Using Gabmap

AbstractGabmap is a freely available, open-source web application that analyzes the data of language variation, e.g. varying words for the same concepts, varying pronunciations for the same words, or varying frequencies of syntactic constructions in transcribed conversations. Gabmap is an integrated part of CLARIN (see e.g. http://portal.clarin.nl). This article summarizes Gabmap's basic functionality, adding material on some new features and reporting on the range of uses to which Gabmap has been put. Gabmap is modestly successful, and its popularity underscores the fact that the study of language variation has crossed a watershed concerning the acceptability of automated language analysis. Automated analysis not only improves researchers’ efficiency, it also improves the replicability of their analyses and allows them to focus on inferences to be drawn from analyses and other more abstract aspects of that study

Finlandssvenskars uppfattningar och åsikter om språklig variation – En webbenkät

The paper reports the results of a web survey that was conducted in order to study the perceptions of and attitudes toward dialectal variation of Swedish-speaking Finns. In the first part of the survey, the participants were asked to give labels to varieties of Finland-Swedish that they have come into contact with. In the second part, attitudes toward three of the self-reported varieties were elicited. The label-naming task was analyzed by means of common linguistic elements, e.g. the use of the word dialekt ‘dialect’, and the geographic distribution and coverage of the varieties. The results show that participants from southern parts of Finland tend to use labels covering larger geographic regions for their own variety, while participants from the region Ostrobothnia in western Finland use village names to a higher extent. The participants largely agree that a Finland-Swedish standard language exists; however, they seem to lack a common, unambiguous label. The attitudes were analyzed by means of attitudinal dimensions. The warmth dimension came out the strongest, which is in line with research showing that warmth judgments are primary in human cognition. In the Finnish context, the extraversion–introversion dimension also seems to be perceived as particularly important. People in the capital area receive negative evaluations in the warmth dimension and positive evaluations in the competence dimension from participants outside this area. In contrast, participants from the capital area gave positive warmth evaluations to speakers from other regions.</p

Using Gabmap

Gabmap is a freely available, open-source web application that analyzes the data of language variation, e.g. varying words for the same concepts, varying pronunciations for the same words, or varying frequencies of syntactic constructions in transcribed conversations. Gabmap is an integrated part of CLARIN (see e.g. http://portal.clarin.nl). This article summarizes Gabmap's basic functionality, adding material on some new features and reporting on the range of uses to which Gabmap has been put. Gabmap is modestly successful, and its popularity underscores the fact that the study of language variation has crossed a watershed concerning the acceptability of automated language analysis. Automated analysis not only improves researchers’ efficiency, it also improves the replicability of their analyses and allows them to focus on inferences to be drawn from analyses and other more abstract aspects of that study.</p

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment