## Posters

**An in-silico framework for comparing and validating transcripts predicted from single and paired-end reads**, Anna Paola Carrieri, Stefano Beretta, Gianluca Della Vedova, Ernesto Picardi, Yuri Pirola, Raffaella Rizzi, Graziano Pesole, and Paola Bonizzoni,*NGS 2012*(poster and abstract).- With the advent of high-throughput sequencing of transcriptome (RNA-Seq), different computational methods that use RNA-Seq data to assemble full-length mRNA isoforms have been proposed, albeit not solving completely the problem. We have analyzed some of the most used available tools, evaluating their performance and accuracy.

Our experimental analysis reveals that using GSNAP instead of TopHat gives more specific predictions with also a minor (but statistically inconclusive) improvement in sensitivity.

We plan to extend our study (i) by introducing some alternatives to EVAL for comparing predictions, (ii) by considering different kinds of simulated data (more coverage levels and/or errors), as well as real data, and (iii) by analyzing in more detail the structure of predicted transcripts since a preliminary study in this direction reveals that the actual methods have various shortcomings in assembling transcripts.

- With the advent of high-throughput sequencing of transcriptome (RNA-Seq), different computational methods that use RNA-Seq data to assemble full-length mRNA isoforms have been proposed, albeit not solving completely the problem. We have analyzed some of the most used available tools, evaluating their performance and accuracy.

## Talks

**Detection of long noncoding (lncRNA) involved in RNA-Seq isoforms**, Hassan Mahmoud ,*DISCO,*May 28, 2015 (slides).- The recent discovery showed that the human and other mammalian genomes produce thousands of mRNA-like molecules namely, long noncoding RNAs (lncRNAs). Almost on a weekly basis, many biological studies detected that lncRNA is to be up or down-regulated in a particular disease. However, these lncRNAs which lack significant protein-coding capacity have been implicated in a wide range of biological functions through diverse and as yet poorly understood molecular mechanisms. The majority of human genes are alternatively spliced in a highly tissue and cell type–specific manner essential for generating protein diversity. The production of alternative splicing mRNAs is regulated by combinatorial use of multiple cis-acting RNA elements along the precursor mRNA (pre-mRNA). In this talk, I will show the concepts and subtypes of lncRNA, their role in gene regulation and their relation to alternative splicing, and the bioinformatics tools used for detecting lncRNA mainly from sequencing isoforms.

**Covering pairs in directed acyclic graphs**, Yuri Pirola,*LATA 2014*(slides).- The Minimum Path Cover problem on directed acyclic graphs (DAGs) is a classical problem that provides a clear and simple mathematical formulation for several applications in different areas and that has an efficient algorithmic solution. In this paper, we study the computational complexity of two constrained variants of Minimum Path Cover motivated by the recent introduction of next-generation sequencing technologies in bioinformatics. The first problem (MinPCRP), given a DAG and a set of pairs of vertices, asks for a minimum cardinality set of paths “covering” all the vertices such that both vertices of each pair belong to the same path. For this problem, we show that, while it is NP-hard to compute if there exists a solution consisting of at most three paths, it is possible to decide in polynomial time whether a solution consisting of at most two paths exists. The second problem (MaxRPSP), given a DAG and a set of pairs of vertices, asks for a single path containing the maximum number of the given pairs of vertices. We show its NP-hardness and also its W[1]-hardness when parametrized by the number of covered pairs. On the positive side, we give a fixed-parameter algorithm when the parameter is the maximum overlapping degree, a natural parameter in the bioinformatics applications of the problem.

**Haplotype-based prediction of gene alleles using pedigrees and SNP genotypes**, Yuri Pirola,*ACM-BCB 2013*(slides).- Computational methods for gene allele prediction have been proposed to substitute dedicated and expensive assays with cheaper in-silico analyses that operate on routinely collected data, such as SNP genotypes. Most of these methods are tailored to the needs and characteristics of human genetic studies where they achieve good prediction accuracy. However, genomic analyses are becoming increasingly important in livestock species too. For livestock species generally the underlying—usually quite large and complex—pedigree is known and available; this information is not fully exploited by current allele prediction methods.

In this work, we propose a new gene allele prediction method based on a simple, but robust, combinatorial formulation for the problem of discovering haplotype-allele associations. The inherent uncertainty of the haplotype inference process is reduced by taking into account the inheritance of gene alleles across the population pedigree while genotypes are phased. The accuracy of the method has been extensively evaluated on a representative real-world livestock dataset under several scenarios and choices of parameters. The median error rate ranged from 0.0537 to 0.0896, with an average of 0.0678; this is 21% better than another state-of-the-art prediction algorithm that does not use the pedigree information. The experimental results support the validity of the proposed approach and, in particular, of the use of pedigree information in gene allele predictions.

