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opencc-by-4.0Mar 2021View details →

Gene expression and splicing counts from the Yepez, Gusic et al study - strand-specific

File description: <ol> <li> geneCounts: gene-level counts  </li> <li> k_j: split counts spanning from one exon to another. </li> <li> k_theta: non-split counts covering a splice site </li> <li> n_psi3: total split counts from a given acceptor site </li> <li> n_psi5: total split counts from a given donor site </li> <li> n_theta: total split and non-split counts for a given splice site </li> <li> Sample annotation describing each sample from the dataset </li> <li> Description file with global information from the dataset </li> </ol>   The gene counts were originated using the GTF file from release 34 of GENCODE <a href="https://www.gencodegenes.org/human/release_34">https://www.gencodegenes.org/human/release_34</a>, and the split and non-split counts contain only the annotated junctions from the same release. Use: The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired-end specifications match. Afterwards, DROP can be used to compute expression and splicing outliers (<a href="https://github.com/gagneurlab/drop">https://github.com/gagneurlab/drop</a>). Number of samples: 269 Tissue: Fibroblast Organism: Homo sapiens Genome assembly: hg19 Gene annotation: gencode34 Disease (ICD-10: N): E72: 4, E75: 2, E77: 1, E88: 199, F82: 1, F89: 7, G31: 14, G40: 2, G71: 3, G82: 1, G93: 2, I42: 1, K72: 4, NONE: 18, P94: 2, Q02: 1, Q78: 1, R16: 2, R27: 3, R29: 1 Strand specific: TRUE Paired end: TRUE Protocol: poly(A) enrichment Dataset contact: Vicente Yepez, yepez@in.tum.de; Julien Gagneur, gagneur@in.tum.de; Holger Prokisch, prokisch@helmholtz-muenchen.de Citation: Cite both the resource using Zenodo's citation and the publication under References

opencc-by-nc-sa-4.0Oct 2022View details →

Machine learning on large-scale proteomics data identifies tissue- and cell type-specific proteins

Using data from 183 public human data sets from PRIDE, a machine learning model was trained to identify tissue and cell-type specific protein patterns. PRIDE projects were searched with ionbot and tissue/cell type annotation was manually added. Data from physiological samples were used to train a Random Forest model on protein abundances to classify samples into tissues and cell types. Subsequently, a one-vs-all classification and feature importance were used to analyse the most discriminating protein abundances per class. Based on protein abundance alone, the model was able to predict tissues with 98% accuracy, and cell types with 99% accuracy. The F-scores describe a clear view on tissue-specific proteins and tissue-specific protein expression patterns. In-depth feature analysis shows slight confusion between physiologically similar tissues, demonstrating the capacity of the algorithm to detect biologically relevant patterns. These results can in turn inform downstream uses, from identification of the tissue of origin of proteins in complex samples such as liquid biopsies, to studying the proteome of tissue-like samples such as organoids and cell lines

opencc-by-4.0May 2022View details →

TCR convergence is a indicator of antigen-specific T cell response in immunotherapies

This compressed file contains all the convergent TCR sequence information involved in this study.

dryad32/100

Mapping and assembly of the Midas cichlid male-specific region supports molecular parallelism in the evolution of a master sex-determining role for amhr2

The evolution of sex chromosomes and their differentiation from autosomes is a major event during genome evolution that happened many times in several lineages. The repeated evolution and lability of sex-determination mechanisms in fishes makes this a well-suited system to test for general and predictable patterns in evolution. According to current theory, differentiation is triggered by the suppression of recombination following the evolution of a new master-sex determining gene. However, the molecular mechanisms that establish recombination suppression are known from few examples, owing to the intrinsic difficulties of assembling sex determining regions (SDRs). Forward-genetics data and the development of long-read sequencing have generated a wealth of data questioning central aspects of the current theory. Here, we demonstrate that sex in Midas cichlids is determined by an XY system, identify and assemble the SDR by combining forward-genetics, long-read sequencing and optical mapping. We show how long-reads aid in the detection of artifacts in genotype-phenotype mapping that arise from incomplete genome assemblies. The male-specific region is restricted to a 100 kb segment on chromosome 4 that harbors transposable elements and a Y-specific duplicate of the anti-Mullerian receptor 2 locus, a known sex-determining gene. Our data suggests that amhr2Y originated by an interchromosomal translocation from chromosome 20 to 4 predating the split of Midas and Flier cichlids. In the later, it is pseudogenized and translocated to another chromosome. Duplication of anti-Mullerian genes is a common route to establishing new sex determiners, highlighting the role of molecular parallelism in the evolution of sex determination.

