dataesr/scientific-paragraphs-categorization huggingface dataset:
TreeMix TreeMix  [22]  was used to infer potential admixture edges in the phylogeny. TreeMix models the correlation of allele frequencies at variable positions across the genome. The correlations that do not fit well under the modeled tree are then corrected for using migration events. We used a randomly sampled allele for each sample and a similar filtering approach as the one described for the D statistics tests. Tests were with combinations of samples as individuals and samples grouped into categories representing the main genetic clusters (for details see Data S1). Sites with at least one individual with coverage per group were kept. The final dataset consisted of a total of 834,537 segregating sites. We ran TreeMix on the final dataset assuming 0 to 4 migration edges (m = 0-4). For each value of m, we ran 100 replicates starting in different seed values and evaluated the replicate with the highest likelihood.
qpGraph We used qpGraph from the ADMIXTOOLS package  [23]  to evaluate the relationships between the different species in our samples. In particular, we addressed the question of whether the African golden wolf can be modeled as a hybrid species. qpGraph uses the correlation on all possible f statistic tests in a given admixture graph to evaluate its overall fit. The same dataset and filtering parameters used for the D statistics tests were used in this analysis. Samples were grouped into clusters representing the main lineages in the admixture graph as indicated in Data S1. First, we started with a tree including the coyote, Ethiopian wolf, gray.
ACKNOWLEDGMENTS The authors would like to acknowledge the assistance of the  Danish National High-Throughput Sequencing Centre  for assistance in Illumina data generation. We also gratefully acknowledge the  Danish National Supercomputer for Life Sciences, Computerome  (https://www. computerome. dk),for the computational resources to perform the sequence analyses. For making sample material available, we would like to thank  Jo ¨rns Fickel  from  Leibniz-Institut fu ¨r Zoo-und Wildtierforschung  and  Kristian Gregersen  from the  Natural History Museum of Denmark. We also acknowledge the following for funding our research: the  Qimmeq  project funded by  The Velux Foundations and Aage og Johanne Louis-Hansens Fond ; Carlsbergfondet grant  CF14-0995  and  Marie Sk1odowska-Curie Actions  grant  655732-WhereWolf  to S.
DATA AND SOFTWARE AVAILABILITY The BioProject accession number for the short read sequences used in this paper is available at the NCBI short read archive under the accession PRJNA494815. e5 Current Biology 28, 1-9. e1-e5, November 5, 2018 Please cite this article in press as: Gopalakrishnan et al. , Interspecific Gene Flow Shaped the Evolution of the Genus Canis, Current Biology (2018), https://doi. org/10. 1016/j. cub. 2018. 08. 041.
Admixture Using the genotype likelihoods obtained from the ANGSD pipeline, the ancestry clusters and admixture proportions for 48 samples representing all species (for details see Data S1) were estimated using NGSadmix  [20]  based on 5. 7 million SNPs. Admixture analyses were performed using only markers with minor allele frequency greater than 0. 1. We used a range of values for the number of clusters  (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) , to explore the structure in the dataset. To avoid convergence to local optima, the admixture analysis was repeated at least 200 times with different random initial parameter values, and the replicate with the highest likelihood was chosen.
* S Supporting Information The Supporting Information is available free of charge on the ACS Publications website at DOI: 10. 1021/acs. jpcb. 8b03528. Details of synthesis and characterization of SP with NMR spectroscopic characterization ( 1 H,  13  C APT, HSQC, HMBC, COSY, and NOESY) of both Z-MCH + and E-MCH + ; actinometry; computational studies; experimental and calculated Raman spectra of the SP/NSP forms and Z-MCH + /Z-NMCH + and E-MCH + /E-NMCH + forms; and additional UV/vis absorption spectral data (PDF).
