I am very new to bioinformatics and trying to repeat the benchmark in the RapMap paper with an experimental tool working in a similar but different fashion.
To test the accuracy of different mapping and alignment tools in a scenario where we know the true origin of each read, we generated data using the Flux Simulator (Griebel et al., 2012). This synthetic dataset was generated for the human transcriptome from an annotation taken from the ENSEMBL (Cunningham et al., 2015) database consisting of 86090 transcripts corresponding to protein-coding genes. The dataset consists of 48 million 76 bp, paired-end reads. [...] When benchmarking these methods, reads were aligned directly to the transcriptome, rather than to the genome.
I understand that they generated reads using flux simulator, but I don't understand which transcriptome they mapped them against. I can't find any other information in the paper about which annotation they used either.
I am assuming one would need to generate an entire transcriptome in .fa format from the GTF and genome? Or did they generate a transcriptome from only the simulated reads and then mapped the same reads against it?
GENCODE offers GTFs and FASTAs for gene-encoding transcripts here, might that be the kind of thing they used? Would the reads simulated from these GTFs fit to these transcript FASTA files?