<p>If they generated reads from the transcriptome then the started with the FASTA version of the ENSEMBL transcriptome and then aligned the reads back to it.  For a project like this I don't think that you need the GTF files, since you don't need to know the location of the transcript on the larger genomic reference.  If you can't find an ENSEMBL transcriptome then you can use the GTF and the bedtools program to create a FASTA.   </p>

CC BY-SA 3.0
2017-11-09T15:43:35.793Z
The read simulator they used, Flux, can only generate reads from GTF format annotation and a genome, not from transcriptomes in FASTA format. For the time being I'm trying to work with the current GENCODE releases, which offer transcriptomes in fasta format, corresponding to their GTF annotations, but I will also look into your suggestion of using bedtools.
JMC
CC BY-SA 3.0
2017-11-08T23:53:07.903Z
2017-11-08T23:53:07.903Z
Bioathlete
<p>Thanks for your interest in RapMap.</p>

<p>At that time we were using flux simulator for simulating read sequence data. We used the genome and gtf file together as an input to flux. </p>

<p>I dug into the scripts and got hold of the gtf link <code>ftp://ftp.ensembl.org/pub/release-80/gtf/homo_sapiens/Homo_sapiens.GRCh38.80.gtf.gz</code>, 
and the genome file link <code>ftp://ftp.ensembl.org/pub/release-80/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.toplevel.fa</code>. </p>

<p>We used <code>rsem-prepare-reference</code> to create the reference transcriptome file later in order to run RapMap and other transcriptome based quantification tools. I hope this helps. </p>

<p>PS: I am a coauthor of the RapMap paper. </p>

CC BY-SA 3.0
2017-12-11T05:27:46.740Z
2017-12-11T07:57:24.453Z
2017-12-11T07:57:24.453Z
CuriousS
<p>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.</p>

<p>In the <a href="https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btw277" rel="nofollow noreferrer">paper</a> (taken from their <a href="https://github.com/COMBINE-lab/RapMap" rel="nofollow noreferrer">github</a>) about RapMap, an alignment/mapping tool for rna-seq reads to a reference genome, the dataset used for their benchmarks is described like this:</p>

<blockquote>
  <p>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.</p>
</blockquote>

<p>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.</p>

<p>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?</p>

<p>GENCODE offers GTFs and FASTAs for gene-encoding transcripts <a href="https://www.gencodegenes.org/releases/current.html" rel="nofollow noreferrer">here</a>, might that be the kind of thing they used? Would the reads simulated from these GTFs fit to these transcript FASTA files?</p>

CC BY-SA 3.0
2017-11-09T00:37:25.807Z
FYI, I took the liberty of asking Rob Patro to have someone from his team reply.
Devon Ryan
<phylogenetics><read-mapping><transcriptome>
RapMap: reference transcriptome for simulated reads
# RapMap: reference transcriptome for simulated reads

(Asked by: username_0 on 2017-11-08)

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.

In the [paper](https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btw277) (taken from their [github](https://github.com/COMBINE-lab/RapMap)) about RapMap, an alignment/mapping tool for rna-seq reads to a reference genome, the dataset used for their benchmarks is described like this:

> 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](https://www.gencodegenes.org/releases/current.html), might that be the kind of thing they used? Would the reads simulated from these GTFs fit to these transcript FASTA files?

**Tags:** phylogenetics, read-mapping, transcriptome
> **Comments:**
> **username_1**: FYI, I took the liberty of asking Rob Patro to have someone from his team reply.  

---

## 2 answers

### Answer by username_3 on 2017-12-11. Score: 5 | Accepted answer

Thanks for your interest in RapMap.

At that time we were using flux simulator for simulating read sequence data. We used the genome and gtf file together as an input to flux.

I dug into the scripts and got hold of the gtf link `ftp://ftp.ensembl.org/pub/release-80/gtf/homo_sapiens/Homo_sapiens.GRCh38.80.gtf.gz`,
and the genome file link `ftp://ftp.ensembl.org/pub/release-80/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.toplevel.fa`.

We used `rsem-prepare-reference` to create the reference transcriptome file later in order to run RapMap and other transcriptome based quantification tools. I hope this helps.

PS: I am a coauthor of the RapMap paper.


---

### Answer by username_2 on 2017-11-08. Score: 1

If they generated reads from the transcriptome then the started with the FASTA version of the ENSEMBL transcriptome and then aligned the reads back to it. For a project like this I don't think that you need the GTF files, since you don't need to know the location of the transcript on the larger genomic reference. If you can't find an ENSEMBL transcriptome then you can use the GTF and the bedtools program to create a FASTA.

> **Comments:**
> **username_0**: The read simulator they used, Flux, can only generate reads from GTF format annotation and a genome, not from transcriptomes in FASTA format. For the time being I'm trying to work with the current GENCODE releases, which offer transcriptomes in fasta format, corresponding to their GTF annotations, but I will also look into your suggestion of using bedtools.  

---

