SSP Transcriptome Assembler from Tehran, TIGER, PEGASAS Genome Assemblers

SSP Transcriptome Assembler from Tehran, TIGER, PEGASAS Genome Assemblers

More genome and transcritome assembly methods are getting published than we can keep track of. They all claim to be better than the existing ones. We are reporting them for the time being without any detailed analysis.

Tiger: tiled iterative genome assembler and approximate multi-genome aligner (h/t: @assemblathon)

Sequence assembly and alignments are two important stepping stones for comparative genomics. With the fast adoption of the next-generation sequencing (NGS) technologies and the coming of the third-generation sequencing (TGS) technologies, genomics has provided us with an unprecedented opportunity to answer fundamental questions in biology and elucidate human diseases. However, most de novo assemblers require an enormous amount of computational resource, which is not readily available to most research groups and medical personnel. Moreover, there has been little progress on sequence assembly qualities, especially for genomes having high repetitions. As more affordable raw data and assembled genomes are accessible to the community, there is an emerging demand for genome searches among the big amount of divergent genomes in gene banks. The genomes can be in the form of raw reads, unfinished/low-quality assemblies, or completed genomes, on which traditional multi-sequence alignment tools may not be suitable to perform similarity searches. Yet there are few research studies aiming at meeting this demand. We have developed a novel de novo assembly framework, called Tiger assembler, which adapts to available computing resources by iteratively decomposing the assembly problem into sub-problems. Our method can flexibly embed different assemblers for various types of target genomes. Using the sequence data from a human chromosome, our results show that Tiger can achieve much better NG50s, better genome coverage, and slightly higher errors, as compared to Velvet and SOAPdenovo, using a modest amount of memory that is available in commodity computers today. We also experimented with a real de novo assembly, i.e., the E. mexicana genome, and demonstrated the strength of our work. The N50s of our contigs and scaffolds by Tiger were 7 and 57 times longer than those by SOAPdenovo. On the other hand, the assembly done by ALLPATHS-LG had only one- third genome size. We also developed a multi-genome sequence aligner, called Tiger aligner, able to perform fast similarity checks among multiple genomes with distant biological relationship and low quality raw data. Practical applications of our tool are demonstrated through experiments. The performance of Tiger aligner on traditional multi-sequence alignments is also compared against existing works, MUMmer and SOAPaligner. The results show the practicality and strengths of our tool. ? Most state-of-the-art assemblers that can achieve relatively high assembly quality need an excessive amount of computing resource (in particular, memory) that is not readily available to most researchers. Tiger assembler provides the only known viable path to utilize NGS de novo assemblers that require more memory than that is present in available computers. Evaluation results demonstrate the feasibility of getting better quality results with low memory footprint and the scalability of using distributed commodity computers. The quantity explosion of genomes makes existing multi-sequence aligners impractical to check similarities among genomes with different characteristics in terms of evolutionary relationship and sequence completeness. Current pairwise sequence aligners cannot cope with them without big revisions because of the inherently algorithmic limitations. Tiger aligner is the first known work invented to deal with the multi-genome problems, leveraging the feature-based image.


In twitter, @srbehera11 forwarded us a new RNA-seq algorithm paper from Tehran.

SSP: An interval integer linear programming for de novo transcriptome assembly and isoform discovery of RNA-seq reads

Recent advances in the sequencing technologies have provided a handful of RNA-seq datasets for transcriptome analysis. However, reconstruction of full- length isoforms and estimation of the expression level of transcripts with a low cost are challenging tasks. We propose a novel de novo method named SSP that incorporates interval integer linear programming to resolve alternatively spliced isoforms and reconstruct the whole transcriptome from short reads. Experimental results show that SSP is fast and precise in determining different alternatively spliced isoforms along with the estimation of reconstructed transcript abundances. The SSP software package is available at


Here is another one from Ontario.

Link (h/t: @assemblathon)

The enormous amount of short reads produced by next generation sequencing (NGS) techniques such as Roche/454, Illumina/Solexa and SOLiD sequencing opened the possibility of de novo genome assembly. Some of the de novo genome assemblers (e.g., Edena, SGA) use an overlap graph approach to assemble a genome, while others (e.g., ABySS and SOAPdenovo) use a de Bruijn graph approach. Currently, the approaches based on the de Bruijn graph are the most successful, yet their performance is far from being able to assemble entire genomic sequences. We developed a new overlap graph based genome assembler called Paired-End Genome ASsembly Using Short-sequences (PEGASUS) for paired- end short reads produced by NGS techniques. PEGASUS uses a minimum cost network flow approach to predict the copy count of the input reads more precisely than other algorithms. With the help of accurate copy count and mate pair support, PEGASUS can accurately unscramble the paths in the overlap graph that correspond to DNA sequences. PEGASUS exhibits comparable and in many cases better performance than the leading genome assemblers.

Edit. We are including relevant twitter discussions.


1. @pathogenomenick said -

“@assemblathon hmm, numerous factual errors in the abstract!”

2. @sebhtml pointed out that the above method is similar to:

Maximum Likelihood Genome Assembly - Paul Medvedev1 and Michael Brudno


@assemblathon forwarded another one:

MS thesis:

Genome Assembly: Scaffolding Guided by Related Genomes

Genomic research relies on computers to process large amounts of genomic data. In order to digitize such data, the genomes have to be sequenced and assembled. Modern sequencing technologies allow fast and inexpensive sequencing. Sequencing machines produce multiple chunks of sequences called reads, which are assembled into contigs, and then further into larger pieces called scaffolds. The process of scaffolding contigs often requires obtaining additional data through lab work, which is both time-consuming and expensive. The purpose of this thesis is to assess whether contigs can be scaffolded with the aid of previously sequenced related genomes, and whether the use of multiple related genomes can increase the precision of the resulting scaffolds. A pipeline with a simple, prototypical algorithm was developed to process contigs using information from related genomes. This pipeline produces scaffolds and provides an evaluation of these. Contigs from 4 bacterial sequencing projects were scaffolded with 10 related genomes as guides for each bacterium. The results showed that using multiple guiding genomes, which were closely related to the target genome, enabled scaffolds to be produced with few errors.

?@OmicsOmicsBlog comments:

@assemblathon a bit of an odd duck, in that little of the presented data is relevant to supposed purpose (assessing with RAD markers)

Written by M. //