WGD is present in 11. 4% of GBM In most cancers, WGD corresponds to tetraploidy, which is a type of polyploidy in which a single cell has two sets of chromosomes (4n or 92 chromosomes) instead of one (2n or 46 chromosomes). SNP array data analysis showed that most GBM (109/123, 88. 6%) had a near-diploid karyotype with a number of chrs between 39 and 52, and an average estimated ploidy of 2. 03. However, some GBM (14/123, 11. 4%) presented a near-tetraploid DNA content, with a number of chrs oscillating between 58 and 92, and an average estimated ploidy of 3. 46, representing WGD (Supplementary Figure  1 ). In comparison with near-diploid GBM, WGD GBM displayed more chr losses (but no gain) and allelic imbalances. In near-diploid GBM, a ploidy status near 2 was observed in 76. 7% cases whereas a ploidy status near 4 was observed in only 22.
4% WGD GBM (p < 0. 0001). There was a tendency for chr losses after genome doubling. This observation is supported by the average estimated ploidy of 3. 46 in near-tetraploid GBM. Hence, GBM with WGD presented with a larger overall number of SCNA. We used a FISH approach to confirm WGD in 6 GBM (out of 14) with a near-tetraploid karyotype (Supplementary Table  2 ). At least three chrs per sample were tested. For all the chrs tested, the copy number was in accordance with that observed on GAP analysis. For case GBM49-003, the SNP array data showed that there were two copies of chr 2 with a heterozygous allelotype, there were three copies of chr 19 with an allelic imbalance, and there were four copies of chr 17 with a heterozygous allelotype. The same copy numbers were detected using FISH (Figure  2 ).
0001), and 19. 4% of CDKN2A-deleted GBM harbored a CT pattern at the CDKN2A locus (9p21. 3) (p = 0. 0003). Yang   GBM using whole genome sequencing  [21]. Four of 12 patients (33%) harboring CDKN2A/B deletion displayed complex rearrangements at the 9p21 locus and 8/14 GBM (57%) with EGFR amplification presented complex rearrangements at 7p11. Taken together, these data suggest that complex rearrangements including CT are responsible for EGFR amplification and CDKN2A/B deletion. Many studies suggest that CT is a phenomenon leading to chr rearrangements (including gene fusions) implicating yet to discover driver genes. Few fusion genes have been described in high-grade gliomas. Singh et al. reported FGFR3-TACC3 and FGFR1-TACC1 gene fusions in 3% GBM  [28]  The FGFR3-TACC3 fusion might be suspected on SNP arrays by detecting focal gains involving FGFR3 (chr 4p16.
3). The identification of such fusion genes allowed the development of targeted therapies, with promising preliminary results  [22]. Frattini et al. described recurrent in-frame fusions involving EGFR (chr 7p11) and different partners (SEPT14, PSPH) in 7% GBM  [30]. Of note, in our cohort, one case harboring a CT pattern on chr 7p11 and EGFR amplification displayed an EGFR-SEPT14 fusion. Four additional cases displayed gene fusions recurrently implicating EGFR, SEPT14 or VOPP1 genes; those fusions, detected by RNA sequencing, were validated by RT-PCR and Sanger sequencing (data not shown, manuscript in preparation). Recently, a fusion between NAB2 and STAT6 genes (chr 12q13. 3) associated with a focal 12q13 amplification has been reported in a 29-year-old patient with an IDH1-mutant GBM  [23].
Isolation of tumor cells from fresh tissue would have allowed analysis of whole nuclear DNA content by flow cytometry. However, FISH technique based on the use of centromere probes represents a sensitive method for detecting chromosome aneuploidies  [31]. Regarding CT, more stringent criteria can be used to identity CT patterns based on whole-genome paired-end DNA sequencing data  [32]. Nonetheless, SNP arrays allow for the detection of the major features of CT: clustering of breakpoints, regularity of oscillating copy-number states, and prevalence of regions with interspersed loss and retention of heterozygosity  [32]. A consensus on which criteria are to be met to define CT has yet to be reached. In conclusion, we demonstrated that WGD was an early event associated with TP53 mutation and leading to aneuploidy in IDH-wild-type GBM.
