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MultiGPS (version 0.74.0)
Conditions
Condition 0

What it does

MultiGPS is a framework for analyzing collections of multi-condition ChIP-seq datasets and characterizing differential binding events between conditions. MultiGPS encourages consistency in the reported binding event locations across conditions and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS performs significant EM optimization of binding events along the genome and across experimental conditions, and it integrates motif-finding via MEME. The tool loads all data into memory, so the potential exists for time and memory intensive analyses if running over many conditions or large datasets.


Options

  • Optional file containing reads from a control experiment - file containing reads from a control experiment
  • Fixed per-base limit - Fixed per-base limit (default: estimated from background model).
  • Poisson threshold for filtering per base - Look at neighboring positions to decide what the per-base limit should be.
  • Use non-unique reads - Use non-unique reads.
  • Fraction of the genome that is mappable for these experiments - Fraction of the genome that is mappable for these experiments
  • Turn off caching of the entire set of experiments? - Flag to turn off caching of the entire set of experiments (i.e. run slower with less memory).
  • Use signal vs control scaling? - Flag to turn off auto estimation of signal vs control scaling factor
  • Use the median signal/control ratio as the scaling factor? - Flag to use scaling by median ratio (default = scaling by NCIS).
  • Use scaling by regression on binned tag counts? - Flag to use scaling by regression (default = scaling by NCIS).
  • Estimate scaling factor by SES? - Specify whether to estimate scaling factor by SES.
  • Multiply control counts by total tag count ratio and then by this factor - Multiply control counts by total tag count ratio and then by this factor (default: NCIS).
  • Window size for estimating scaling ratios - Window size in base pairs for estimating scaling ratios
  • Plot diagnostic information for the chosen scaling method? - Flag to plot diagnostic information for the chosen scaling method.
  • Optional binding event read distribution file - Binding event read distribution file for initializing models. The true distribution of reads around binding events is estimated during MultiGPS training. A default initial distribution appropriate for ChIP-seq data is used if this option is not specified.
  • Maximum number of training rounds for updating binding event read distributions - Maximum number of training rounds for updating binding event read distributions.
  • Perform binding model updates? - Perform binding model updates?
  • Minimum number of events to support an update of the read distribution - Minimum number of events to support an update of the read distribution
  • Perform binding model smoothing? - Smooth with a cubic spline using a specified smoothing factor.
  • Spline smoothing parameter - Smoothing parameter for smoothing cubic spline.
  • Perform Gaussian model smoothing? - Select "Yes" to use Gaussian model smoothing using a specified smoothing factor if binding model smoothing is not performed.
  • Allow joint events in model updates? - Specify whether to allow joint events in model updates.
  • Keep binding model range fixed to inital size? - Flag to keep binding model range fixed to inital size (default: vary automatically)
  • Poisson log threshold for potential region scanning - Poisson log threshold for potential region scanning.
  • Alpha scaling factor - Alpha scaling factor. Increasing this parameter results in stricter binding event calls.
  • Impose this alpha - The alpha parameter is a sparse prior on binding events in the MultiGPS model. It can be interpreted as a minimum number of reads that each binding event must be responsible for in the model. Default: estimate alpha automatically.
  • Share component configs in the ML step? - Flag to not share component configs in the ML step
  • Optional file containing a set of regions to ignore during MultiGPS training - File containing a set of regions to ignore during MultiGPS training. It’s a good idea to exclude the mitochondrial genome and other ‘blacklisted’ regions that contain artifactual accumulations of reads in both ChIP-seq and control experiments. MultiGPS will waste time trying to model binding events in these regions, even though they will not typically appear significantly enriched over the control (and thus will not be reported to the user).
  • Perform inter-experiment positional prior? - Flag to turn off inter-experiment positional prior (default=on).
  • Probability that events are shared across conditions - Probability that events are shared across conditions.
  • Perform both motif-finding and motif priors? - Flag to turn off motif-finding and motif priors.
  • Perform motif-finding only? - Flag to turn off motif priors only.
  • Number of motifs MEME should find for each condition - Number of motifs MEME should find for each condition.
  • Minimum motif width for MEME - minw arg for MEME.
  • Maximum motif width for MEME - maxw arg for MEME.
  • Minimum Q-value (corrected p-value) of reported binding events - Minimum Q-value (corrected p-value) of reported binding events.
  • Minimum event fold-change vs scaled control - Minimum event fold-change vs scaled control.
  • Run differential enrichment tests? - Choose whether to run differential enrichment tests.
  • EdgeR over-dispersion parameter value - EdgeR over-dispersion parameter value.
  • Minimum p-value for reporting differential enrichment - Minimum p-value for reporting differential enrichment.