RT Journal
A1 Liu, Peng
A1 Ewald, Jessica
A1 Galvez, Jose Hector
A1 Head, Jessica
A1 Crump, Doug
A1 Bourque, Guillaume
A1 Basu, Niladri
A1 Xia, Jianguo
T1 Ultrafast functional profiling of RNA-seq data for nonmodel organisms
JF Genome Research 
JO Genome Research 
YR 2021 
FD April 01 
VO 31 
IS 4 
SP 713 
OP 720 
DO 10.1101/gr.269894.120 
UL http://genome.cshlp.org/content/31/4/713.abstract 
AB Computational time and cost remain a major bottleneck for RNA-seq data analysis of nonmodel organisms without reference genomes. To address this challenge, we have developed Seq2Fun, a novel, all-in-one, ultrafast tool to directly perform functional quantification of RNA-seq reads without transcriptome de novo assembly. The pipeline starts with raw read quality control: sequencing error correction, removing poly(A) tails, and joining overlapped paired-end reads. It then conducts a DNA-to-protein search by translating each read into all possible amino acid fragments and subsequently identifies possible homologous sequences in a well-curated protein database. Finally, the pipeline generates several informative outputs including gene abundance tables, pathway and species hit tables, an HTML report to visualize the results, and an output of clean reads annotated with mapped genes ready for downstream analysis. Seq2Fun does not have any intermediate steps of file writing and loading, making I/O very efficient. Seq2Fun is written in C++ and can run on a personal computer with a limited number of CPUs and memory. It can process >2,000,000 reads/min and is >120 times faster than conventional workflows based on de novo assembly, while maintaining high accuracy in our various test data sets.