ISMARA - Integrated System for Motif Activity Response Analysis

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Dear users, we believe that in current situation when you have to work from home the ismara uploader might be very usefull tool. You can run it from command line on remote machine which is storing your data. This script supports all features of web-interface "Standard mode". If you have question or need assistance with running the script please do not hesitate to contact us.

Please provide email address, choose appropriate options, add files and click "Start upload" button.

Important! If you submit FASTQ files, please take in account that paired end reads should be submitted as two files with suffix "_R1" for the first end and "_R2" for the second end. Example: "sample1_R1.fastq.gz". "sample1_R2.fastq.gz". If your data is a single end then please avoid such suffixes ("_R1" and "_R2") in the file names.

Important! If you want submit FASTA files and your reads are shorther than 30 nucleotides then please contact us!

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For Expert users only!


ISMARA - The Integrated System for Motif Actitivity Response Analysis is an online tool that models genome-wide expression or ChIP-seq data, in terms of computationally predicted regulatory sites for transcription factors (TFs) and micro-RNAs (miRNAs).

The only input required for running ISMARA is either expression data (microarray CEL files or RNA-seq FASTQ and BED/BAM/SAM alignment files), or ChIP-seq data (FASTQ and BED/BAM/SAM alignment files), from a set of biological samples.

Using the given gene expression or chromatin state data across a set of samples, ISMARA identifies the key transcription factors and miRNAs driving the observed expression/chromatin state changes, and makes detailed predictions regarding their regulatory roles. Results include, for each regulatory motif, inferred activities across the input samples, predicted genome-wide targets, enriched pathways and functional classes of genes, and direct interactions between regulators. All results are presented within interactive and easily navigable HTML pages. The full results are also available for download.

More extensive documentation and sample input data are provided under the "Usage" link. Please also note ISMARA's "Terms of use"

Video tutorial:

Citation:

ISMARA: Automated modeling of genomic signals as a democracy of regulatory motifs
Piotr J. Balwierz, Mikhail Pachkov, Phil Arnold, Andreas J. Gruber, Mihaela Zavolan & Erik van Nimwegen Genome Research 2014

Intro

The only input required to run ISMARA is either a set of microarray CEL files (gene expression data) or a set of FASTQ files or BED/BAM/SAM alignment files (RNA-seq or ChIP-seq data) that contain the genomic mappings of the sequencing reads. Example input files are presented in "Example results" section. ISMARA normalizes all input data, and then uses them to calculate a quantitative `signal' associated with each promoter in the genome. ISMARA then models the promoter signals across the samples in terms of computationally predicted transcription factor binding sites in the neighborhood of the promoter (and, when analyzing gene expression data, also miRNA binding sites in the 3' UTRs of associated transcripts). As a result, ISMARA predicts the genome-wide regulatory interactions that explain the provided input data. These results include quantification of the importance of each regulator in explaining the input data, the activity of each regulator across the input samples, genome-wide targets of each regulator, direct interactions between regulators, and so on. A more extensive description of the results is provided here.

How to run ISMARA

Please submit the input files (CEL, BED, BAM, SAM, FASTQ) to the form above. Files can be submitted one by one or compressed into an archive (zip, tar.gz). Please specify the data type and, for RNA-seq or ChIP-seq data, please specify the genome assembly used for the mapped reads. We advice all users to provide an email address. A notification email will be send when ISMARA has finished analyzing the data, and this email also contains the URL of the results. After this, press the "Start upload" button. You will then be redirected to a page which shows the current status of your job. If you chose not to provide an email address, please make sure to bookmark or save the URL of this page!

ISMARA accepts different file formats. CEL files for microarray data and BED/BAM/SAM files for RNA-Seq and Chip-Seq data, which should contain the genomic mappings of the sequencing reads (see the sample data below). If you have more than 5 files, it is most practical to put all files into archive (zip, tar.gz, tar.bz2) and submit this archive to ISMARA. Note, the archive should contain just CEL/BED/BAM/SAM, i.e. files no folders or subfolders.

An "Expert" mode is available for experienced users that want to run ISMARA with individually defined sets of genomic regions and their own regulatory site predictions. An explanation is available here (Epi-MARA).

Supported affymetrix chips

Currently nine human and eleven mouse Affymetrix Gene Chips™ are supported. In addition, two Saccharomyces cerevisiae chips are supported.

Human chips:

  • HG-U133A
  • HG-U133B
  • HG-U133+2
  • HG-U133A_2
  • HuGene-1_0-st-v1
  • HuGene-1_1-st-v1
  • HuGene-2_0-st
  • HuGene-2_1-st
  • HT_HG-U133A
  • HT_HG-U133B
  • HT_HG-U133_Plus_PM
  • PrimeView
  • HG_U95Av2
  • Clariom_D_Human

Mouse chips:

  • MOE430A
  • MOE430B
  • Mouse430_2
  • Mouse430A_2
  • MoGene-1_0-st-v1
  • MoGene-1_1-st-v1
  • MoGene-2_0-st
  • HT_MG-430A
  • HT_MG-430B
  • MG_U74Av2
  • MG_U74Bv2
  • MG_U74Cv2
  • Clariom_S_Mouse

Yeast chips:

  • YG_S98
  • Yeast_2

E.coli chips:

  • E_coli_2

Rat chips:

  • RaGene-1_0-st-v1
  • RaGene-2_0-st
  • RaGene-2_1-st
  • RAE230A
  • RAE230B
  • RG_U34A
  • RG_U34B
  • RG_U34C
  • Rat230_2

ISMARA results

A description of the results that ISMARA provides is given here.

How to upload data:

There are a few posibilities to upload your data to the iSMARA server.

  • Use web-interface. For that you need to click "Add files" button and select one or more files to add for upload. You can click this button multiple times. Once all your files are added check that appropriate optios are set correctly and click "Start upload" button.
  • Use ISMARA client. This is a standalone application which can be installed on a user's computer (Linux/OSX) in order to locally pre-process data and submit it to the server. The pre-processed data is significantly smaller in size and can be uploaded in reasonable time even with slow Internet connection speed. You can find more in formation and instructions here.
  • Use ISMARA uploader. This is a python script which uploads your files to the server in headless mode and starts the analysis. You do not need browser or graphical user interface in order to use it. More information and download is here

If you experience any problems with the methods above please do not hesitate to contact us! There are other posibilities how you can share your data with us and we will find the most appropriate way for you.

Example results:

Epi-Mara results:

Arnold, Schöler et al. "Modeling of epigenome dynamics during differentiation reveals REST as a mediator of Polycomb targeting in neuronal progenitors."

Dynamics of the Mouse Liver

Transcriptional response to SARS-CoV-2 infection (GSE147507)

This analysis was conducted by Dr. Andreas Gruber for covid-19-bh20 biohackathon

The developers of ISMARA give permission to you and your institution to use the ISMARA webserver for internal, research purposes, on the following conditions:

  1. The ISMARA webserver will be used by you and/or your institution solely for non-commercial purposes, except with express permission from the authors.
  2. You may provide us with feedback on the use of the ISMARA webserver in your research, and we are permitted to use any information you provide in making changes to ISMARA.
  3. Any risk associated with using the ISMARA webserver is with you and your institution.
  4. The ISMARA webserver should be cited in any publication(s) reporting on data obtained by using it as:
    ISMARA: Automated modeling of genomic signals as a democracy of regulatory motifs Piotr J. Balwierz, Mikhail Pachkov, Phil Arnold, Andreas J. Gruber, Mihaela Zavolan & Erik van Nimwegen Genome Research 2014

Commercial users should contact us for licensing arrangements.