limma

There are 0 repository under limma topic.

• jmzeng1314 / GEO

  geolimmagokegg
  Language:R 744

• nf-core / differentialabundance

  Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq

  nextflownf-corepipelineworkflowatac-seqchip-seqdeseq2differential-abundancedifferential-expressiongsealimmamicroarrayrna-seqshiny
  Language:Nextflow 46

• ComputationalProteomics / NormalyzerDE

  Tools for normalization, evaluation of outliers, technical biases and batch effects and differential expression analysis.

  bioconductorproteomicslimmabioinformaticsnormalization
  Language:R 18

• yafeng / DEqMS

  DEqMS is a tool for quantitative proteomic analysis

  limmaquantitative-proteomic-analysis
  Language:R 18

• eonurk / RNA-seq-differential-analyses-guideline

  A quick recap of widely used differential analyses methods in R for RNA-seq experiments

  edgerdeseq2limmalimma-voomlimma-trendrna-seq-pipeline
  12
• cinaR

  eonurk / cinaR

  A differential and enrichment analyses pipeline for bulk ATAC-seq (and RNA-seq)

  atac-sequnknown-batch-effectsedgerdeseq2limmadifferential-analysisenrichment-analysisgenesetsgene-setsrr-package
  Language:R 11

• dlaperriere / GEO_microarrays

  analyze_geo_microarrays.py : Differential expression analysis of published microarrays datasets from the NCBI Gene Expression Omnibus (GEO)

  microarraylimmabioinformaticsncbi-geo
  Language:Python 10

• peterlipan / DE_rpy2

  Differential expression analysis: DESeq2, edgeR, limma. Realized in python based on rpy2

  pandasdeseq2deseq2-analysisedgerlimmarlanguagedifferential-expression
  Language:Jupyter Notebook 10

• epigen / dea_limma

  A Snakemake workflow for performing and visualizing differential expression analyses (DEA) on NGS data powered by the R package limma.

  atac-seqbioinformaticsbiomedical-data-sciencechip-seqdifferential-expression-analysislimmalimma-trendlimma-voomrrna-seqscrna-seqsnakemakestatisticsvisualizationvolcano-plotworkflow
  Language:R 9

• dev-ev / isobaric-prot-wf-r

  Simple workflows for the isobaric-labeling proteomic data from Proteome Discoverer with ANOVA, t-testing, DEqMS/limma and annotation via fgsea

  data-visualizationdeqmslimmaproteomicsproteomics-datastatistical-analysistmt-data-analysis
  Language:R 5

• LieberInstitute / SPEAQeasyWorkshop2020

  EuroBioc2020 SPEAQeasy workshop https://eurobioc2020.bioconductor.org by Nick Eagles and Josh Stolz. For more information about SPEAQeasy check http://research.libd.org/SPEAQeasy/. For an example on how to use this RNA-seq processing pipeline and analyze the output files check http://research.libd.org/SPEAQeasy-example/.

  rstatsspeaqeasybioconductorlimmarnaseq-pipelinenextflownextflow-pipelines
  Language:R 3

• mejian1 / ExopherGeneExpressionProfiling

  Bioinformatic analysis of gene expression microarray profiles and DGEs on R and R studio

  differential-expressionelegansgenomicslimmancbi-geopythonrstudiotranscriptional-regulationdriscolllabgenefamilies
  Language:Jupyter Notebook 2

• mucosal-immunology-lab / microbiome-analysis

  A selection of analytical approaches, tools, and utilities for the processing of microbiome data derived from either 16S rRNA amplicon sequencing or shotgun metagenomics.

  limmamicrobiomemicrobiome-analysisphyloseq
  Language:R 2
• SPresnell_GSE147507

  BenaroyaResearch / SPresnell_GSE147507

  GSE147507 SARS-Cov-2 Dataset from Mt. Sinai

  rlimmadifferential-gene-expressioncovid-19sars-cov-2geo
  1

• SamThilmany / microarray-analysis_treatment-kinetics

  This R script is used to analyze microarray data acquired by an Agilent SureScan Microarray Scanner.

  limmamicroarraymicroarray-datamicroarray-data-analysisr
  Language:R 1

• aobermayer4 / CPTAC_LUAD_HaploAnalysis

  Methods overview with scripts looking at mtDNA and haplogroup association with CPTAC LUAD study.

  cptacluadredgerlimmaglimmadgehaplogroupnsclc
  Language:R 0

• BIGslu / 2022_ASM_Microbe_RNAseq

  limmarrna-seqrnaseqkimma
  Language:HTML 0

• Hemangini09 / Microarray-data-analysis

  This scripts involves five major steps including GEO dataset download, data normalization, data manipulation, fetching phenodata and feature data and differentially expressed genes (DEGs) analysis using R and bioconductor packages.

  affydiabetesgeoquerylimmadegs-screening
  Language:R 0

• Hemangini09 / RNA-seq-limma-voom-

  Performing RNA-seq data analysis with limma package

  degs-screeninglimmatcga
  Language:R 0

• LICMLeuven / LICMEpigenetics

  Provides easy to use, objective oriented functions for preprocessing methylation data produced by an Illumina Infinium BeadChip and detecting differentially methylated positions and regions within the DNA.

  repigeneticsminfilimmapreprocessing
  Language:R 0

• LsuhscBioinformatics / BIG-DE

  Gene Expression analysis with BIG-DE

  rshinyshinyappgene-expressionlimmavolcanoheatmapsbioinformatics
  Language:R 0

• nedaghohabi / TCGA-RNA-seq

  TCGA Colorectal Cancer RNA seq Data Analysis Pipeline

  limmarna-seq-analysistcgabiolinks
  Language:R 0

• zjyoung9490 / Gene-Expression-Analysis-of-Prostate-Tumor-Samples

  Normalization, outlier detection, statistical analysis, and visualization of microarray data from 79 tumor samples to identify differentially expressed genes between recurrent and non-recurrent prostate cancer.

  geoquerymarraymulttestlimmamasssamrbioconductorr
  0

• kmyafi / Breast-Cancer-Differential-Gene-Expression-Analysis

  Differential Gene Expression (DGE) Analysis in Curated Microarray Data of Breast Cancer Subtypes

  breast-cancerdifferential-gene-expressiongene-expressiongene-ontologylimmamicroarraygene-filteringr
  Language:R

• rgarcia-herrera / tuberculosis-diff

  Tuberculosis@LOG and NPR, Macrophage gene expression time series.

  microarrayagilentlimmatuberculosisgenomics
  Language:Python