Drosophila melanogaster has been a popular model organism in the study of sleep and circadian rhythm.The Drosophila activity monitoring(DAM)system is one of the many tools developed for investigating sleep behavior in...Drosophila melanogaster has been a popular model organism in the study of sleep and circadian rhythm.The Drosophila activity monitoring(DAM)system is one of the many tools developed for investigating sleep behavior in fruit flies and has been acknowledged by researchers around the world for its simplicity and cost-effectiveness.Based on the simple activity data collected by the DAM system,a wide range of parameters can be generated for sleep and circadian studies.However,current programs that analyze DAM data cover a limited number of metrics and fail to provide individual data for the user to plot graphs and conduct analysis using other software.Therefore,we have developed SleepyFlyR,an R package that:(1)is simple and easy to use with a user-friendly user interface script;(2)provides a comprehensive analysis of sleep and activity parameters;(3)generates double-plotted graphs for sleep and activity patterns;(4)offers visualization of sleep and activity profiles across multiple days or within a single day;(5)calculates the changes of sleep and activity parameters between baseline and experiment;(6)stores both summary data and individual data in files with unique title.展开更多
The past two decades have witnessed a revolution in identifying genetic risk factors underlying diseases and complex traits using genome-wide association studies （GWAS） （Risch and Merikangas, 1996; Hirschhom and Da...The past two decades have witnessed a revolution in identifying genetic risk factors underlying diseases and complex traits using genome-wide association studies （GWAS） （Risch and Merikangas, 1996; Hirschhom and Daly, 2005; Altshuler et al., 2008）. Together with advanced high-throughput technologies for genotyping and sequencing, GWAS have discovered thousands of susceptibility loci for various traits （Welter et al., 2014）.展开更多
QTLNetworkR is an R package that aims to provide a user-friendly and platform-independent tool to visualize quantitative trait loci (QTL) mapping results. The graphical functions of the QTLNetworkR are based upon latt...QTLNetworkR is an R package that aims to provide a user-friendly and platform-independent tool to visualize quantitative trait loci (QTL) mapping results. The graphical functions of the QTLNetworkR are based upon lattice and grid packages, and the graphical user interface (GUI) of the QTLNetworkR is built upon RGtk2 and gWidgetsRGtk2 packages. Six functions are designed to help visualize marker interval, putative QTL, QTL-by- environment interactions, marker interval interactions, epistasis, and the predicted genetic architecture of complex traits. It is especially helpful in profiling results for multiple traits at multiple environments. The current version of QTLNetworkR is able to accept QTL mapping results from QTLNetwork, and it is ready for possible extensions to import results from some other QTL mapping software packages. In addition, we presented a QTL mapping result in rice (Oryza sativa) as an example to describe the features of QTLNetworkR.展开更多
Accurate estimation of crop evapotranspiration(ETc) and soil water balance, which is vital for optimizing water management strategy in crop production, can be performed by simulation. But existing software has many de...Accurate estimation of crop evapotranspiration(ETc) and soil water balance, which is vital for optimizing water management strategy in crop production, can be performed by simulation. But existing software has many deficiencies, including complex operation, limited scalability, lack of batch processing, and a single ETc model. Here we present simET, an open-source software package written in the R programming language. Many concepts involved in crop ETc simulation are condensed into functions in the package. It includes three widely used crop ETc models built on these functions: the single-crop coefficient,double-crop coefficient, and Shuttleworth–Wallace models, along with tools for preparing model data and comparing estimates. SimET supports ETc simulation in crops with repeated growth cycles such as alfalfa, a perennial forage crop that is cut multiple times annually.展开更多
The Owen’s T function is presented in four new ways, one of them as a series similar to the Euler’s arctangent series divided by 2π, which is its majorant series. All possibilities enable numerically stable ...The Owen’s T function is presented in four new ways, one of them as a series similar to the Euler’s arctangent series divided by 2π, which is its majorant series. All possibilities enable numerically stable and fast convergent computation of the bivariate normal integral with simple recursion. When tested computation on a random sample of one million parameter triplets with uniformly distributed components and using double precision arithmetic, the maximum absolute error was 3.45 × 10<sup>-</sup><sup>16</sup>. In additional testing, focusing on cases with correlation coefficients close to one in absolute value, when the computation may be very sensitive to small rounding errors, the accuracy was retained. In rare potentially critical cases, a simple adjustment to the computation procedure was performed—one potentially critical computation was replaced with two equivalent non-critical ones. All new series are suitable for vector and high-precision computation, assuming they are supplemented with appropriate efficient and accurate computation of the arctangent and standard normal cumulative distribution functions. They are implemented by the R package Phi2rho, available on CRAN. Its functions allow vector arguments and are ready to work with the Rmpfr package, which enables the use of arbitrary precision instead of double precision numbers. A special test with up to 1024-bit precision computation is also presented.展开更多
