dataesr/scientific-paragraphs-categorization huggingface dataset:
; https://doi. org/10. 1101/103010 doi: bioRxiv preprint 8 analysis, significant SNPs within 1 Mbp from each other where grouped into a common selection signature (FDR 1%). Candidate genes were identified in regions containing 10 or more significant SNPs. For hapFLK, a number of haplotype clusters has to be specified in order to fit the  Scheet and  Stephens model  (Scheet and Stephens, 2006). This number was set to 30, from results obtained using the cross validation procedure included in the fastPHASE software. P-values for hapFLK were obtained by fitting a chi-squared distribution to the empirical distribution as explained in ref. (Boitard et al. , 2016)  using the script available on the hapflk software web page. For the hapFLK analysis, regions were constructed from significant SNPs (FDR 5%) and grouped together if they were 1 Mbp or less apart.
1 Cycle Sequencing Kit (http://www. appliedbiosystems. com). The primers are listed in Supplementary Table  2. Sequences from three animals from each breed exhibiting a selection signature were aligned against scaffold 00839 of the Ovis aries musimon assembly (GenBank accession HG925721. 1), which we found of better quality than the OAR3. 1 reference genome, using CLC software and allowed the detection of polymorphisms. The discovered polymorphisms were genotyped for all the animals of the relevant breeds by sequencing purified PCR products with internal primers using the same protocol. The sheep genome browser from EBI (www. ensembl. org) was used to determine conserved regions through 39 eutherian mammals and calculate GERP scores. CC-BY-ND 4. 0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
The Ouessant sheep breed has historically been isolated and consequently has accumulated substantial drift. Its position in the tree is consistent with it having a distant origin from the other breeds in the data set. The Ouessant breed possibly originated from a first wave of colonization after domestication, as has been shown for other ancient European breeds of sheep such as the Soay sheep  (Chessa et al. , 2009). However, its positioning in the population tree might not be very reliable due its long branch length. The other highly inbred breed is the Mérinos de Rambouillet. This breed consists of a single flock of animals that has been raised without the introduction of additional animals since 1786. Although it has a very long branch in the population tree, it clusters with the other Merino population in the dataset, the Mérinos d'Arles.
The migration edge from the Mérinos de Rambouillet branch to the branch of both Île de France and Berrichon du Cher breeds is likely representative of the crossing of these breeds with Merinos in the nineteenth century to improve wool quality  (Porter, 2002). The migration edge from the Roussin de la Hague branch to the branch with Texel, Rouge de l'Ouest, Île de France and Berrichon du Cher breeds could come from the use of British breeds to crossbreed in the eighteenth century to improve meat production  (Porter, 2002). However this is difficult to confirm because the main British breeds involved, the Leicester Longwool and Southdown, are not part of our dataset nor of the SheepHapMap dataset. Finally, the migration branch from the Île de France to Mourerous breed was an unexpected result and might be due to.
French sheep populations and the meeting of European sheep domestication routes To place the population structure of French sheep into the context of European population diversity, population tree with mixture events and individual ancestry coefficients were estimated using European sheep breeds from the SheepHapMap project and included the as the French data set downscaled to medium density SNP information. The maximum likelihood population tree with no migration events (Figure  4  As when considering French breeds only, the tree obtained from the inclusion of the SheepHapMap breeds separated into: southern breeds, which included Spanish and Italian breeds;. CC-BY-ND 4. 0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
Only a few northern breeds had some more. CC-BY-ND 4. 0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 25, 2017. ; https://doi. org/10. 1101/103010 doi: bioRxiv preprint 16 elevated haplotype diversity, which allowed detecting selection when included with the southern breed. Interestingly, the selection signature in this region looked quite widespread for the same haplotype in most of the breeds in the dataset. As only three signatures were specific to analyzing all breeds together, we then focused our inference on the analyses performed in each group separately. We had more power to detect signatures of selection when separating breeds into the two groups: for FLK and hapFLK we detected 61 and 26 regions respectively for northern sheep populations and 65 and 42 regions for southern sheep populations.