SNP array and copy number analysis SNP array was performed on the 123 samples. Tumor DNA was extracted using the Nucleospin Tissue Kit (Macherey Nagel) and quantified using Qubit dsDNA BR Assay Kit (Life Technologies). Tumor DNA was hybridized with Infinium CytoSNP-850 K Illumina Beadchips (Illumina) according to the manufacturer's instructions. SNP arrays were scanned on an iScan (Illumina) and data were processed using the genotyping module in Genome Studio v2011. 1 (Illumina) to calculate B-allele frequencies (BAF) and logR ratios. GAP method was used to call SCNA and to determine the number of chrs and the ploidy pattern (near-diploid, near-tetraploid) for each tumor  [35]. The GAP method relies on two parameters to estimate tumor ploidy: 1) the DNA index for a tumor genome estimated as an average copy number in a genome divided by 2, and 2) the chromosome counts in a tumor genome estimated as a sum of copy numbers at pericentric regions of each chromosome arm.
CT identification CT events were detected using segmented data (LogR ratio, BAF value) from the SNP arrays. They were identified following the three criteria described by Korbel and Campbell  [32] : 1) There were at least 10 genomic rearrangements per chr arm with such rearrangements occurring in no more than 4 chrs in a given sample, 2) There was a clustering of breakpoints, 3) There was interspersed loss and retention of heterozygosity with no more than two to three different copy number states (except for focal amplification or homozygous deletion (involving key cancer genes)). After manual screening according to the abovementioned criteria, a validation analysis was performed on segmented data using CTLPScanner, a web server for detection of CT patterns  [37]. Scanner parameters and thresholds were as follows: genome assembly = hg19; copy number status change times ≥ 10; log10 of likelihood ratio ≥ 6; minimum segment size = 5 Kb.
Stable isotope records from speleothems provide information on past climate changes, most particularly information that can be used to reconstruct past changes in precipitation and atmospheric circulation. These records are increasingly being used to provide "out-of-sample" evaluations of isotope-enabled climate models. SISAL (Speleothem Isotope Synthesis and Analysis) is an international working group of the Past Global Changes (PAGES) project. The working group aims to provide a comprehensive compilation of speleothem isotope records for climate reconstruction and model evaluation. The SISAL database contains data for individual speleothems, grouped by cave system. Stable isotopes of oxygen and carbon (δ 18 O, δ 13 C) measurements are referenced by distance from the top or bottom of the speleothem.
Furthermore, none of them provide comprehensive coverage of the globe. Table  1. Information on speleothem records (entities) in the SISAL_v1 database. Elevation (Elv) is given in metres above sea level and latitude (Lat) and longitude (Long) in decimal degrees. For convenience, we have given the location of each record, although this information is not available in the database itself. Note that the latitude and longitude of Abaliget, Brown's cave and Uamh an Tartair are given correctly here but are incorrect in the SISAL_v1 database.
BC01-07 Brown SISAL (Speleothem Isotope Synthesis and Analysis) is an international working group set up in 2017 under the auspices of the Past Global Changes (PAGES) programme (http: //pastglobalchanges. org/ini/wg/sisal, last access: 4 September 2018). The aim of the working group is to compile the many hundreds of speleothem isotopic records worldwide, paying due attention to careful screening and metadata documentation, the construction of standardized age models, and age-model uncertainties, in order to produce a public-access database that can be used for palaeoclimate reconstruction and for climate-model evaluation. In this paper, we document the first publicly available version of the SISAL database, focusing on describing its structure and contents including the information that has been included to facilitate quality control.
Compilation of data The database contains stable carbon and oxygen isotope measurements made on speleothems, as well as supporting metadata to facilitate the interpretation of these records. All available speleothem data are included, and no attempt was made to screen records on the basis of the time period covered, the resolution of the records, or the quality of the data or age models. Adequate metadata are provided to allow database users to select the records that are suitable for a particular type of analysis. The raw data were either provided by members of the SISAL working group or extracted from data lodged in PANGAEA or from the National Centres for Environmental Information. Additional information on the records was compiled from publications. All the records in the current version of the database (SISAL_v1) are listed and described in Table  1.