Metallic elements have various origins: natural and anthropogenic sources as geochemical, marine and atmospheric sources resulting from the fallout of pollutants emitted or dust raised and which are transported by wat...Metallic elements have various origins: natural and anthropogenic sources as geochemical, marine and atmospheric sources resulting from the fallout of pollutants emitted or dust raised and which are transported by water and air currents. Thus marine, brackish and fresh continental waters may have high metal concentrations. In addition, some essential metals can become toxic above certain concentration values in aquatic environments. The aquatic ecosystems of Cotonou channel and lake Nokoué receive the pollutants charges from the town cities of Cotonou, Abomey-Calavi and town hall of So Ava. The aim of this study is to analyze waters from Eighteen (18) stations identified in the two ecosystems (nine by ecosystem). The concentrations of magnesium (Mg), calcium (Ca), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), cadmium (Cd), beryllium (Be), aluminum (Al), strontium (Sr), molybdenum (Mo), silver (Ag), tin (Sn), barium (Ba), platinum (Pt), mercury (Hg), thallium (Tl), lead (Pb), thorium (Th) and uranium (U) were measured after acid digestion of the water samples using the inductively coupled plasma source mass spectrometer (ICP-MS). The results of the analyses indicate an unequal distribution of metals in the different ecosystems. However, atypical concentrations were observed at some stations of the lake and the channel. Magnesium, calcium and manganese have very high values in Lake Nokoué respectively at Ganvié market station GAN_M (2990 ± 105 mg/L), Ganvié center, station GAN_C (4991 ± 177 mg/L) and Lake middle station MLak4 (10662 ± 17.03 μg/L). On the other hand, iron, aluminum and strontium have very high concentrations in the Cotonou Channel respectively at Agbato station AGB (5236 ± 103 and 8289 ± 519 μg/L) and at the estuary station EST (6118 ± 68 μg/L). The concentrations were compared to wells and cborehole waters in sixth neighborhood of Cotonou. We have used statistical analyzers such as MANOVA which have made it possible to classify the waters and metals in the ecosystems studied compared to groundwater and Well water waters. We use hierarchical clustering on principal components to identify similarities between stations based on metal concentration with R software packages “FactoMineR” and “factoextra”. In general, we can conclude that most of the metals have an anthropogenic source except strontium and major elements (Ca and Mg) which could respectively provide from marine waters and geochemical sources.展开更多
The comparative analysis of gene regulatory networks(GRNs)across various biological conditions reveals crucial shifts in regulatory mechanisms,shedding light on how genetic and environmental signals influence gene fun...The comparative analysis of gene regulatory networks(GRNs)across various biological conditions reveals crucial shifts in regulatory mechanisms,shedding light on how genetic and environmental signals influence gene function.Recent advances in highresolution technologies have provided support and made it possible to profile gene expression at the single-cell level,thereby enabling more precise studies of transcriptional regulation.We have developed the scTen i fol dNet and scTeni foldKnk R packages,which offer streamlined workflows for constructing single-cell gene regulatory networks(scGRNs)and facilitating comparisons across different samples or between pre-and postgene perturbation states.Both packages employ a"tensor decomposition+manifold alignment"approach to achieve robust and effective comparisons.展开更多
Single-cell RNA sequencing(scRNA-seq)and spatial transcriptomics(ST)techniques hold great value in evaluating the heterogeneity and spatial characteristics of hematopoietic cells within tissues.These two techniques ar...Single-cell RNA sequencing(scRNA-seq)and spatial transcriptomics(ST)techniques hold great value in evaluating the heterogeneity and spatial characteristics of hematopoietic cells within tissues.These two techniques are highly complementary,with scRNA-seq offering single-cell resolution and ST retaining spatial information.However,there is an urgent demand for well-organized and user-friendly toolkits capable of handling single-cell and spatial information.Here,we present HemaScope,a specialized bioinformatics toolkit featuring modular designs to analyze scRNA-seq and ST data generated from hematopoietic cells.It enables users to perform quality control,basic analysis,cell atlas construction,cellular heterogeneity exploration,and dynamical examination on scRNA-seq data.Also,it can perform spatial analysis and microenvironment analysis on ST data.Meanwhile,HemaScope takes into consideration hematopoietic cell-specific features,including lineage affiliation evaluation,cell cycle prediction,and marker gene collection.To enhance the user experience,we have deployed the toolkit in user-friendly forms:HemaScopeR(an R package),HemaScopeCloud(a web server),HemaScopeDocker(a Docker image),and HemaScopeShiny(a graphical interface).In case studies,we employed it to construct a cell atlas of human bone marrow,analyze age-related changes,and identify acute myeloid leukemia cells in mice.Moreover,we characterized the microenvironments in angioimmunoblastic T cell lymphoma and primary central nervous system lymphoma,elucidating tumor boundaries.HemaScope is freely available at https://zhenyiwangthu.github.io/HemaScope_Tutorial/.展开更多