Origin of the causal mutation in MSTN In the case of MSTN, the causal mutation is a SNP that is part of the HD SNP array used in our study (rs408469734). We found that it was the SNP showing the most significant FLK signal of the corresponding selection signature, and local population trees highlighted the Texel breed as being the selected population (page 14 of Supplementary Table  3 ). As it is the causative mutation, our dataset allows us to highlight the evolutionary history of this particular mutation: we found this SNP segregating in another meat breed, the Rouge de l'Ouest where it is carried by a similar but smaller haplotype than in the Texel. To evaluate the spread of the signal due to the selection in Texel, we conducted a new FLK analysis on chromosome 2 with all animals except the Texel sheep.
In Soay sheep, horn type (horns or scurs) and horn length was associated with the same region on chromosome 10 which was mapped to a single candidate gene, RXFP2  (Johnston et al. , 2011). Later, a single SNP was found to be highly predictive for horns (dominant when inherited maternally) in Australian Merino sheep on chromosome 10  (Dominik et al. , 2012). A synonymous mutation, p. P375 (c. 1125A > G) in Tan and Suffolk sheep was found to be associated with the appearance or absence of horns  (Wang et al. , 2014). When comparing horned and polled animals from seven Swiss breeds of sheep a 1833 bp insertion in a 4 kb region at the 3 prime end of RXFP2 was found only in polled animals  (Wiedemar and Drogemuller, 2015). Finally, the RXPF2 region was detected as a signature of selection in different population groups of the SheepHapMap dataset  (Kijas et al.
, 2012; Fariello et al. , 2014). The haplotype cluster frequency plots from those breeds under selection highlighted the complexity of selection in this region. The signal in our study was detected in all (page 28 of Supplementary Table  3 ) and separate analyses of northern and southern sheep with the two most significant SNPs in the southern analyses within RXFP2 (both intronic mutations) while the signal from hapflk results of northern sheep peaked 89 Kb before the gene. None of the northern breeds included in our dataset are horned, and the reason for detecting a signature here is because different haplotypes have been selected on within this region. When we looked at the region extending 100 kbp on either side of RXFP2, while the SNP frequencies within the gene were similar among northern sheep and other polled southern sheep, in the 100 kbp before the gene there were four distinct haplotypes in polled French sheep.
; https://doi. org/10. 1101/103010 doi: bioRxiv preprint 24 pheomelanin is produced depending on whether an agonist, the melanocyte stimulating hormone (α-MSH), or antagonist, the agouti signalling protein (ASIP), respectively bind to the melanocortin 1 receptor (MC1R)  (Ducrest et al. , 2008). The melanosomes transfer melanin to keratinocytes, the most predominant cell type in the outer layer of skin, the epidermis  (Birbeck et al. , 1956). Keratinocytes can then incorporate melanin  (Forrest et al. , 1985). For example, it has been shown in a study of Asiatic sheep that black individuals had only eumelanin present in their wool  (Aliev et al. , 1990). Our analysis revealed that selection in this region affected the only three black faced breeds in our dataset: the Romanov, the Suffolk and the Noire du Velay.
Furthermore, haplotype diversity plots showed they were clearly selected on different haplotypes (Figure  2A, B ). To test whether these three breeds were selected not only on different haplotypes but also on different mutations in MC1R we resequenced individuals from these breeds as well as a breed not found to be selected in this region, the Texel. Sequencing of 6 894 bp of the MC1R region and genotyping of the Noire du Velay, Romanov, Suffolk and Texel breeds allowed us to generate a reference sequence (EMBL accession number LT594967) with 2 remaining N blocks of 270 and 261 nucleotides in the 5' region. It exhibits a unique open reading frame, which is consistent with the literature  (Fontanesi et al. , 2011). We identified a potential TATA box with a "TATAAA" motif ( at positions 14 229 176-14 229 181), 2 522 bp before the start codon and a potential polyadenylation signal "AATAAA" (at positions 14 233 015-14 233 020).
