I have worked on rna seq and microareay public datasets. I have used Chipster Platform to reprocess the puplic datasets from fastq files or cel files to tsv files of differentially expressed genes(DEGs). The most important columns in those tsv files of DEGs of each dataset contain columns of p values, p adjusted values and log2fold change. I need to know how to interpret those data. I mean, what is the next step. How to find the most clinically relevant DEGs. Is there cutoff point to use the log2fold change. I mean, i have many DEGs with p values lower than 0.05, but many of those DEGs have fold changes less than one, minus or positive sign. I mean, -0.4, 0.66, or o.73 for example. How can i filter those data using log2fold change or p values. Thanks.
Many thanks for your answer. But if i have adjusted p value <0.05 but log 2 fc <1 what will be the solution?? Please put into consideration that values are given as log2fc not fc. Should this be converted??
A Log2 FC of 1 is the same as a FC of 2.