Our study introduces scITDG,a tool designed for the analysis of time-dependent gene expression in single-cell transcriptomic sequencing data,effectively filling a gap in current analytical resources.A key advantage of...Our study introduces scITDG,a tool designed for the analysis of time-dependent gene expression in single-cell transcriptomic sequencing data,effectively filling a gap in current analytical resources.A key advantage of scITDG is its ability to identify dynamic gene expression patterns across multiple time points at single-cell resolution,which is pivotal for deciphering com-plex biological processes such as aging and tissue regeneration.The tool is compatible with widely used single-cell analysis platforms such as Seurat and Scanpy.By integrating natural cubic splines regression with bootstrapping resampling,scITDG enhances the functionality of these platforms and broadens their applicability.In this study,based on scITDG,we revealed intricate gene expression modules in mice aging and axolotl limb regeneration,providing valuable insights into cellular function and response mechanisms.The versatility of scITDG makes it applicable to a wide range of biological contexts,including development,circadian rhythms,disease progression,and therapeutic responses.展开更多
The field of ecology has been greatly enhanced by the integration of computational tools and statistical methods,with the programming language R emerging as a pivotal and flexible tool for ecological research.As ecolo...The field of ecology has been greatly enhanced by the integration of computational tools and statistical methods,with the programming language R emerging as a pivotal and flexible tool for ecological research.As ecological studies accelerate,understanding the prevalent trends and specific usage patterns of R in recent research is crucial.This study investigated the use of R and its packages in 125494 scholarly articles published in 40 ecology journals from 2008 to 2023.A total of 52658 articles(42%)designated R as their principal analytical tool,demonstrating a steady linear growth in its utilization from 10.3%in 2008 to 66.9%in 2023.Twelve R packages,including'lme4','vegan','nlme','MuMln','ape','ggplot2','car','mgcv','MAsS','raster','multcomp and'lmerTest',each played a pivotal role in contributing to more than 1000 scholarly articles.The highest usage rate of the'lme4'package indicates that mixed-effect models have a particularly important role in ecological research,and the application of these models has helped ecologists solve many important scientific problems.Journal-specific package preferences aligned with their scientific domains,while the rise in the average number of R packages per article indicates a trend towards more complex and diverse analytical methods in ecology.Our findings reveal a reciprocal relationship between the development of R and ecological research,underscoring the need for collaboration among quantitative ecologists,R developers and ecologists to further advance both the language and the field.Such collaboration will not only enhance the functionality and versatility of R but also provide robust technical support for the continued progress of ecological research.展开更多
Dissolved organic matter(DOM)contains thousands of molecules and is key for biogeochemical cycles in aquatic and terrestrial ecosystems by interacting with microbes.Over the last decade,the study of DOM has been advan...Dissolved organic matter(DOM)contains thousands of molecules and is key for biogeochemical cycles in aquatic and terrestrial ecosystems by interacting with microbes.Over the last decade,the study of DOM has been advanced and accelerated with the developments of instrumental and statistical approaches.However,it is still challenging in statistical analyses,data visualization,and theoretical interpretations largely due to the complexity of molecular composition and underlying ecological mechanisms.In this study,we developed an R package iDOM with functions for the basic and advanced statistical analyses and the visualization of DOM derived from Fourier transform ion cyclotron resonance mass spectrometer(FT‐ICR MS).The package could handle various data types of DOM,including molecular compositional data,molecular traits,and uncharacterized molecules(i.e.,dark matter).It could integrate explanatory data,such as environmental and microbial data,to explore the relationships between DOM and abiotic or biotic drivers.To illustrate its use,we presented case studies with an example dataset of DOM and microbial communities under experimental warming.We included case studies of basic functions for the calculation of molecular traits,the assignment of molecular classes,and the compositional analyses of chemical diversity and dissimilarity.We further showed the case studies with advanced functions to quantify DOM assembly processes,assess the effects of dark matter on molecular interactions,analyze the ecological networks between DOM and microbes,and explore their response to warming.The source code and example dataset of iDOM are publicly available on https://github.com/jianjunwang/iDOM.We expect that iDOM will serve as a comprehensive pipeline for DOM statistical analyses and bridge the gap between chemical characterization and ecological interpretation in a theoretical framework.展开更多