Therefore we can assume that the 5'UTR of the sheep MC1R transcript is about 2 500 bp long and the 3'UTR around 500 bp long. Few data are present for mammalian 5'UTR of. CC-BY-ND 4. 0 International license a certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under The copyright holder for this preprint (which was not this version posted January 25, 2017. ; https://doi. org/10. 1101/103010 doi: bioRxiv preprint 25 MC1R transcripts. The NM_002386. 3 human transcript also shows a long 5'UTR (1 380 bp) and a 766 bp 3'UTR. The deduced MC1R sheep protein is 317 amino acids, the same number as in cattle (Bos Taurus) with a 96% identity between the two proteins. Our sequences allowed us to detect and further genotype six SNPs and one 11 bp insertion (Figure  2C ) (dbSNP accession numbers ss# 1996900605 to 1996900611).
In particular, we have showed that some of these regions have been targets of selection on different mutations, in independent genetic pools. This demonstrates the importance of these adaptive regions for agronomical and biological traits in sheep and most likely in other mammalian species. Working with a large set of diverse populations allows to reveal at least partially the history of adaptive mutations and in one particular case through selection on adaptive introgression. Finally, we believe that the combination of this dataset with other likely to come offers great prospects to decipher the history of animal domestication, and its relation to the human neolithic expansion.
) showed that French sheep complement the SheepHapMap dataset in the European sheep population tree. Most of the breeds in our dataset added to the global diversity, as they tend to root in internal branches of the population tree, either within northern or southern breeds (e. g. the Berrichon du Cher/Île de France and Causse du Lot/Rava/Limousine respectively) or at the basis of the population tree (e. g. the Ouessant or Romanov breeds). The other French breeds branched in population groups that are already present in the SheepHapMap: the Corsican breed is closely related to Italian breeds, and the Sardinian Ancestral Black in particular; the other cases corresponded to breeds that are also found in other countries and the population tree reflects the diversity within these breeds between countries (examples include the French and Irish Suffolk populations, the German, Scottish, New Zealand and French Texel sheep populations, and the Australian Merino, Mérino d'Arles and Mérino de Rambouillet breeds).
Acknowledgements CMR benefited from a joint grant from the  European Commission  and the  Swedish University of Agricultural Sciences , within the framework of the  Erasmus Mundus joint doctorate "EGS-ABG ". This work was funded by the  Animal Genetics division  from the  French National Institute for Agricultural Research (INRA) , the  European 7th Framework Programme  ( 3SR  project) and the CORAM members ( OPA project lead by Jérôme Raoul ). The biological samples for the Merinos de Rambouillet were obtained thanks to the  CRB-Anim infrastructure ,  ANR-11-INBS-0003 , funded by the  French National Research Agency  in the frame of the ' Investing for the Future' program. The funders had no role in study design, and analysis, decision to publish, or preparation of the manuscript. We deeply appreciated the involvement of various breeding organizations for their assistance in sample collection (France Génétique Elevage http://en.
2) and discusses its relevance for this context. Section 2. 3 reviews existing estimation techniques for the LBM and discusses their advantages and limitations. In Section 3 we introduce the exact ICL along with a greedy algorithm for inference purposes. We also draw strong parallels with the approach of  Wyse & Friel (2012)  in this section, and highlight the sensible and pragmatic nature of the algorithm. The computational complexity of the algorithm is discussed in Section 3. 4. In Section 3. 6 we show how large computational savings can be made over a naive implementation of this algorithm. Section 4 compares the proposed approach with the competing MCMC algorithm through a simulation study. Section 5 applies the approach to a number of datasets. We conclude with a discussion. 2 Bipartite networks and the latent blockmodel.
Study set-up The data was generated from the model outlined in Section 2, with K = 5 and G = 5. The label distributions were chosen as ω k = 1/5, k = 1,. , 5 and ρ g = 1/5, g = 1,. , 5. The node sets were chosen to be of size N = 100 and M = 100, giving a 100 × 100 adjacency matrix. Using the absent/present linking attribute outlined in Section 3. 2, the ties were generated so as to give different levels of overlap in the blocks. There are five blocks of varying clarity in the matrix following θ kg = 1 -q if k = g q otherwise where we let q vary from 0. 0125 to 0. 5 in steps of 0. 0125, giving 40 values of q in total. As q gets closer to 0. 5 the clustering task becomes more difficult, as the probability of a tie becomes constant across all blocks. Twenty datasets were generated at each value of q.
