An easy-to-use application for microarray, RNA-Seq and metabolomics analysis. For splicing sensitive platforms (RNA-Seq or Affymetrix Exon, Gene and Junction arrays), AltAnalyze will assess alternative exon (known and novel) expression along protein isoforms, domain composition and microRNA targeting. In addition to splicing-sensitive platforms, AltAnalyze provides comprehensive methods for the analysis of other data (RMA summarization, batch-effect removal, QC, statistics, annotation, clustering, network creation, lineage characterization, alternative exon visualization, gene-set enrichment and more).
CEL-Seq provides its first single-cell, on-chip barcoding method, and we detected gene expression changes accompanying the progression through the cell cycle in mouse fibroblast cells. The pipeline consists of the following steps: (1) demultiplexing: using the barcode from R1 we split R2 reads into their original samples creating a separate file for each sample. Since the unique molecular identifier (UMI) is also read in R1 we extract it and attach it to the R2 read metadata for downstream analysis; (2) mapping: using Bowtie2, we map the reads of the different samples in parallel, cutting the analysis time by roughly the number of available cores; (3) read counting: A modified version of the htseq-count script that supports the identification and elimination of reads sharing the same UMI to generate an accurate molecule count for each feature. We use binomial statistics to convert the number of UMIs into transcript counts. The different steps in the pipeline are wrapped together in a single program with a simple configuration file allowing to control for different run modes.
Contains useful tools for the analysis of single-cell gene expression data using the statistical software R. scater places an emphasis on tools for quality control, visualisation and pre-processing of data before further downstream analysis. scater enables the following: (i) automated computation of QC metrics; (ii) transcript quantification from read data with pseudo-alignment; (iii) data format standardisation; (iv) rich visualisations for exploratory analysis; (v) seamless integration into the Bioconductor universe; (vi) simple normalisation methods.
Reconstructs continuous biological processes at single-cell resolution. Waterfall is a pipeline that uses k-means clustering to build a trajectory and assign an individual cell a pseudotime based on each cell’s proximity to the cluster-derived trajectory. Adult neurogenesis was used as a model and the software was applied to other stem cell datasets. It can be used for single-cell omics analyses of various continuous biological processes.
Allows quality control (QC) and analysis components of parallel single cell transcriptome and epigenome data. Dr.seq is a quality control (QC) and analysis pipeline that provides both multifaceted QC reports and cell clustering results. Parallel single cell transcriptome data generated by different technologies can be transformed to the standard input with contained functions. Using relevant commands, the software can also be used to report quality measurements based on four aspects and can generate detailed analysis results for scATAC-seq and Drop-ChIP datasets.
Provides a way of removing amplification biases, the assumed absolute quantification does not appear to hold true perfectly. Umis is a flexible tool for counting the number of unique molecular identifiers. There are four steps in this method: (i) formatting reads, (ii) filtering noisy cellular barcodes, (iii) pseudo-mapping to cDNAs, and (iv) counting molecular identifiers. The quantitation used in umis handles reads that could come from multiple transcripts by assigning a fractional count to each transcript and then filtering for a minimum count at the end.
Processes Chromium single cell 3’ RNA-seq output to align reads, generates gene-cell matrices and performs clustering and gene expression analysis. Cell Ranger combines Chromium-specific algorithms with the widely-used RNA-seq aligner STAR. It is delivered as a single, self-contained tar file that can be unpacked anywhere on the system. The tool includes four pipelines: cellranger mkfastq; cellranger count; cellranger aggr; cellranger reanalyze.