With the gradual maturity of sequencing technology,many microbiome studies have published,driving the emergence and advance of related analysis tools.R language is the widely used platform for microbiome data analysis...With the gradual maturity of sequencing technology,many microbiome studies have published,driving the emergence and advance of related analysis tools.R language is the widely used platform for microbiome data analysis for powerful functions.However,tens of thousands of R packages and numerous similar analysis tools have brought major challenges for many researchers to explore microbiome data.How to choose suitable,efficient,convenient,and easy-to-learn tools from the numerous R packages has become a problem for many microbiome researchers.We have organized 324 common R packages for microbiome analysis and classified them according to application categories(diversity,difference,biomarker,correlation and network,functional prediction,and others),which could help researchers quickly find relevant R packages for microbiome analysis.Furthermore,we systematically sorted the integrated R packages(phyloseq,microbiome,MicrobiomeAnalystR,Animalcules,microeco,and amplicon)for microbiome analysis,and summarized the advantages and limitations,which will help researchers choose the appropriate tools.Finally,we thoroughly reviewed the R packages for microbiome analysis,summarized most of the common analysis content in the microbiome,and formed the most suitable pipeline for microbiome analysis.This paper is accompanied by hundreds of examples with 10,000 lines codes in GitHub,which can help beginners to learn,also help analysts compare and test different tools.This paper systematically sorts the application of R in microbiome,providing an important theoretical basis and practical reference for the development of better microbiome tools in the future.All the code is available at GitHub github.com/taowenmicro/EasyMicrobiomeR.展开更多
In recent years,perovskite has received increasing attention in the medical field.However,there has been a lack of related bibliometric analysis in this research field.This study aims to analyse the research status an...In recent years,perovskite has received increasing attention in the medical field.However,there has been a lack of related bibliometric analysis in this research field.This study aims to analyse the research status and hot topics of perovskite in the medical field from a bibliometric perspective and explore the research direction of perovskite.This study collected 1852 records of perovskite research in the medical field from 1983 to 2022 in the Web of Science(WOS)database.The country,institution,journal,cited references,and keywords were analysed using CiteSpace,VOS viewer,and Bibliometrix software.The number of articles related to perovskite research in the medical field has been increasing every year.China and USA have published the most papers and are the main forces in this research field.The University of London Imperial College of Science,Technology,and Medicine is the most active institution and has contributed the most publications.ACS Applied Materials&Interfaces is the most prolific journal in this field.“Medical electronic devices”,“X-rays”,and“piezoelectric materials”are the most researched directions of perovskite in the medical field.“Performance”,“perovskite”,and“solar cells”are the most frequently used keywords in this field.Advanced Materials is the most relevant and academically influential journal for perovskite research.Halide perovskites have been a hot topic in this field in recent years and will be a future research trend.X-ray,electronic medical equipment,and medical stents are the main research directions.展开更多
基金the National Natural Science Foundation of China(No.81970999)the Shanghai Rising Star Project(No.19QA1404900)。
文摘Drosophila melanogaster has been a popular model organism in the study of sleep and circadian rhythm.The Drosophila activity monitoring(DAM)system is one of the many tools developed for investigating sleep behavior in fruit flies and has been acknowledged by researchers around the world for its simplicity and cost-effectiveness.Based on the simple activity data collected by the DAM system,a wide range of parameters can be generated for sleep and circadian studies.However,current programs that analyze DAM data cover a limited number of metrics and fail to provide individual data for the user to plot graphs and conduct analysis using other software.Therefore,we have developed SleepyFlyR,an R package that:(1)is simple and easy to use with a user-friendly user interface script;(2)provides a comprehensive analysis of sleep and activity parameters;(3)generates double-plotted graphs for sleep and activity patterns;(4)offers visualization of sleep and activity profiles across multiple days or within a single day;(5)calculates the changes of sleep and activity parameters between baseline and experiment;(6)stores both summary data and individual data in files with unique title.
