[TM4-Announce] MeV v4.7.3 released

Fri Jul 15 13:08:23 MDT 2011

The MeV team is proud to announce MeV v4.7.3. This version, and the 
closely-related v4.7.2, include many small improvements and bug fixes. 
We recommend all MeV users upgrade to v4.7.3.

      MeV v4.7.3

/July 15, 2011/

*New Features*

* The EASE module has been re-enabled for use with RNA-Seq data.

      MeV v4.7.2

/July 11, 2011/

      New Features

* Custom annotation loading for RNA-Seq data.

      Bugfixes

* Restored the MeV.exe icon.

* Fixed the broken link to HBGB Genome Browser.

* Fixed a Mac-specific bug in the GOSeq module that prevents the module 
from running.

* Fixed bug for zero-variance genes using Pearson Correlation.

* Enabled top-panel resizing.

      Other Changes

* The GOSeq Module has been moved to the Meta Analysis toolbar.

      MeV v4.7.1

/May 19, 2011/

      Bugfixes

* A few new validation checks to RNA-Seq file loader

* Fixed a bug that showed up if the input RANseq file was incomplete.

      MeV v4.7

/May 16, 2011/

      New RNA-Seq Features

MeV is now capable of loading and analyzing RNA-Seq data.

New File Loader
MeV can now load summarized RNASeq data from a simple, tab-delimited 
file format. This format is fully described in the appendix of the MeV 
user manual. The loader can load count data, RPKM or FPKM, or 
combinations of the two data types.

GOSeq: GO term enrichment detection for RNASeq data (Young, et al, 2010).
GOSEQ is a technique for identifying differentially expressed sets of 
genes, such as GO terms while accounting for the biases inherent to 
sequencing data.

EdgeR: differential expression analysis of digital gene expression data  
(Robinson et al., 2010).
EdgeR is a Bioconductor software package for examining differential 
expression of replicated count data. An over-dispersed Poisson model is 
used to account for both biological and technical variability. Empirical 
Bayes methods are used to moderate the degree of over-dispersion across 
transcripts, improving the reliability of inference. The methodology can 
be used even with the most minimal levels of replication, provided at 
least one phenotype or experimental condition is replicated.

DESeq: Digital gene expresion analysis based on the negative binomial 
distribution  (Anders and Huber, 2010).
The BioC package DESeq provides a powerful tool to estimate the variance 
in count data and test for differential expression. It can estimate 
variance-mean dependence in count data from high-throughput sequencing 
assays and test for differential expression based on a model using the 
negative binomial distribution.

DGESeq: An R package to identify differentially expressed genes from 
RNA-Seq data  (L. Wang et al., 2010).
Identify differentially expressed genes from RNA-seq data. RNA 
sequencing is modeled as a random sampling process, in which each read 
is sampled independently and uniformly from every possible nucleotide in 
the sample. Under this assumption the number of reads coming from a gene 
(or transcript isoform) follows a binomial distribution (and could be 
approximated by a Poisson distribution). Based on this statistical 
model, Fisher's exact test, likelihood ratio test and 2 other methods 
were proposed to identify differentially expressed genes.

      Other New Features

Expression Graphs
In the Sample Cluster Manager, a new graph view is available, called 
Expression Graphs. This option allows the creation of boxplots and bar 
charts of individual genes or groups of genes, compared across sample 
groups.

Major updates to GSEA user interface
Simpler, easier UI allows more intuitive use of the Gene Set Enrichment 
Module.  Several calculation improvements and algorithm fixes have been 
applied to the newest release.

Import File feature added to List Import option in Cluster Manager
Clusters can now be created by loading a file containing a gene list.

New MeV User Manual
We have updated the MEV manual to a web-based format. Now, the help 
buttons within MeV link directly to a local copy of the user manual. 
Full information about the linked module is available immediately.

R 2.11
All R-dependent MeV functions call R version 2.11 by default.

R package auto-download
MeV now automatically downloads R support packages after installation. 
The packages no longer have to be included in the initial download.

"Set as Data Source" Option Removed
We have removed a feature of the MeV result tree. Previously, the 
right-click context menu for cluster nodes in the result tree contained 
an option called "Set as Data Source". Choosing this option would cause 
the genes in the selected cluster to be treated as the entire MeV source 
dataset. All subsequent modules and filters run in MeV would be applied 
only to that subset of the data. We have removed this option because it 
was redundant and not particularly stable. Users who want to work with 
only a subset of their data have two options, both of which are more 
robust and fit better with the MeV data metaphor.
Option 1. Launch as new Viewer:
Create a gene or sample cluster from the result node of interest, by 
right-clicking on the viewer window and choosing Store Entire Cluster.
Go to the appropriate Cluster Manager (Gene Cluster Manager or Sample 
Cluster Manager, in the result tree under the node Cluster Manager).
Right-click on the cluster you just created, and choose Open/Launch -> 
Launch MeV Session. This will create a new Multiple Array Viewer 
containing only the data from the selected cluster. All analyses 
executed in this MAV will only apply to the selected data.

Option 2. Select data cluster during module execution
Create a gene or sample cluster from the result node of interest, by 
right-clicking on the viewer window and choosing Store Entire Cluster.
In the module execution dialog, select that cluster from the cluster 
selection panel. The module will apply its analysis to only the 
genes/samples in that cluster.

      Bugfixes

* The viewers for single-color Affymetrix data now handle the heatmap 
display of zero values properly
* GSEA bugfixes
* Missing HCL header bug resolved.
* NMF Plotviewer error fixed.
* The GSEA p-value graph viewer now saves and restores state correctly.
* The Windows version of MeV v4.6.2 shipped without a MeV executable. 
While the program was still usable with the tmev.bat file, it was 
annoying the MeV.exe file has been restored.
* Agilent file loader fixed for loading of 1-color data.
* Agilent file loader fixed for loading of multiple samples simultaneously.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://tm4.org/pipermail/tm4-announce_tm4.org/attachments/20110715/465e0d87/attachment.html>