Hello everyone,
I am trying to figure out how to analyse some bisulfite sequencing data that I have and I am hoping that someone will have some suggestions as to how I should go about doing it. I have looked online and in statistics textbooks, but am totally stumped
I have performed 454 BS sequencing of a number of PCR amplicons. I have two different treatment groups, with n=3 biological replicates in each (six sets of read data in total). I want to use two types of statistical analysis to assess differences in methylation between the treatment groups. I would like to test for differences in methylation (1) at individual CpG sites within an amplicon and (2) across each amplicon as a whole. I think that it will be necessary for me to analyse my results as count data rather than %methylation values, as I have a small sample size and the %methylation values probably do not conform to normality or homogeneity of variance assumptions. Similar studies that I have seen in the literature have used a Fisher's exact test for (1) and a negative binomial generalised linear model for (2). However, these studies have analysed unreplicated data (where biological replicates were pooled prior to PCR) far and as I know these stat tests are unable to accommodate my replicated data. In another post, somebody suggested that the program DESeq could be used for (1). After trying to use DESeq to analyse my data I realised that this is not possible as the relatively small number of CpG sites that I have to analyse result in inaccurate mean/dispersion estimates.
If anyone has any idea as to which statistical tests would be appropriate for my data I would be very grateful.
Thank you in advance
I am trying to figure out how to analyse some bisulfite sequencing data that I have and I am hoping that someone will have some suggestions as to how I should go about doing it. I have looked online and in statistics textbooks, but am totally stumped
I have performed 454 BS sequencing of a number of PCR amplicons. I have two different treatment groups, with n=3 biological replicates in each (six sets of read data in total). I want to use two types of statistical analysis to assess differences in methylation between the treatment groups. I would like to test for differences in methylation (1) at individual CpG sites within an amplicon and (2) across each amplicon as a whole. I think that it will be necessary for me to analyse my results as count data rather than %methylation values, as I have a small sample size and the %methylation values probably do not conform to normality or homogeneity of variance assumptions. Similar studies that I have seen in the literature have used a Fisher's exact test for (1) and a negative binomial generalised linear model for (2). However, these studies have analysed unreplicated data (where biological replicates were pooled prior to PCR) far and as I know these stat tests are unable to accommodate my replicated data. In another post, somebody suggested that the program DESeq could be used for (1). After trying to use DESeq to analyse my data I realised that this is not possible as the relatively small number of CpG sites that I have to analyse result in inaccurate mean/dispersion estimates.
If anyone has any idea as to which statistical tests would be appropriate for my data I would be very grateful.
Thank you in advance
Comment