基金supported by the Fundamental Research Funds for the Central Universities (BLX2013026)the National Natural Science Foundation of China (No. 31470675)+2 种基金the National Institutes of Health (K01AA023321)supported by the National Heart, Lung, and Blood Institute in collaboration with Boston University (Contract No. N01-HC-25195)Funding for SHARe Affymetrix genotyping was provided by NHLBI Contract N02-HL-64278
文摘The past two decades have witnessed a revolution in identifying genetic risk factors underlying diseases and complex traits using genome-wide association studies （GWAS） （Risch and Merikangas, 1996; Hirschhom and Daly, 2005; Altshuler et al., 2008）. Together with advanced high-throughput technologies for genotyping and sequencing, GWAS have discovered thousands of susceptibility loci for various traits （Welter et al., 2014）.
基金Project supported by the National Basic Research Program (973) of China (No. 2008CB117002)the Ministry of Agriculture Public Benefit Research Foundation of China (No. 200803034)the National High-Tech R & D Program (863) of China (No. 2006AA10A102)
文摘QTLNetworkR is an R package that aims to provide a user-friendly and platform-independent tool to visualize quantitative trait loci (QTL) mapping results. The graphical functions of the QTLNetworkR are based upon lattice and grid packages, and the graphical user interface (GUI) of the QTLNetworkR is built upon RGtk2 and gWidgetsRGtk2 packages. Six functions are designed to help visualize marker interval, putative QTL, QTL-by- environment interactions, marker interval interactions, epistasis, and the predicted genetic architecture of complex traits. It is especially helpful in profiling results for multiple traits at multiple environments. The current version of QTLNetworkR is able to accept QTL mapping results from QTLNetwork, and it is ready for possible extensions to import results from some other QTL mapping software packages. In addition, we presented a QTL mapping result in rice (Oryza sativa) as an example to describe the features of QTLNetworkR.
基金jointly supported by the National Natural Science Foundation of China (32171679 and 32201475)。
文摘Accurate estimation of crop evapotranspiration(ETc) and soil water balance, which is vital for optimizing water management strategy in crop production, can be performed by simulation. But existing software has many deficiencies, including complex operation, limited scalability, lack of batch processing, and a single ETc model. Here we present simET, an open-source software package written in the R programming language. Many concepts involved in crop ETc simulation are condensed into functions in the package. It includes three widely used crop ETc models built on these functions: the single-crop coefficient,double-crop coefficient, and Shuttleworth–Wallace models, along with tools for preparing model data and comparing estimates. SimET supports ETc simulation in crops with repeated growth cycles such as alfalfa, a perennial forage crop that is cut multiple times annually.
文摘The Owen’s T function is presented in four new ways, one of them as a series similar to the Euler’s arctangent series divided by 2π, which is its majorant series. All possibilities enable numerically stable and fast convergent computation of the bivariate normal integral with simple recursion. When tested computation on a random sample of one million parameter triplets with uniformly distributed components and using double precision arithmetic, the maximum absolute error was 3.45 × 10<sup>-</sup><sup>16</sup>. In additional testing, focusing on cases with correlation coefficients close to one in absolute value, when the computation may be very sensitive to small rounding errors, the accuracy was retained. In rare potentially critical cases, a simple adjustment to the computation procedure was performed—one potentially critical computation was replaced with two equivalent non-critical ones. All new series are suitable for vector and high-precision computation, assuming they are supplemented with appropriate efficient and accurate computation of the arctangent and standard normal cumulative distribution functions. They are implemented by the R package Phi2rho, available on CRAN. Its functions allow vector arguments and are ready to work with the Rmpfr package, which enables the use of arbitrary precision instead of double precision numbers. A special test with up to 1024-bit precision computation is also presented.
