Entering edit mode
6.5 years ago
kyusikkim
▴
20
Hello All! I had some questions involving alignment based v alignment free mapping done by Salmon as well as some other general questions pertaining specifically to our experiments. Please excuse any perceived ignorance as I'm more of a molecular than computation biologist and statistics is not my strong suit!
- If one will probably map the reads in order to visualize downstream via tools like IGV, is it better to use the alignment based mapping so that Salmon agrees with the alignment output?
- Our experiments involve looking at ribosome profiling data when translation is disrupted - resulting in low read counts. We also have the corresponding RNA-Seq data. Should one use gcbias and seqbias for one/both data sets? My idea was to not use either option to avoid introducing bias into our already limited ribosome profiling data set.
- Could someone provide a better explanation for fldMean and fldSD? We are using Illumina HiSeq 50 bp single end reads. Would changing the default settings be more useful? I had a hard time understanding the documentation / comments in Source Code
- While I believe I generally understand the kmer parameter in alignment free mapping, I don't quite understand how it works for reads with lengths < kmer length. I ask because our ribosomal fragments range from 12-36 nt but I get maximum mapping percentage at k=17. Are the smaller fragments simply excluded? (I forgot to check if # unmapped = total reads with lengths < 17, I will check and edit).
Thank you for the understanding and help!