The pruned algorithm is usually about 10 times faster than the basic greedy algorithm. Figure  2  shows the average value of the normalized mutual information over the twenty datasets for each value of q for each of the algorithms. The MCMC algorithm is shown in blue, the greedy algorithm in red and the pruned greedy algorithm in green. It can be seen that as the value of q approaches 0. 5, the greedy algorithms slightly outperform the MCMC algorithm, with the MCMC outperforming the greedy algorithm around q = 0. 35. However, the observation most of note here is that the greedy algorithm gives essentially the same information as the longer MCMC run in a very small fraction of the time.
Movie-Lens 100k The Movie-Lens dataset gives 100,000 ratings of movies by users. In total, there are 943 users and 1,682 movies. Many users do not rate particular movies so the network is quite sparse (93%) and it is useful to use the approach mentioned in Section 3. 6. 2. The ratings (linking attributes) are assumed Poisson distributed, due to the ordinal nature of the ratings going from 1-5. This is a sensible model choice in this context due to both the ordinal and discrete nature of the ratings. The clustering task will cluster groups of individuals giving a similar rating to specific groups of movies. One could expect that this would glean more information than treating the 1-5 ratings as purely categorical since the Poisson model captures in some ways the ordinal features of the data.
A missing rating is just given the value 0 when assuming the ratings are Poisson. The data is shown in Figure  5. One run of each of the algorithms was carried out each with two restarts with results in Table  4. The reordered data is shown for algorithms A1 and A3 in Figure  5. A glance at these results reveals that the pruning based algorithms give different number of clusters to those that do not involve pruning. This could be due to the effect of the value of the difference in exact ICL considered for the pruning. A value of this threshold which is too high could introduce some degeneracy into the search space, with labels settling in sub-optimal groups. The result for this dataset can vary depending on the pruning threshold chosen. However, pruning does give a considerable reduction in computing time which is favourable from a scalability viewpoint.
Due to the fast run time, we can circumvent this somewhat in practice by running, say 10 instances of the greedy algorithm and taking the one that gives the highest ICL (indicating the best clustering). The greedy algorithm (especially the sparse versions) scale well enough to make this feasible. The risk that this will happen to the MCMC algorithm is less due to its stochastic nature. ICL does still possess many of the benefits of MCMC, the strongest of which is that it allows for automatic choice of the number of clusters. Considering the complexity of the task it performs (model selection and clustering), the ICL algorithm does appear to scale quite well, running on the Movie-Lens 100k data in less than 3 minutes, and the congressional voting data in less than a second. For many of the applications of bi-clustering in the literature, this is competitive.
In addition, we provide code (written in C with an R wrapper) which is available from the first author's webpage https://sites. google. com/site/jsnwyse/ (a Makefile is provided to compile on Unix-alikes). In Section 3. 6 we showed how sparsity (a common feature of observed networks) can be exploited to provide a faster version of the greedy search exact ICL algorithm. Although not possible to provide exact quantification for the order of speed up (in terms of N and M ) we observed considerable computational gain in exploiting sparsity. The applicability of these ideas may stretch well beyond implementation of the LBM. For example, it may be possible to use the same kind of representation for SBMs. We believe that the latent blockmodel is an appealing model for bipartite networks, although to our knowledge, no authors have appeared to explicitly discuss it in the context of network modelling.