文摘Metallic elements have various origins: natural and anthropogenic sources as geochemical, marine and atmospheric sources resulting from the fallout of pollutants emitted or dust raised and which are transported by water and air currents. Thus marine, brackish and fresh continental waters may have high metal concentrations. In addition, some essential metals can become toxic above certain concentration values in aquatic environments. The aquatic ecosystems of Cotonou channel and lake Nokoué receive the pollutants charges from the town cities of Cotonou, Abomey-Calavi and town hall of So Ava. The aim of this study is to analyze waters from Eighteen (18) stations identified in the two ecosystems (nine by ecosystem). The concentrations of magnesium (Mg), calcium (Ca), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), selenium (Se), cadmium (Cd), beryllium (Be), aluminum (Al), strontium (Sr), molybdenum (Mo), silver (Ag), tin (Sn), barium (Ba), platinum (Pt), mercury (Hg), thallium (Tl), lead (Pb), thorium (Th) and uranium (U) were measured after acid digestion of the water samples using the inductively coupled plasma source mass spectrometer (ICP-MS). The results of the analyses indicate an unequal distribution of metals in the different ecosystems. However, atypical concentrations were observed at some stations of the lake and the channel. Magnesium, calcium and manganese have very high values in Lake Nokoué respectively at Ganvié market station GAN_M (2990 ± 105 mg/L), Ganvié center, station GAN_C (4991 ± 177 mg/L) and Lake middle station MLak4 (10662 ± 17.03 μg/L). On the other hand, iron, aluminum and strontium have very high concentrations in the Cotonou Channel respectively at Agbato station AGB (5236 ± 103 and 8289 ± 519 μg/L) and at the estuary station EST (6118 ± 68 μg/L). The concentrations were compared to wells and cborehole waters in sixth neighborhood of Cotonou. We have used statistical analyzers such as MANOVA which have made it possible to classify the waters and metals in the ecosystems studied compared to groundwater and Well water waters. We use hierarchical clustering on principal components to identify similarities between stations based on metal concentration with R software packages “FactoMineR” and “factoextra”. In general, we can conclude that most of the metals have an anthropogenic source except strontium and major elements (Ca and Mg) which could respectively provide from marine waters and geochemical sources.
文摘The comparative analysis of gene regulatory networks(GRNs)across various biological conditions reveals crucial shifts in regulatory mechanisms,shedding light on how genetic and environmental signals influence gene function.Recent advances in highresolution technologies have provided support and made it possible to profile gene expression at the single-cell level,thereby enabling more precise studies of transcriptional regulation.We have developed the scTen i fol dNet and scTeni foldKnk R packages,which offer streamlined workflows for constructing single-cell gene regulatory networks(scGRNs)and facilitating comparisons across different samples or between pre-and postgene perturbation states.Both packages employ a"tensor decomposition+manifold alignment"approach to achieve robust and effective comparisons.
基金supported by the CAMS Innovation Fund for Medical Sciences(Grant No.CIFMS 2021-I2M-5-010)the China National Postdoctoral Program for Innovative Talents(Grant No.BX20230229)+2 种基金the China Postdoctoral Science Foundation(Grant No.2024M752038)the National Natural Science Foundation of China(Grant No.32470681)the Innovative Research Team of High-Level Local Universities in Shanghai.
文摘Single-cell RNA sequencing(scRNA-seq)and spatial transcriptomics(ST)techniques hold great value in evaluating the heterogeneity and spatial characteristics of hematopoietic cells within tissues.These two techniques are highly complementary,with scRNA-seq offering single-cell resolution and ST retaining spatial information.However,there is an urgent demand for well-organized and user-friendly toolkits capable of handling single-cell and spatial information.Here,we present HemaScope,a specialized bioinformatics toolkit featuring modular designs to analyze scRNA-seq and ST data generated from hematopoietic cells.It enables users to perform quality control,basic analysis,cell atlas construction,cellular heterogeneity exploration,and dynamical examination on scRNA-seq data.Also,it can perform spatial analysis and microenvironment analysis on ST data.Meanwhile,HemaScope takes into consideration hematopoietic cell-specific features,including lineage affiliation evaluation,cell cycle prediction,and marker gene collection.To enhance the user experience,we have deployed the toolkit in user-friendly forms:HemaScopeR(an R package),HemaScopeCloud(a web server),HemaScopeDocker(a Docker image),and HemaScopeShiny(a graphical interface).In case studies,we employed it to construct a cell atlas of human bone marrow,analyze age-related changes,and identify acute myeloid leukemia cells in mice.Moreover,we characterized the microenvironments in angioimmunoblastic T cell lymphoma and primary central nervous system lymphoma,elucidating tumor boundaries.HemaScope is freely available at https://zhenyiwangthu.github.io/HemaScope_Tutorial/.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDC0200000)the National Natural Science Foundation of China(82322025,82488301,82125011,82271600,82361148131)+15 种基金the National Key Research and Development Pro-gram of China(2022YFA1103700,2020YFA0804000)the Stra-tegic Priority Research Program of the Chinese Academy of Sci-ences(XDA0460403)the National Natural Science Foundation of China(92168201,82330044,32341001,32121001,82192863,82361148130,8231101626)Non-Communicable Chronic Diseases-National Science and Technology Major Project(2024ZD0530400)Youth Innovation Promotion Association of CAS(2022083)Young Elite Scientists Sponsorship Program by CAST(2021QNRC001)International Partnership Program of Chinese Academy of Sciences(073GJHZ2023019FN)he Program of the Beijing Natural Science Foundation(JQ24044,Z240018,F251011,Z230011)Shenzhen Medi-cal Research Fund(C2406001)CAS Project for Young Scientists in Basic Research(YSBR-076,YSBR-012)the Informatization Plan of Chinese Academy of Sciences(CAS-WX2022SDC-XK14)New Cor-nerstone Science Foundation through the XPLORER PRIZE(2021-1045)Beijing Municipal Public Welfare Development and Reform Pilot Project for Medical Research Institutes(JYY2023-13)CAS Youth Interdisciplinary Team,Key Laboratory of Alzheimer's Disease of Zhejiang Province(ZJAD-2024001)Initiative Scientific Research Program,Institute of Zoology,CAS(2023IOZ0102,2023IOZ0202,2024IOZ0103)Beijing Anzhen Hospital High Level Research Funding(2024AZB3002).
