Tophat2 version download

In this article, homo sapiens reference genome from Ensembl database is used. For homo sapiens the file labeled toplevel combines all chromosomes. Download and uncompress the reference genome, using the following UNIX commands :. Before reads can be aligned, the reference FASTA files need to be preprocessed into an index that allows the aligner easy access. This procedure needs to be run only once for each reference genome used.

Since the downstream statistical analysis of differential expression relies on this table, carefully inspect and correct, if necessary the metadata table. In the call to tophat2, the option -o specifies the output directory, -p specifies the number of threads to use affect run times, vary depending on the resources available. The first argument is the name of the index. For experiments with paired-end reads, pairs of FASTQ files are given as separate arguments and the order in both arguments must match.

The commands can be executed by copy and paste in UNIX terminal. The list of the commands can also be stored in a text file and use UNIX source command.

BAM files are organized into a single directory. This scalability suggests that as read lengths grow, TopHat2 will continue to report accurate, sensitive alignment results and allow for robust downstream analysis. We believe that TopHat2 reports more accurate alignments than competing tools, using fewer computational resources.

RNA-seq experiments are becoming increasingly common and are now routinely used by many biologists. We expect that TopHat2 will provide these scientists with accurate results for use with expression analysis, gene discovery, and many other applications.

Given RNA-seq reads as input, TopHat2 begins by mapping reads against the known transcriptome, if an annotation file is provided. This transcriptome mapping improves the overall sensitivity and accuracy of the mapping.

It also gives the whole pipeline a significant speed increase, owing to the much smaller size of the transcriptome compared with that of the genome see Figure 6. After the transcriptome-mapping step, some reads remain unmapped because they are derived from unknown transcripts not present in the annotation, or because they contain many miscalled bases.

In addition, there may be poorly aligned reads that have been mapped to the wrong location. TopHat2 aligns these unmapped or potentially misaligned reads against the genome Figure 6 , step 2. Any reads contained entirely within exons will be mapped, whereas other spanning introns may not be. TopHat2 also provides an option to allow users to remap some of the mapped reads, depending on the edit distance values of these reads; that is, those reads whose edit distance is greater than or equal to a user-provided threshold will be treated as unmapped reads.

To accomplish this, the unmapped reads and previously mapped reads with low alignment scores are split into smaller non-overlapping segments 25 bp each by default which are then aligned against the genome Figure 6 , step 3. Tophat2 examines any cases in which the left and right segments of the same read are mapped within a user-defined maximum intron size usually between 50 and , bp.

When this pattern is detected, TopHat2 re-aligns the entire read sequence to that genomic region in order to identify the most likely locations of the splice sites Figure 6.

Using a similar approach, indels and fusion breakpoints are also detected in this step. The genomic sequences flanking these splice sites are concatenated, and the resulting spliced sequences are collected as a set of potential transcript fragments.

Any reads not mapped in the previous stages or mapped very poorly are then re-aligned with Bowtie2 [ 15 ] against this novel transcriptome. After these steps, some of the reads may have been aligned incorrectly by extending an exonic alignment a few bases into the adjacent intron Figure 1 ; Figure 6 , steps 3 to 5.

TopHat2 checks if such alignments extend into the introns identified in the split-alignment phase; if so, it can realign these reads to the adjacent exons instead. In the final stage, TopHat2 divides the reads into those with unique alignments and those with multiple alignments. For the multi-mapped reads, TopHat2 gathers statistical information for example, the number of supporting reads about the relevant splice junctions, insertions, and deletions, which it uses to recalculate the alignment score for each read.

Based on these new alignment scores, TopHat2 reports the most likely alignment locations for such multi-mapped reads. For paired-end reads, TopHat2 processes the two reads separately through the same mapping stages described above. In the final stage, the independently aligned reads are analyzed together to produce paired alignments, taking into consideration additional factors including fragment length and orientation.

For the experiments described in this study, the program version numbers were: TopHat2 2. For the specific parameters for each program, see Additional file 1 , Table S9, and for the source code of TopHat 2. Nat Methods. Genome Biol. Nucleic Acids Res. Genome Res. The Illumina Body Map 2. PLoS Biol. Nucleic acids Res. Google Scholar. Download references. Illumina Inc. You can also search for this author in PubMed Google Scholar.

Correspondence to Daehwan Kim. RK implemented the indel-alignment algorithms, with help from DK. All authors read and approved the final manuscript. Reprints and Permissions. Kim, D. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol 14, R36 Download citation.

Received : 15 November Revised : 05 April Accepted : 25 April Published : 25 April Anyone you share the following link with will be able to read this content:.

Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Skip to main content. Search all BMC articles Search. Download PDF. Background RNA-sequencing technologies [ 1 ], which sequence the RNA molecules being transcribed in cells, allow exploration of the process of transcription in exquisite detail.

Figure 1. Full size image. Results and discussion TopHat2 can use either Bowtie [ 17 ] or Bowtie2 [ 15 ] as its core read-alignment engine. Alignments of simulated reads error-free We generated 40,, paired-end reads and performed two sets of experiments, using: 1 20,, 'left' reads from the paired-end dataset Table 1 and 2 20,, pairs of reads Table 2. Table 1 Performance of TopHat2 and other spliced aligners on a set of 20 million bp, single-end reads, simulated based on transcripts from the entire human genome.

Full size table. Table 2 Performance of TopHat2 and other spliced aligners on a set of 20 million pairs of bp reads, simulated based on transcripts from the entire human genome.

Table 3 Performance of TopHat2 and other spliced aligners on single-end reads containing insertions and deletions indels of 1 to 3 bp. Table 4 Performance of TopHat2 and other spliced aligners on paired reads in which at least one of the reads contained insertions and deletions indels of 1 to 3 bp. Figure 2. Figure 3. Table 5 Expression levels of genes with pseudogene copies from Chen et al.

Figure 4. Figure 5. Conclusions Discovery of new genes and transcripts is a major objective in many RNA-seq experiments.

Methods Given RNA-seq reads as input, TopHat2 begins by mapping reads against the known transcriptome, if an annotation file is provided. Figure 6. TopHat2 pipeline. A: Yes! As of version 3. A: MATS 3. X can handle both non-replicates and replicates. A: New version of samtools deprecated -X option. Please use samtools v0. Users can map your reads independently using Tophat2 or any other aligners then feed rMATS with the resulting bam files. We strongly recommend that users map reads independently using their choice of aligner including Tophat2 to reduce the rMATS running time and to preserve their own mapping procedures.

Q: I have problem downloading Bowtie indexes for human and mouse A: Some browsers have a limit on downloadable file size. Use a different browser or download indexes directly from Linux command line. MATS 3.