Genetics of Disease-associated Mutations in mt-aaRSs We recently developed a knowledge-based repository coupled with a web server (http:// misynpat. org) that integrates and links clinical, genetic, and structural data on disease-related mutations of human mt-aaRSs  [22]. The MiSynPat repository is one of the sources of the data discussed below and contains an exhaustive list of reported mutations and related references. Presently, 208 different disease-related variations have been identified, either in coding sequences (153) or in intronic regions (55) of mt-aaRS genes. For a variety of diseases associated with mt-aaRSs mutations, patients are mainly compound heterozygotes  [22]. Homozygosity is sometimes reported (26 of 153 missense or nonsense mutations). Although it seems obvious that mutations in essential enzymes would cause disease, one can also expect that most mutations in such enzymes are lethal.
mt-aaRSs are encoded in the nucleus and mt-tRNAs in the mt-DNA, and thus mutations segregate in patients following Mendelian or maternal inheritance, respectively (Box 1). The primary impacts of the mutations are classified according to five major organ systems: central nervous system (CNS), cardiovascular, endocrine, musculoskeletal, and urinary. A further category named 'various' contains reports of less frequent diseases. Data are extracted from the MiSynPat (http://misynpat. org [22] ) and MitoMap (www. mitomap. org/MITOMAP [21] ) databases for mutations in mt-aaRSs and mt-tRNAs, respectively. reach some conclusions  [22]. Protein architectures can be extracted either from crystal structures or from models derived by homology (based on crystallographic structures of homologous proteins).
However, in some instances only, mutations occur at positions that are involved in substrate binding, suggesting a putative impairment in the canonical function of aaRSs)  [22]. models (which include MTSs) of mt-ArgRS, mt-GluRS, mt-TyrRS, mt-AspRS, and LysRS were uploaded from MiSynPat (http://misynpat. org [22] ). Human mt-PheRS is depicted in a 'closed' state in the absence of cognate tRNA (PDB: 3CMQ  [38] ) or in the 'open' state when complexed with Thermus thermophilus tRNA Phe (in grey) (PDB: 2TUP  [84] ). For all structures, the mitochondrial targeting sequence (MTS) is in yellow, the catalytic domain in red, the anticodon binding domain in green, and the hinge region in grey, and additional domains are in hues of blue (the color code is the same as in Figure  3 ). Where appropriate, the second dimer is displayed in light grey.
Background: Understanding the age-structure of mosquito populations, especially malaria vectors such as Anopheles gambiae, is important for assessing the risk of infectious mosquitoes, and how vector control interventions may impact this risk. The use of near-infrared spectroscopy (NIRS) for age-grading has been demonstrated previously on laboratory and semi-field mosquitoes, but to date has not been utilized on wild-caught mosquitoes whose age is externally validated via parity status or parasite infection stage. In this study, we developed regression and classification models using NIRS on datasets of wild An. gambiae (s. l. ) reared from larvae collected from the field in Burkina Faso, and two laboratory strains. We compared the accuracy of these models for predicting the ages of wild-caught mosquitoes that had been scored for their parity status as well as for positivity for Plasmodium sporozoites.
Results: Regression models utilizing variable selection increased predictive accuracy over the more common fullspectrum partial least squares (PLS) approach for cross-validation of the datasets, validation, and independent test sets. Models produced from datasets that included the greatest range of mosquito samples (i. e. different sampling locations and times) had the highest predictive accuracy on independent testing sets, though overall accuracy on these samples was low. For classification, we found that intramodel accuracy ranged between 73. 5-97. 0% for grouping of mosquitoes into "early" and "late" age classes, with the highest prediction accuracy found in laboratory colonized mosquitoes. However, this accuracy was decreased on test sets, with the highest classification of an independent set of wild-caught larvae reared to set ages being 69.
These mosquitoes were held for either 3, 6, 9, 12 or 15 days prior to scanning. Blood meals were offered via the arm of a human volunteer in compliance with the Helsinki Declaration (Colorado State University Institutional Review Board approval #09-1148H) at day 2 post-emergence, and the evening prior to their designated scan day (12-18 h later). Mosquito numbers of those successfully blood-fed in each calibration set are listed in Additional file 1: Table  S1. Prior to scanning, all adult mosquitoes were classified under light microscopy to species by taxonomic key  [37]. Samples kept for each dataset were based on collection amounts for each day. In general, sample sizes were held to 40 samples per time point in an effort to make the sample sizes equal across all days. In some instances this was impossible due to low sample numbers; in these cases all samples were held to a similar value (i.