Very new to bioinformatics. I am trying to figure out the steps required to convert a chip-seq fastq file into a genome browser track, with the end goal of being able to access the sequence (x) vs. activity level/count (y) data associated.
Here x is the sequence axis, and y is the activity/count axis. Typically the x(i) is the nucleotide associated with the precise genomic coordinate i (an integer number) depending on the genome used to align (human, mouse, etc.). What I need is a format allowing direct access to the nucleotide representation x(i), associated with the index i, as well as the count levels at y(x(i)). What is the closest data file type that I need? And how do I get to it?
In other words, what are the steps for a fastq file associated with a chip-seq data to be transformed to this x(i),y(i) format, or best yet if there is an example Python or R code out there that could illustrate the steps of going from file1.fastq to something like to two files file1_x_sequences and file2_y_counts? I only know the first step is an alignment to a genome, but stuck on the next steps to complete the picture. Thank you.
Ultimately I need a list of sequences (tags) lets say 250bp long, and a count number that represents the chip-seq enrichment for the part of the genome (the 250bp region). Further reading, indicates I need to detect/call "peaks" with MACS2/homer to generate a BAM file and ultimately a Fasta file for the sequence lists, but I don't know yet how the 'counts' come in (in what file format and where from). Any hints there would complete the picture I think. Ultimately this is training data for x=250bp sequence to y=count/chip-seq enrichment activity model.