Showing 6 of total 6 results (show query)
r-lidar
lidR:Airborne LiDAR Data Manipulation and Visualization for Forestry Applications
Airborne LiDAR (Light Detection and Ranging) interface for data manipulation and visualization. Read/write 'las' and 'laz' files, computation of metrics in area based approach, point filtering, artificial point reduction, classification from geographic data, normalization, individual tree segmentation and other manipulations.
Maintained by Jean-Romain Roussel. Last updated 2 months ago.
alsforestrylaslazlidarpoint-cloudremote-sensingopenblascppopenmp
623 stars 14.47 score 844 scripts 8 dependents
strohne
volker:High-Level Functions for Tabulating, Charting and Reporting Survey Data
Craft polished tables and plots in Markdown reports. Simply choose whether to treat your data as counts or metrics, and the package will automatically generate well-designed default tables and plots for you. Boiled down to the basics, with labeling features and simple interactive reports. All functions are 'tidyverse' compatible.
Maintained by Jakob Jünger. Last updated 16 days ago.
5 stars 7.16 score 125 scripts
jedick
chem16S:Chemical Metrics for Microbial Communities
Combines taxonomic classifications of high-throughput 16S rRNA gene sequences with reference proteomes of archaeal and bacterial taxa to generate amino acid compositions of community reference proteomes. Calculates chemical metrics including carbon oxidation state ('Zc'), stoichiometric oxidation and hydration state ('nO2' and 'nH2O'), H/C, N/C, O/C, and S/C ratios, grand average of hydropathicity ('GRAVY'), isoelectric point ('pI'), protein length, and average molecular weight of amino acid residues. Uses precomputed reference proteomes for archaea and bacteria derived from the Genome Taxonomy Database ('GTDB'). Also includes reference proteomes derived from the NCBI Reference Sequence ('RefSeq') database and manual mapping from the 'RDP Classifier' training set to 'RefSeq' taxonomy as described by Dick and Tan (2023) <doi:10.1007/s00248-022-01988-9>. Processes taxonomic classifications in 'RDP Classifier' format or OTU tables in 'phyloseq-class' objects from the Bioconductor package 'phyloseq'.
Maintained by Jeffrey Dick. Last updated 9 days ago.
16s-rrnacarbon-oxidation-statechemical-metricsgenomic-adaptationmicrobial-communities
4 stars 5.89 score 8 scripts
dzhakparov
GeneSelectR:Comprehensive Feature Selection Worfkflow for Bulk RNAseq Datasets
GeneSelectR is a versatile R package designed for efficient RNA sequencing data analysis. Its key innovation lies in the seamless integration of the Python sklearn machine learning framework with R-based bioinformatics tools. This integration enables GeneSelectR to perform robust ML-driven feature selection while simultaneously leveraging the power of Gene Ontology (GO) enrichment and semantic similarity analyses. By combining these diverse methodologies, GeneSelectR offers a comprehensive workflow that optimizes both the computational aspects of ML and the biological insights afforded by advanced bioinformatics analyses. Ideal for researchers in bioinformatics, GeneSelectR stands out as a unique tool for analyzing complex RNAseq datasets with enhanced precision and relevance.
Maintained by Damir Zhakparov. Last updated 10 months ago.
19 stars 4.98 score 7 scripts
vandomed
stocks:Stock Market Analysis
Functions for analyzing and visualizing stock market data. Main features are loading and aligning historical data, calculating performance metrics for individual funds or portfolios (e.g. annualized growth, maximum drawdown, Sharpe/Sortino ratio), and creating graphs.
Maintained by Dane R. Van Domelen. Last updated 5 years ago.
investment-analysisportfolio-constructionportfolio-optimizationsharpe-ratiostock-markettime-seriescpp
22 stars 4.63 score 39 scripts
gage1145
quicR:RT-QuIC Data Formatting and Analysis
Designed for the curation and analysis of data generated from real-time quaking-induced conversion (RT-QuIC) assays first described by Atarashi et al. (2011) <doi:10.1038/nm.2294>. 'quicR' calculates useful metrics such as maxpoint ratio: Rowden et al. (2023) <doi:10.1099/vir.0.069906-0>; time-to-threshold: Shi et al. (2013) <doi:10.1186/2051-5960-1-44>; and maximum slope. Integration with the output from plate readers allows for seamless input of raw data into the R environment.
Maintained by Gage Rowden. Last updated 12 days ago.
1 stars 4.06 score 11 scripts