opencc-zeroOct 2022View details →

opencc-by-4.0Jan 2022View details →

Towards a Generic Grasp Planning Pipeline using End-Effector Specific Primitive Grasping Actions

In the past few years, several robotic end-effectors based on diverse kinematics and actuation principles have been developed to provide grasping and manipulation functionalities. To ease the control and application of these wide-ranging end-effectors, the development of effective reusable tools that can facilitate the end-effector motion planning and control is necessary. In this work, we introduce a generic grasp planner that leverages on the concept of the primitive grasping actions. Given the specific characteristics of an end-effector, including its kinematic and actuation arrangements, a number of primitive grasping actions are extracted and employed by the proposed grasp planner to autonomously plan and synthesize more complex grasping behaviours. The grasp planner is validated through experimental trials involving the HERI II robotic hand, a four-fingers tendon-driven under-actuated hand. The results of these experiments demonstrate the efficacy of the proposed method to generate appropriate planning actions enabling to grasp objects of different shapes.

Fig. 4 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane

Fig. 4. Parameter estimates for fixed effects (β) in spatial mixed effects models (spaMM) for each species, with 95% CIs, testing the effects of Elevation (scaled), AMT (scaled), and Elevation * AMT interaction on traits; Asterisk indicates the CIs did not encompass zero. If no estimate is shown that variable was not included in the model for that species. Maps show spatial trends of trait value from interpolation of estimates for each model (filled.mapMM function in spaMM). Note, for B. vosnesenskii mass and pw-Empty, the low-AIC models were intercept plus random effect only, but for visualization, results are presented for the next best model with at least one fixed effect (seeTable 2 for model details).

Fig. 3 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane

Fig. 3. Effect predictions (with 95% CI) of mass (field and empty), thorax size (ITS), forewing area, and transformed wing loading (pw-Field, pw-Empty) against (A) latitude, (B) AMT (Worldclim BIO1 variable), and (C) elevation from univariate linear mixed effects models for B. vancouverensis (blue) and B. vosnesenskii (red). Statistical analyses were conducted on log-transformed mass, ITS, and wing loading (see SuppTable S4 [online only]), but responses were back-transformed to the original scale for plotting (plot_model function in sjPlot). Lines are labeled with significance estimate of the β parameter estimated from lmerTest (*P <0.05; ***P <0.001; unlabeled = not significant, CI encompasses zero).

Fig. 1 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane

Fig. 1. Map of sampling localities in California, Oregon, and Washington, United States.Bombus vancouverensis is indicated by circles,B. vosnesenskii by triangles, and additional B. vosnesenskii from 2013 used to improve elevational coverage at middle latitudes for some traits by open triangles. Grayscale shading reflects a digital elevation model for the region.

Fig. 5 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane

Fig. 5. Relationships among space, population structure (FST), and average mass and wing loading (pw) differences among pair of populations for (A) B. vancouverensis and (B) B. vosnesenskii. Panels include plots of isolation by distance (FST by geographic distance), effects of population structure on mass, and the effects of elevation on mass and pw residuals from models including FST and geographic distance.The latter panels are included to illustrate the remaining positive effect of elevational separation on wing loading differences among B. vancouverensis populations after accounting for space and population structure, but not for B. vosnesenskii populations and not for mass in either species (seeTable 3 and Supp Fig. S6 [online only]).