- Computational methods for gene allele prediction have been proposed to substitute dedicated and expensive assays with cheaper in-silico analyses that operate on routinely collected data, such as SNP genotypes. Most of these methods are tailored to the needs and characteristics of human genetic studies where they achieve good prediction accuracy. However, genomic analyses are becoming increasingly important in livestock species too. For livestock species generally the underlying—usually quite large and complex—pedigree is known and available; this information is not fully exploited by current allele prediction methods.
**A fast and practical approach to genotype phasing and imputation on a pedigree with erroneous and incomplete information**, Yuri Pirola,*ICCABS 2012*(slides).- This work proposes the Min-Recombinant Haplotype Configuration with Bounded Errors problem (MRHCE), which extends the original Min-Recombinant Haplotype Configuration formulation by incorporating two common characteristics of real data: errors and missing genotypes (including untyped individuals). We describe a practical algorithm for MRHCE that is based on a reduction to the Satisfiability problem (SAT) and exploits recent advances in the constraint programming literature. An experimental analysis demonstrates the soundness of our model and the effectiveness of the algorithm under several scenarios. The analysis on real data and the comparison with state-of-the-art programs reveals that our approach couples better scalability to large and complex pedigrees with the explicit inclusion of genotyping errors into the model. The software, released under the GNU General Public License, can be freely downloaded from this page.

**Basic Algorithmic Aspects of NGS data analysis**, Gianluca Della Vedova,*NGS Milan Meeting*, July 17, 2012 (slides).- A short tutorial on the Burrows-Wheeler Transform and its uses in Bioinformatics.

**A Novel Perspective in Algorithmic Combinatorial Methods for Phasing Populations in a Coalescent Model**, Paola Bonizzoni,*(invited talk)**ICCABS 2011*.**PIntron: a fast method for gene structure prediction via maximal pairings of a pattern and a text**, Yuri Pirola,*ICCABS 2011*(slides).- In this work, we propose a novel pipeline for computational gene-structure prediction based on spliced alignment of expressed sequences (ESTs and mRNAs). This pipeline, called
**PIntron**, is composed by four steps: Firstly, alternative alignments of expressed sequences to a reference genomic sequence are implicitly computed and represented in a graph (called embedding graph) by a novel fast spliced alignment procedure. Secondly, biologically meaningful alignments are extracted. Then, a consensus gene structure induced by the previously computed alignments is determined based on a parsimony principle. Finally, the resulting introns are reconciliated and classified according to general biological criteria. The software, released under the GNU Affero General Public License, can be freely downloaded from this page.

- In this work, we propose a novel pipeline for computational gene-structure prediction based on spliced alignment of expressed sequences (ESTs and mRNAs). This pipeline, called
**Haplotype Inference on Pedigrees with Recombinations and Mutations**, Yuri Pirola,*WABI 2010*(slides).- The work proposes a new combinatorial formulation for haplotype inference on general pedigrees that generalizes the existing combinatorial ones to a more realistic settings. We prove an approximation-preserving reduction from this problem, called
**Minimum Change Haplotype Configuration**(MCHC), to a well-known coding theory problem, namely the Nearest Codeword Problem. This reduction automatically implies the approximability of MCHC within a factor O(n/log n) and, more importantly, it leads to a new very efficient heuristic algorithm that has been experimentally compared with other state-of-the-art HI methods. The software implementing the heuristic is freely available at this page under the GNU General Public License.

- The work proposes a new combinatorial formulation for haplotype inference on general pedigrees that generalizes the existing combinatorial ones to a more realistic settings. We prove an approximation-preserving reduction from this problem, called
**Minimum Factorization Agreement of Spliced ESTs**, Yuri Pirola,*WABI 2009*(slides).- The work presents a new parsimony-based formulation for the problem of choosing the best alignment of an expressed sequence against a genomic sequence exploiting the redundancy of current expressed sequence databases. A preliminary experimental evaluation of the formulation and the related algorithm shows their applicability on real instances. The implementation of this approach is integrated in our software PIntron.

**Pure Parsimony Xor Haplotyping**, Yuri Pirola,*ISBRA 2009*(slides).- In this work we addressed the problem of haplotype inference from xor genotypes under the pure parsimony assumption. Exact algorithms for restricted instances, a fixed parameter algorithm, an approximation algorithm, and an effective heuristic have been proposed. A prototypical implementation of the heuristic is freely available at this page under the GNU General Public License.