Structure of the database The data are stored in a relational database (MySQL), which consists of 14 linked tables, specifically site, entity, sample, dating, dating lamina, gap, hiatus, original chronology, δ 13 C, δ 18 O, entity link reference, reference, composite link entity and notes. Figure  S1  shows the relationships between these tables. A detailed description of the structure and content of each of the tables is given below. The details of the predefined lists for all fields can be found in Table  S1.
, 2015). The database includes information on whether the cave site has been monitored: positive returns in this field mean that monitoring of in-cave environmental parameters (e. g. cave air temperature) and/or cave drip chemistry has been carried out periodically for at least one entire season (as opposed to one-off measurements of in-cave conditions when the speleothem was collected). The database does not contain monitoring data, but inclusion of this field facilitates researchers being able to contact the original data providers about monitoring information, which can be useful in understanding if a cave is likely to contain speleothems that have been deposited close to isotopic equilibrium.
, 2011; Spötl et al. , 2005; Tremaine et al. , 2011). The entity table also contains a field to document whether any tests have been carried out to establish whether there is oxygen and carbon isotope quasi-equilibrium between the drip water (CO 2 -H 2 O system) and the speleothem (CaCO 3 ). There are several such tests (see for example  Hendy, 1971; Johnston et al. , 2013; Mickler et al. , 2006; Tremaine et al. , 2011) , but no attempt is made to identify which test has been applied in the database. The drip type (e. g. seepage flow, seasonal drip, vadose flow;  Smart and Friederich, 1987 ) also provides useful hydrological information: seepage flow shows a small inter-annual variability of discharge and the speleothem record will therefore more likely reflect a long-term average state over several years; other drip types, such as seasonal drip, will indicate the potential to record seasonal or individual rainfall events.
The main focus of the SISAL database is stable isotope measurements, but the entity metadata table also contains information on the kinds of measurements that have been made for a specific speleothem. Only the stable isotope measurements are currently archived in the database. However, listing the range of data available from any speleothem will facilitate future updates of the database to include other types of measurements apart from stable isotopes (i. e. trace elements) and will help researchers in locating speleothems where multiple types of measurements have been done. The entity metadata table contains four fields to facilitate data traceability. The first two fields give the name of the person who was responsible for collating the data, and a DOI or URL for the original data. Some records have been partially or entirely updated since first being published.
Dating information (table name: dating) The dating information table (Table  S5 ) provides information on the radiometric dates used to construct the original age model for each of the speleothem entities, including type of radiometric date (e. g. U series), depth of dated sample, thickness of dated sample and sample weight. Dates that are used to anchor sequences that are dated by lamina counting (see Sect. 2. 2. 5) are included in the dating information table and identified in date type as an event (i. e. the start or end of a laminated sequence). The degree of precision varies between different dating methods and techniques, for example mass spectrometric U/Th dating generally produces a more precise age than the alpha spectrometry U/Th data method. So the inclusion of the dating method provides a basic measure of the reliability, in terms of analytical precision, of any given date.
The corrected U/Th age is adjusted for detrital contamination; the corrected calibrated 14 C age is adjusted for dead carbon. The correction factors used to derive the corrected U/Th or 14 C age are included in the dating information table. The decay constant used to calculate the U/Th ages is given because the values used have changed through time  (Cheng et al. , 2000 (Cheng et al. , , 2013;; Edwards et al. , 1987; Ivanovich and Harmon, 1992). The calibration curve used to convert radiocarbon ages to calendar years in the original publication is also given. Several different standards have been used in the original publications for the modern reference state (e. g. BP(1950) , b2k, CE / BCE or the year when U/Th chemical separation was performed) but all of these have been converted to  BP(1950)  in the database.