Fig. 2 in Divergence in Body Mass, Wing Loading, and Population Structure Reveals Species-Specific and Potentially Adaptive Trait Variation Across Elevations in Montane

Fig. 2. Boxplots (shown for site means) and tests of differences between species in overall field mass (A), empty mass (B), ITS (C), forewing area (D), pw-Field (E), and pw-Empty (F). Statistical tests are summaries taken from linear mixed models (full report and parameter estimates in Supp Table S1 [online only]), showing marginal (R 2) and conditional (R 2) R2 values and with df for the species effect t statistic and P-values (***P <0.001; N.S. = not significant) associated with the M C relevant fixed effect estimated using lmertest. Mass, ITS, and pw values were log-transformed for statistical tests but plotted untransformed. Panels G–L show scatterplots of correlations among several traits for each bee and are presented with Pearson's correlation coefficients (r) and 95% CIs (see SuppTables 2 and 3 [online only] and Supp Figs. S2–S4 [online only] for additional trait correlation statistical details).

opencc-by-4.0Oct 2022View details →

Sex-specific summary statistics

Provided are summary statistics for 27 traits using UK Biobank genotype and phenotype data. plink2.00 alpha is used to generate the summary statistics.

Supplementary material 7 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646

Comprehensive Blast analysis : Explanation note: Blast results against the NCBI nt database (June 2015) for all eukaryotes presented in a Megan5 plot.

Supplementary material 6 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646

Alternative ordinations based on binary data and taxonomy : Explanation note: Two alternative NMDS accompanied by corresponding PERMANOVA statistics based on a) the presence/absence of OTUs (left panel) and the Jaccard index, and b) the taxonomic classification of SILVA NGS and the Cao index. The ellipses (coloured to POM type) are based on standard deviations around centroids with a confidence level of 0.95.

Supplementary material 5 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646

Rarefaction analysis : Explanation note: Rarefaction curves based on the OTU table without OTU singletons for all eukaryotes (left panel) and for fungal OTUs (right panel).

Supplementary material 8 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646

Phylogenetic tree of Neocallimastigales sequences : Explanation note: Phylogenetic bayesian tree based on 10 million generations. Sequences that were classified as Neocallimastigales in the manuscript are coloured in red with the frequency of sequences in the dataset in black. The name corresponds to the representative read identifier in the dataset (accessible at ENA nucleotide archive: PRJEB14236). Node labels are posterior probabilities above 0.8. Statistically supported branches have an probability of 0.95-1.

Supplementary material 4 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646

Krona charts of classified OTUs (RDP) and sequences (SILVA NGS). : Explanation note: File archive in "zip" format. Decompress with e.g., "unzip" for inspecting individual html files. Open html files with an internet browser (network connection must be enabled). Krona charts presenting the classified sequences based on a) OTUs classified by the RDP classifier, and b) based clipped reads processed by the SILVA NGS pipeline.

Supplementary material 3 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646

Detailed results of the clipping procedure : Explanation note: File archive in "zip" format. Decompress with e.g., "unzip" for inspecting individual files. Files describing the bioinformatic processing and the effects of the clipping procedure.

Supplementary material 1 from: Wurzbacher C, Warthmann N, Bourne EC, Attermeyer K, Allgaier M, Powell JR, Detering H, Mbedi S, Grossart H-P, Monaghan MT (2016) High habitat-specificity in fungal communities in oligo-mesotrophic, temperate Lake Stechlin (North-East Germany). MycoKeys 16: 17-44. https://doi.org/10.3897/mycokeys.16.9646

Accompanying data tables : Explanation note: Two additional tables stating 1) the physicochemistry of the lake during the sampled time span, 2) the proportions of fungal-like organism and terrestrial fungi ("forest fungi", see main text).

opencc-by-4.0Sep 2015View details →

Supplementary material 4 from: Hong SC, Magarey RD, Borchert DM, Vargas RI, Souder SK (2015) Site-specific temporal and spatial validation of a generic plant pest forecast system with observations of Bactrocera dorsalis (oriental fruit fly). NeoBiota 27: 37-67. https://doi.org/10.3897/neobiota.27.5177

Figure S1: Explanation note: Fit of low temperature mortality function (line) to observations (diamonds).