A direct comparison of genome alignment and transcriptome pseudoalignment
- Creators
- Yi, Lynn
- Liu, Lauren
- Melsted, Páll
- Pachter, Lior
Abstract
Motivation: Genome alignment of reads is the first step of most genome analysis workflows. In the case of RNA-Seq, transcriptome pseudoalignment of reads is a fast alternative to genome alignment, but the different coordinate systems of the genome and transcriptome have made it difficult to perform direct comparisons between the approaches. Results: We have developed tools for converting genome alignments to transcriptome pseudoalignments, and conversely, for projecting transcriptome pseudoalignments to genome alignments. Using these tools, we performed a direct comparison of genome alignment with transcriptome pseudoalignment. We find that both approaches produce similar quantifications. This means that for many applications genome alignment and transcriptome pseudoalignment are interchangeable. Availability and Implementation: bam2tcc is a C++14 software for converting alignments in SAM/BAM format to transcript compatibility counts (TCCs) and is available at https://github.com/pachterlab/bam2tcc. kallisto genomebam is a user option of kallisto that outputs a sorted BAM file in genome coordinates as part of transcriptome pseudoalignment. The feature has been released with kallisto v0.44.0, and is available at https://pachterlab.github.io/kallisto/.
Additional Information
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license. bioRxiv preprint first posted online Oct. 16, 2018. Availability and Implementation: bam2tcc is available at https://github.com/pachterlab/bam2tcc. kallisto v0.44.0 containing the novel genomebam feature is available at https://pachterlab.github.io/kallisto/. The scripts and code used to regenerate our analysis are available at https://github.com/pachterlab/YLMP_2018. We thank Valentine Svensson for helpful feedback during the implementation of bam2tcc. Funding: LY was funded by the UCLA/Caltech MSTP, NIH T32 GM007616, NIH U19MH114830, the Lee Ramo Endowment, the Treadway Endowment, and the Hearst Endowment. LP was partly funded by U19MH114830.Attached Files
Submitted - 444620.full.pdf
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Additional details
- Eprint ID
- 90482
- Resolver ID
- CaltechAUTHORS:20181029-160959571
- UCLA-Caltech Medical Scientist Training Program
- T32 GM007616
- NIH Predoctoral Fellowship
- U19MH114830
- NIH
- Lee Ramo Endowment
- Treadway Endowment
- Hearst Endowment
- U19MH114830
- NIH
- Created
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2018-10-30Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field