RNA-Bloom is a fast and memory-efficient de novo transcript sequence assembler. It is designed for the following sequencing data types:

• paired-end bulk RNA-seq (strand-specific/agnostic)
• paired-end single-cell RNA-seq (strand-specific/agnostic)
• nanopore RNA-seq (PCR cDNA/direct cDNA/direct RNA)

Written by Ka Ming Nip 📧

©️ 2018-2020 Canada's Michael Smith Genome Sciences Centre, BC Cancer

---

Dependency 📌

• Java SE Runtime Environment (JRE) 8

• External software used:

software	short reads	long reads
minimap2	required	required
Racon	not used	required
ntCard >=1.2.1	required for -ntcard	required for -ntcard

⚠️ Their executables must be accessible from your PATH!

Installation 🔧

RNA-Bloom can be installed in two ways:

(A) install with conda:

conda install -c bioconda rnabloom

RNA-Bloom can be run as rnabloom ...

(B) download from GitHub:

1. Download the binary tarball rnabloom_vX.X.X.tar.gz from the releases section.
2. Extract the downloaded tarball with the command:

tar -zxf rnabloom_vX.X.X.tar.gz

RNA-Bloom can be run as java -jar /path/to/RNA-Bloom.jar ...

Quick Start for Short Reads 🏃

⚠️ Input reads must be in either FASTQ or FASTA format and may be compressed with GZIP.

(A) assemble bulk RNA-seq data:

java -jar RNA-Bloom.jar -left LEFT.fastq -right RIGHT.fastq -revcomp-right -ntcard -t THREADS -outdir OUTDIR

(B) assemble single-cell RNA-seq data:

java -jar RNA-Bloom.jar -pool READSLIST.txt -revcomp-right -ntcard -t THREADS -outdir OUTDIR

RNA-Bloom was tested on Smart-seq2 and SMARTer datasets.

file format for the -pool option:

This text file is expected to have 3 columns, ie.

column 1	column 2	column 3
cell ID	path of left reads	path of right reads

Columns are separated by space/tab characters, eg.

cell1 /path/to/cell1/left.fastq /path/to/cell1/right.fastq
cell2 /path/to/cell2/left.fastq /path/to/cell2/right.fastq
cell3 /path/to/cell3/left.fastq /path/to/cell3/right.fastq

(C) strand-specific assembly:

java -jar RNA-Bloom.jar -stranded ...

The -stranded option indicates that input reads are strand-specific.

Strand-specific reads are typically in the F2R1 orientation, where /2 denotes left reads in forward orientation and /1 denotes right reads in reverse orientation.

Configure the read file paths accordingly for bulk RNA-seq data:

-left /path/to/reads_2.fastq -right /path/to/reads_1.fastq

and for scRNA-seq data:

cell1 /path/to/cell1/reads_2.fastq /path/to/cell1/reads_1.fastq

(D) reference-guided assembly:

java -jar RNA-Bloom.jar -ref TRANSCRIPTS.fasta ...

The -ref option specifies the reference transcriptome FASTA file for guiding short-read assembly.

Quick Start for Nanopore Reads 🏃

(A) assemble nanopore PCR cDNA sequencing data:

java -jar RNA-Bloom.jar -long READS.fasta -ntcard -t THREADS -outdir OUTDIR

Input reads are expected to be in a mix of both forward and reverse orientations.

(B) assemble nanopore direct cDNA sequencing data:

java -jar RNA-Bloom.jar -long READS.fasta -stranded -revcomp-long -ntcard -t THREADS -outdir OUTDIR

Input reads are expected to be only in the reverse orientation.

(C) assemble nanopore direct RNA sequencing data:

java -jar RNA-Bloom.jar -long READS.fasta -stranded -ntcard -t THREADS -outdir OUTDIR

Input reads are expected to be only in the forward orientation.

By default, uracil (U) is written as T. Use the -uracil option to write U instead of T in the output assembly.

ntCard v1.2.1 supports uracil in reads.

General Settings ⚙️

(A) set Bloom filter sizes automatically:

java -jar RNA-Bloom.jar -fpr 0.01 -nk 28077715 ...

This sets the size of Bloom filters automatically to accommodate 28,077,715 unique k-mers for a max false positive rate (FPR) of 1%.

Instead of specifying the exact number of k-mers, you may use ntCard to count k-mers:

java -jar RNA-Bloom.jar -fpr 0.01 -ntcard ...

To use the -ntcard option, ntcard must be found in your PATH.

As a rule of thumb, a lower FPR may result in a better assembly but requires more memory for a larger Bloom filter.

(B) set the total size of Bloom filters:

java -jar RNA-Bloom.jar -mem 10 ...

This sets the total size to 10 GB. If neither -nk, -ntcard, or -mem are used, then the total size is configured based on the size of input read files.

(C) stop at an intermediate stage:

java -jar RNA-Bloom.jar -stage N ...

N	short reads	long reads
1	construct graph	construct graph
2	assemble fragments	correct reads
3	assemble transcripts	assemble transcripts

This is a very useful option if you only want to assemble fragments or correct long reads (ie. with -stage 2)!

(D) list all available options in RNA-Bloom:

java -jar RNA-Bloom.jar -help

(E) limit the size of Java heap:

java -Xmx2g -jar RNA-Bloom.jar ...

or if you installed with conda:

export JAVA_TOOL_OPTIONS="-Xmx2g"
rnabloom ...

This limits the maximum Java heap to 2 GB with the -Xmx option. Note that java options has no effect on Bloom filter sizes.

See documentation for other JVM options.

Implementation 📝

RNA-Bloom is written in Java with Apache NetBeans IDE. It uses the Apache Commons CLI library and JGraphT core library.

Citing RNA-Bloom 📜

If you use RNA-Bloom in your work, please cite us:

Ka Ming Nip, Readman Chiu, Chen Yang, Justin Chu, Hamid Mohamadi, Rene L Warren, Inanc Birol. (2019) RNA-Bloom provides lightweight reference-free transcriptome assembly for single cells. bioRxiv 701607. doi: https://doi.org/10.1101/701607

---