文摘Our study introduces scITDG,a tool designed for the analysis of time-dependent gene expression in single-cell transcriptomic sequencing data,effectively filling a gap in current analytical resources.A key advantage of scITDG is its ability to identify dynamic gene expression patterns across multiple time points at single-cell resolution,which is pivotal for deciphering com-plex biological processes such as aging and tissue regeneration.The tool is compatible with widely used single-cell analysis platforms such as Seurat and Scanpy.By integrating natural cubic splines regression with bootstrapping resampling,scITDG enhances the functionality of these platforms and broadens their applicability.In this study,based on scITDG,we revealed intricate gene expression modules in mice aging and axolotl limb regeneration,providing valuable insights into cellular function and response mechanisms.The versatility of scITDG makes it applicable to a wide range of biological contexts,including development,circadian rhythms,disease progression,and therapeutic responses.
基金supported by the National Nature Science Foundation of China(grant nos 32271551,42271051,42471054)Jiangsu Social Development Project(grant no.BE2022792)the Metasequoia fund of Nanjing Forestry University.
文摘The field of ecology has been greatly enhanced by the integration of computational tools and statistical methods,with the programming language R emerging as a pivotal and flexible tool for ecological research.As ecological studies accelerate,understanding the prevalent trends and specific usage patterns of R in recent research is crucial.This study investigated the use of R and its packages in 125494 scholarly articles published in 40 ecology journals from 2008 to 2023.A total of 52658 articles(42%)designated R as their principal analytical tool,demonstrating a steady linear growth in its utilization from 10.3%in 2008 to 66.9%in 2023.Twelve R packages,including'lme4','vegan','nlme','MuMln','ape','ggplot2','car','mgcv','MAsS','raster','multcomp and'lmerTest',each played a pivotal role in contributing to more than 1000 scholarly articles.The highest usage rate of the'lme4'package indicates that mixed-effect models have a particularly important role in ecological research,and the application of these models has helped ecologists solve many important scientific problems.Journal-specific package preferences aligned with their scientific domains,while the rise in the average number of R packages per article indicates a trend towards more complex and diverse analytical methods in ecology.Our findings reveal a reciprocal relationship between the development of R and ecological research,underscoring the need for collaboration among quantitative ecologists,R developers and ecologists to further advance both the language and the field.Such collaboration will not only enhance the functionality and versatility of R but also provide robust technical support for the continued progress of ecological research.
基金supported by the National Natural Science Foundation of China(42225708,U24A20578,42377122,92251304,and 42077052)Basic Research Program of Jiangsu Province(BK20240111)+2 种基金the Research Program of Sino‐Africa Joint Research Center,Chinese Academy of Sciences(151542KYSB20210007)Science and Technology Planning Project of NIGLAS(NIGLAS2022GS09)Key Laboratory of Lake and Watershed Science for Water Security(NKL2023‐QN04).
