Cell Browser: Visualize single-cell clustering data

The Cell Browser allows for the visualization of single-cell clustering data with the option to color cell by metadata attributes such as sex, age, and gene expression. A number of published datasets are available through the Cell Browser website or set up a Cell Browser for your own data using the code on GitHub.
Cell - Browser Website

The Cell Browser was created by Max Haeussler.

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PluriTest: Check for Pluripotency

Pluritest allows you check your samples for pluripotentcy through uploading RNA-seq fastq files or Affymetrix and Illumina arrays. Note: Use of Pluritest requires you to register an account.
Müller FJ, Schuldt BM, Williams R, Mason D, Altun G, Papapetrou EP, Danner S, Goldmann JE, Herbst A, Schmidt NO et al. A bioinformatic assay for pluripotency in human cells. Nat Methods. 2011 Apr;8(4):315-7. PMID: 21378979; PMC: PMC3265323
PluriTest Website

PluriTest was created by Roy Williams and the Jeanne Loring Lab.

Pgltools: Manipulate Hi-C and ChIA-PET data

The pgltools package gives you a number of utilities for manipulating files in the "paired genomic loci" format, common in both Hi-C and ChIA-PET experiments. These utilities allow you to things such as convert pgl files to a number of other formats, compare and contrast multiple pgl files, and other basic operations like sorting or merging files.
Greenwald WW, Li H, Smith EN, Benaglio P, Nariai N, Frazer KA. Pgltools: a genomic arithmetic tool suite for manipulation of Hi-C peak and other chromatin interaction data. BMC Bioinformatics. 2017 Apr 7;18(1):207. PMID: 28388874; PMC: PMC5384132
Pgltools GitHub

The Pgltools package was created by Bill Greenwald.

SCIMITAR: Single Cell Inference of MorphIng Trajectories and their Associated Regulation

The SCIMITAR package contains a number of tools to help scientists analyze cell trajectory maps based on single cell sequencing data.
Cordero P, Stuart JM. Tracing co-regulatory network dynamics in noisy, single-cell transcriptome trajectories . Pac Symp Biocomput. 2016;22:576-587. PMID: 27897008; PMC: PMC5203771
SCIMITAR GitHub

SCIMITAR was created Pablo Cordero.

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Tag Storm: Metadata made simple

The tag storm format offers an easy way to describe a hierarchical set of metadata for your data. The tag storm format is made up of a number of key/value pairs spread across stanzas at various indentation levels. Lower indentation levels inherit information from higher levels, so the most general metadata, e.g. lab or dataset names, are generally found at the highest level and more specifc metadata, e.g. sex or file name, are found at the lower level.

The Tag Storm GitHub page contains more information about the format as well as a suite of tools to work with and manipulate tag storm files.
Tag Storm GitHub

TagStorm format and utilities were developed by Jim Kent.

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RIGGLE: Regulator Inference by Graph-Guided LASSO Estimation

RIGGLE (Regulatory Inference by Graph-Guided LASSO Estimation) is a machine learning framework designed to discover the transcription factor regulators of a cell development trajectory by taking in expression data, known transcription factor targets, and a cell development graph.

This process produces predictions for the transcription factor's activities in each of the cell types represented in the graph based on the coordinated expression of its targets, while respecting the developmental relationships between the cells.

RIGGLE was created by Dan Carlin.

/images/SamplePsychicReportCard.png" alt="Report Card view, showing matches grouped by sample. Has CSV download.">

/images/SamplePsychicDetailedView.png" alt="By-sample view. Similar to Report Card but easier to navigate.">

/images/SamplePsychicPlot.png" alt="Experimental tSNE clustering of input samples.">

Sample Psychic: See how your cells compare

Sample Psychic can take your gene expression data and compare it to curated references. This comparison is used to produce a scorecard which shows how closely your data maps up to the curated cell types.

The Sample Psychic web application allows users to upload gene expression data and gain insights into those samples by applying suites of pre-trained concept classifiers to each sample. The resulting set of classification scores is presented as a report card that can be used to validate the identity of the samples and explore similarity between these samples and target concepts represented in in the Sample Psychic suite. For CIRM, classifiers were built for both fetal tissue clusters and hand labeled brain regions. One binary classifier is created for tissue type/cluster. A total of 96 fetal tissue clusters are represented in the Sample Psychic classifier compendium along with 30 classifiers representing hand-labeled brain regions. The pattern of individual classifier scores can give a picture of how user samples map to brain regions and to previously analyzed clusters.
Sample Psychic Website

Sample Psychic was created by James Durbin.

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MISCE: A Minimum Information About a Stem Cell Experiment

MISCE, or Minimum Information about a Stem Cell Expriment, is a spreadsheet that attempts to collect a rich set of useful information (metadata) about any experiment involving stem cells. The hope is that in using MISCE, the detailed metadata will make the experimental data useful to others attempting to use it in the future.

MISCE consists of a number of different modules with each module describing a different experimental process, e.g. celluar reprogramming or RNA sequencing, and all of the important information related to this process, e.g. "Biosample disease stage" or "Assay platform". Each module can be included or excluded based on the type of experiment being performed. For example, you might not include the "Assay_DNAMethyl" module if you are not performing DNA methylation assays as part of your experiment.
/MISCEv1.1.pdf">PDF of MISCE modules

MISCE was created by Sagar Jain and Richard Scheuermann; it is currently maintained by UCSC.