Abstract
Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations. © 2020, The Author(s).

Abstract
RNA-sequencing (RNA-Seq) has become the technology of choice for whole-transcriptome profiling. However, processing the millions of sequence reads generated requires considerable bioinformatics skills and computational resources. At each step of the processing pipeline many tools are available, each with specific advantages and disadvantages. While using a specific combination of tools might be desirable, integrating the different tools can be time consuming, often due to specificities in the formats of input/output files required by the different programs. Here we present iRAP, an integrated RNA-seq analysis pipeline that allows the user to select and apply their preferred combination of existing tools for mapping reads, quantifying expression, testing for differential expression. iRAP also includes multiple tools for gene set enrichment analysis and generates web browsable reports of the results obtained in the different stages of the pipeline. Depending upon the application, iRAP can be used to quantify expression at the gene, exon or transcript level. iRAP is aimed at a broad group of users with basic bioinformatics training and requires little experience with the command line. Despite this, it also provides more advanced users with the ability to customise the options used by their chosen tools.

Abstract
The high levels of degradation characteristic of ancient DNA molecules severely hinder the recovery of endogenous DNA fragments and the discovery of genetic variation, limiting downstream population analyses. Optimization of read mapping strategies for ancient DNA is therefore essential to maximize the information we are able to recover from archaeological specimens. In this paper we assess Burrows-Wheeler Aligner (BWA) effectiveness for mapping of ancient DNA sequence data, comparing different sets of parameters and their effect on the number of endogenous sequences mapped and variants called. We also consider different filtering options for SNP calling, which include minimum values for depth of coverage and base quality in addition to mapping quality. Considering our results, as well as those of previous studies, we conclude that BWA-MEM is a good alternative to the current standard BWA-backtrack strategy for ancient DNA studies, especially when the computational resources are limited and time is a constraint.

Abstract
The orders Neuroptera and Raphidioptera include the species of insects known as lacewings and snake flies, respectively. In Portugal, these groups account for over 100 species, some of which are very difficult to identify by morphological analysis. This work is the first to sample and DNA sequence lacewings and snakeflies of Portugal. A reference collection was built with captured specimens that were identified morphologically. DNA barcode sequences of 658 bp were obtained from 243 specimens of 54 species. The results showed that most species can be successfully identified through DNA barcoding, with the exception of seven species of Chrysopidae (Neuroptera). Additionally, the first published distribution data are presented for Portugal for the neuropterans Gymnocnemia variegata (Schneider, 1845) and Myrmecaelurus (Myrmecaelurus) trigrammus (Pallas, 1771).

Abstract

Abstract
The study of phenotypic evolution in island birds following colonization is a classic topic in island biogeography. However, few studies explicitly test for the role of selection in shaping trait evolution in these taxa. Here, we studied the Azores woodpigeon (Columba palumbus azorica) to investigate differences between island and mainland populations, between females and males, and interactions between geographical origin and sex, by using spectrophotometry to quantify plumage colour and linear measurements to examine external and skeletal morphology. We further tested if selection explains the observed patterns by comparing phenotypic differentiation to genome-wide neutral differentiation. Our findings are consistent with several predictions of morphological evolution in island birds, namely differences in bill, flight and leg morphology and coloration differences between island and mainland birds. Interestingly, some plumage and morphological traits that differ between females and males respond differently according to geographical origin. Sexual dimorphism in colour saturation is more pronounced in the mainland, but this is driven by selection on female plumage coloration. Differences in flight morphology between females and males are also more pronounced in the mainland, possibly to accommodate contrasting pressures between migration and flight displays. Overall, our results suggest that phenotypic differentiation between mainland and island populations leading to divergent sexual dimorphism patterns can arise from selection acting on both females and males on traits that are likely under the influence of natural and sexual selection.