M reads"

[andrewejaffe]

Joo Heon aligns a small number of reads (like 1M) to other species to assess contamination during the library construction process. Basically it would involve:

1. subset 1M reads
2. align those reads to mm10 and rn6
3. retain hisat2 summary metrics

I am not completely convinced this adds much more usable information, as in the past, those samples with high cross-mapping tended to have higher chrM and rRNA mapping since those are homologous genes and thus relate to worse quality samples...

However, we will need to do something like this for the Stem Cell paper, as the neurons were a mix of human (neurons) and rat (glia) but I was going to have steve or badoi do it as a project-specific run

-a

On Thu, Jan 26, 2017 at 11:31 AM, Emily Burke notifications@github.com wrote:

Cool that rRNA_rate code worked, thanks. What do you mean in the first bullet point? "add cross-species alignment with 1M reads"

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