文摘Dissolved organic matter(DOM)contains thousands of molecules and is key for biogeochemical cycles in aquatic and terrestrial ecosystems by interacting with microbes.Over the last decade,the study of DOM has been advanced and accelerated with the developments of instrumental and statistical approaches.However,it is still challenging in statistical analyses,data visualization,and theoretical interpretations largely due to the complexity of molecular composition and underlying ecological mechanisms.In this study,we developed an R package iDOM with functions for the basic and advanced statistical analyses and the visualization of DOM derived from Fourier transform ion cyclotron resonance mass spectrometer(FT‐ICR MS).The package could handle various data types of DOM,including molecular compositional data,molecular traits,and uncharacterized molecules(i.e.,dark matter).It could integrate explanatory data,such as environmental and microbial data,to explore the relationships between DOM and abiotic or biotic drivers.To illustrate its use,we presented case studies with an example dataset of DOM and microbial communities under experimental warming.We included case studies of basic functions for the calculation of molecular traits,the assignment of molecular classes,and the compositional analyses of chemical diversity and dissimilarity.We further showed the case studies with advanced functions to quantify DOM assembly processes,assess the effects of dark matter on molecular interactions,analyze the ecological networks between DOM and microbes,and explore their response to warming.The source code and example dataset of iDOM are publicly available on https://github.com/jianjunwang/iDOM.We expect that iDOM will serve as a comprehensive pipeline for DOM statistical analyses and bridge the gap between chemical characterization and ecological interpretation in a theoretical framework.
基金This study was financially supported by the Agricultural Science and Technology Innovation Program(CAAS-ZDRW202308)the Natural Science Foundation of China(42277297,42090060,U21A20182)+2 种基金Jiangsu Funding Program for Excellent Postdoctoral Talent(2022ZB325)Scientific and technology innovation project of China Academy of Chinese Medical Sciences(C12021A04115)the Fundamental Research Funds for the Central public welfare research institutes(ZZ13-YQ-095).
文摘With the gradual maturity of sequencing technology,many microbiome studies have published,driving the emergence and advance of related analysis tools.R language is the widely used platform for microbiome data analysis for powerful functions.However,tens of thousands of R packages and numerous similar analysis tools have brought major challenges for many researchers to explore microbiome data.How to choose suitable,efficient,convenient,and easy-to-learn tools from the numerous R packages has become a problem for many microbiome researchers.We have organized 324 common R packages for microbiome analysis and classified them according to application categories(diversity,difference,biomarker,correlation and network,functional prediction,and others),which could help researchers quickly find relevant R packages for microbiome analysis.Furthermore,we systematically sorted the integrated R packages(phyloseq,microbiome,MicrobiomeAnalystR,Animalcules,microeco,and amplicon)for microbiome analysis,and summarized the advantages and limitations,which will help researchers choose the appropriate tools.Finally,we thoroughly reviewed the R packages for microbiome analysis,summarized most of the common analysis content in the microbiome,and formed the most suitable pipeline for microbiome analysis.This paper is accompanied by hundreds of examples with 10,000 lines codes in GitHub,which can help beginners to learn,also help analysts compare and test different tools.This paper systematically sorts the application of R in microbiome,providing an important theoretical basis and practical reference for the development of better microbiome tools in the future.All the code is available at GitHub github.com/taowenmicro/EasyMicrobiomeR.
基金Key Supported Projects of the Joint Fund of the National Natural Science Foundation of China,No.U22A20357the National Key R&D Program of China,No.2020YFC1107601the Natural Science Foundation of Hebei Province-for Distinguished Young Scholars,No.H2021206329.
文摘In recent years,perovskite has received increasing attention in the medical field.However,there has been a lack of related bibliometric analysis in this research field.This study aims to analyse the research status and hot topics of perovskite in the medical field from a bibliometric perspective and explore the research direction of perovskite.This study collected 1852 records of perovskite research in the medical field from 1983 to 2022 in the Web of Science(WOS)database.The country,institution,journal,cited references,and keywords were analysed using CiteSpace,VOS viewer,and Bibliometrix software.The number of articles related to perovskite research in the medical field has been increasing every year.China and USA have published the most papers and are the main forces in this research field.The University of London Imperial College of Science,Technology,and Medicine is the most active institution and has contributed the most publications.ACS Applied Materials&Interfaces is the most prolific journal in this field.“Medical electronic devices”,“X-rays”,and“piezoelectric materials”are the most researched directions of perovskite in the medical field.“Performance”,“perovskite”,and“solar cells”are the most frequently used keywords in this field.Advanced Materials is the most relevant and academically influential journal for perovskite research.Halide perovskites have been a hot topic in this field in recent years and will be a future research trend.X-ray,electronic medical equipment,and medical stents are the main research directions.