Some of the dates listed for a given entity were not used in the original age model, for example because the dating sample was contaminated with organic material or because of age inversions. The dates excluded from the original age model are flagged in the database (date_used) but the other information on these dates is nevertheless included in the dating information table to ensure transparency. The geochemical characteristics of the sample provide information that is required to assess the quality or reliability of these dates. The ratio of 230 Th / 232 Th, for example, is a measure of detrital thorium concentration in the sample and thus provides an initial quality control on each date. A 230 Th / 232 Th activity ratio > 300 is considered a good indicator of a reliable date  (Hellstrom, 2006) ; a higher ratio indicates a cleaner sample with higher accuracy.
Gap place mark information (table name: gap) When a composite record is created based on more than one individual speleothem from the same cave system, there may be discontinuities in the overlapping time of the individual records. These gaps are not growth hiatuses, but must be identified to facilitate plotting of the records. The gap place mark information table  (Table S8 ) provides information on the location of sample gaps. The gap is referenced to the specific depth at which it occurs, and this depth is considered as an imaginary sample which then appears with a specific sample_id in the sample table. In composite records where sample depths are not given, the location of a gap can be derived from the sample ordering and the absence of isotopic information for a given sample. In point of fact, this table is empty in version 1 of the database.
Link composite and entity information (table name: composite_link_entity) Multiple speleothem records showing a temporal overlap (and a similar signal) can be combined to create a composite record of changes through time. The composite record is treated as a distinct entity in the database. The link composite and entity information table  (Table S14 ) is provided in order to be able to link this composite record to the individual speleothem records from which it was derived. Thus any single composite entity (composite_entity_id) is linked to multiple single entities (single_entity_id).
Quality control Individual records in the SISAL database were compiled either by the original authors or from published and openaccess material by specialists in the collection and interpretation of speleothem records. In this latter case, the data compilers made every attempt to contact original authors to check that the compiled data were correct. The name of the person who compiled the data is included in the database (entity table, contact) so that they can be consulted in the future about queries or corrections. Individual records for the database were subsequently checked by a small number of regional coordinators, to ensure that records were being entered in a consistent way. Prior to entry in the database, the records were automatically checked using specially designed database scripts (in Python) to ensure that the entries to individual fields were in the format expected (e.
g. text, decimal numeric, positive integers) or were selected from the predefined lists provided for specific fields. In defining both the formats and the pre-defined lists, the SISAL working group has taken special care to ensure that the entries are unambiguous. Null values for metadata fields were identified during the checking procedure, and checks were made with the data contributors whenever possible to ensure that null fields genuinely corresponded to missing information. The database contains information designed to allow an assessment of the quality of an individual record. Thus, the entity metadata table contains information on, for example, the distance of the speleothem from the cave entrance in order to allow the user to assess whether cave temperatures are driven by advection of air or conduction through the bedrock.
There are several other factors that can affect ventilation, for example the contrast between the cave and external climates, and cave morphology such as the size of the entrance or the number of entrances. Information on these factors is only rarely given in publications; we assume that this information would be more likely to be available if the original authors thought that ventilation was a significant influence on the speleothem record. Including information on distance from the cave entrance is therefore being regarded as a minimal indicator for record quality. Other fields that are included to allow the user to select appropriate records include geology, rock age, speleothem type and drip type. The database also contains information to allow an assessment of the reliability of the dates used in constructing the original age model.
The most important of these fields are those with information on the sample geochemistry (see Sect. 2. 2. 4), which allows the user to determine whether the samples were sufficiently large and sufficiently pure to yield good U/Th dates. The database also gives information on sample weight, which also addresses this issue. The information on the corrections employed, dating uncertainties and whether the original authors considered the date reliable (and therefore used it in constructing an age model) also provide insights into the reliability of individual chronologies. The SISAL database is an ongoing effort and continuing efforts to update the records will include updating missing data fields for individual records. Analysis of the data is also useful for verification purposes and may result in corrections of some data.
Any such changes to sites and entities included in version 1 of the database will be documented in subsequent updates. The SISAL working group also aims to provide new chronologies in future versions of the database based on Bayesian approaches, namely OxCal  (Bronk Ramsey, 1995 , 2008) , COPRA  (Breitenbach et al. , 2012)  and Sta-lAge  (Scholz and Hoffmann, 2011).