Pipeline data

Pita is capable of using various types of information. This section describes which data types are currently supported.

Raw data

Two types of data generally should be present when running the pipeline:

  • RNA-seq

    Mapped RNA-seq data in bam files.

  • ChIP-seq

    Mapped ChIP-seq data in bam files. There are multiple types of ChIP-seq data. Pita was tested on H3K4 tri-methylations.

Annotation

  • Splice sites

    Splice sites counts for each bam file in the Raw data section, according to the following format

    Chr Start Stop Count
    Chr01 23000 23001 2

    Example script: https://github.com/simonvh/pita/blob/master/scripts/bam2splicecount

  • Assembled transcripts

    Transcript assembled based on RNA-seq data. For testing we used the tool stringtie on each seperate RNA-seq bam file (guided by a reference file) and merged them after.

    $ stringtie input.bam -G /path/to/geneModels.gff3 -o output.gtf (on each bam file)
$ stringtie --merge -G /path/to/geneModels.gff3 [list of gtf files]

  • ESTs & cDNA

    These two data types can be used as an input. For testing we retrieved the sequences from sources such as xenbase and ensembl. However just the sequences are not enough, we need the locations on the genome which requires mapping to the reference genome. We reccomend gmap to do this.

  • Protein sequences

    Protein sequences can be very informative to predict coding regions. Pita is not able to directly use the amino acid sequences so some preprocessing is required. Using blat the amino acids can be mapped to the genome resulting in the location of the proteins. Blat does a good job in mapping, however the splice sites are usually not great. It is recommended to correct the splice sites with scipio. Scipio uses the result psl file from Blat as an input file to generate a gff file with corrected splice sites. The resulting gff file can be used as an input file for Pita .

  • Existing gene models

    Existing gene models can be used to guide the annotation process and usually do not need any preprocessing. The prefered format is bed, but gff is supported as well.

References

  • Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT & Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads Nature Biotechnology 2015, doi:10.1038/nbt.3122
  • Wu, T. D., & Watanabe, C. K. (2005). GMAP: a genomic mapping and alignment program for mRNA and EST sequences. Bioinformatics (Oxford, England), 21(9), 1859–75. http://doi.org/10.1093/bioinformatics/bti310