Trinity --seqType fq --left reads_1.fq --right reads_2.fq --CPU 6 --max_memory 20G
Trinity: RNA-Seq De novo Assembly Application
Category
Published on
Abstract
Quick Guide for the Impatient
Trinity assembles transcript sequences from Illumina RNA-Seq data.
Download Trinity here.
Build Trinity by typing make : ; in the base installation directory.
Assemble RNA-Seq data like so:
Find assembled transcripts as: trinity_out_dir/trinity.fasta
Trinity on Galaxy
User Forum
Intro to Trinity
"Trinity, developed at the Broad Institute and the Hebrew University of Jerusalem, represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the transcriptional complexity at at a given gene or locus, and then processes each graph independently to extract full-length splicing isoforms and to tease apart transcripts derived from paralogous genes. Briefly, the process works like so:
-
Inchworm assembles the RNA-seq data into the unique sequences of transcripts, often generating full-length transcripts for a dominant isoform, but then reports just the unique portions of alternatively spliced transcripts.
-
Chrysalis clusters the Inchworm contigs into clusters and constructs complete de Bruijn graphs for each cluster. Each cluster represents the full transcriptonal complexity for a given gene (or sets of genes that share sequences in common). Chrysalis then partitions the full read set among these disjoint graphs.
-
Butterfly then processes the individual graphs in parallel, tracing the paths that reads and pairs of reads take within the graph, ultimately reporting full-length transcripts for alternatively spliced isoforms, and teasing apart transcripts that corresponds to paralogous genes."
Have a question - ask us
References
Cite this work
Researchers should cite this work as follows:
-
Grabherr MG; Brian Haas; Yassour M; Levin JZ; Thompson DA; Amit I; Adiconis X; Fan L; Raychowdhury R; Zeng Q; Chen Z; Mauceli E; Hacohen N; Gnirke A; Rhind N; Di Palma F; Birren BW; Nusbaum C; Lindblad-toh K; Friedman N; Regev A (2015), "Trinity: RNA-Seq De novo Assembly Application," https://ncihub.cancer.gov/resources/1026.