I am interested in calling all the mismatches/conversions in my RNA modification dataset that is generated using Illumina TruSeq protocol (dUTP). I am using the JACUSA2 pileup method for this step. Since the JACUSA2 pileup requires libraries/samples from two different conditions, I am interested in knowing the best way to concatenate the results or matrices obtained via read_result if I have more than two conditions. For example:
I ran the JACUSA2 pileup between cond1 and cond2. I get the GRanges matrix using read_result function, say this matrix is mat1. Now, I have another condition, cond3, and will compare it to cond1. I run JACUSA2 pile up on this comparison and get another GRanges matrix using read_result. The matrix I get is mat2. What is the best way to combine the two matrices so that I can calculate the substitution in my RNA libraries uniformly and not have issues due to the depth of the sequencing?
I am interested in calling all the mismatches/conversions in my RNA modification dataset that is generated using Illumina TruSeq protocol (dUTP). I am using the JACUSA2 pileup method for this step. Since the JACUSA2 pileup requires libraries/samples from two different conditions, I am interested in knowing the best way to concatenate the results or matrices obtained via
read_result
if I have more than two conditions. For example:I ran the JACUSA2 pileup between cond1 and cond2. I get the
GRanges
matrix usingread_result
function, say this matrix is mat1. Now, I have another condition, cond3, and will compare it to cond1. I run JACUSA2 pile up on this comparison and get anotherGRanges
matrix usingread_result
. The matrix I get is mat2. What is the best way to combine the two matrices so that I can calculate the substitution in my RNA libraries uniformly and not have issues due to the depth of the sequencing?