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Stat 18 0 – Git Integration With Finder User

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Integration

950 8 8 silver badges 18 18 bronze badges. It is able to compute stats for a project (a group of git repositories) as well as for a contributor and a group of contributors. It provides a REST interface and a web UI. The web UI provides various information like, for a given contributor. User contributions licensed under cc by-sa. Give the output in the long-format. This is the default.-v -verbose. In addition to the names of files that have been changed, also show the textual changes that are staged to be committed (i.e., like the output of git diff -cached).If -v is specified twice, then also show the changes in the working tree that have not yet been staged (i.e., like the output of git diff).

This is the page of the underlying data and code for the analysis of the paper above, which has been published in Nature Methods in 2008. While the paper focuses on mouse tissues, we have since used the same code in C elegans and human cell lines with great success.

If using Bowtie 0.10.X, please make sure to use the new '--strata' flag in order to handle multireads correctly. Note that ERANGE is not compatible with bowtie 0.9.9.X.

ERANGE Development Edition

ERANGE is now available through Git. Future releases starting with ERANGE 4.0 will be available through a git repository. Development snapshots will be uploaded periodically for any interested parties. Available right now is a development alpha of ERANGE 4.0. Woldlab Gitweb portal

Developers wishing to create a clone of the repository can do so using:

git clone git://woldlab.caltech.edu/erange.git

Experimental BAM support

Stat 18 0 – Git Integration With Finder User Manual

A development version of ERANGE is available from the Git repository. This version includes a full rewrite of ReadDataset.py to use BAM files instead of the prior rds files. This build is still in testing, but should now be stable enough for limited use.

Important: Discontinue use of ERANGE version 3.2.1

Recently, an error in version 3.2.1 of Erange has emerged that will result in too many peaks being returned by findall.py and a reported FDR that is too high. Additionally gene counts will be returned as zero although rpkm values will be correct.

It is recommended that ERANGE 4.0a be downloaded from the above repository and used. This version has been tested with several of our datasets and the results agree with the prior (v3.2) release.

ERANGE 4.0a

New Features and Functions

Erange supports configuration files

  • The files erange.config in the current working directory or ~/.erange.config will be read by most erange scripts. These files should now be used instead of environmental variables to set the root directory and temp directories for cistematic. Command line options can also be set in config files for most erange scripts.

Cistematic integration

  • Cistematic will now be developed and released in concert with erange.

Erange supports optparse

  • Command line processing is now carried out by using optparse. This will require all long command line arguments to use a double dash (--) instead of the current single dash (-).

Improved package topology

  • End user software built on top of erange will now find it easier to import erange either entirely or as submodules.

Untitled goose game 1 0 7 torrent. The following READMEs constitute the bulk of the documentation for ERANGE:

  • A guide to building RDS files: README.build-rds

  • A guide to using ERANGE for ChIP-seq: README.chip-seq

  • A guide to using ERANGE for (expressed) SNPs: README.rna-esnp

  • https://jahiq.over-blog.com/2020/12/roblox-for-mac-os-x-10-6-8.html. A guide to using ERANGE for RNA-seq: README.rna-seq

  • A list of steps describing the standard RNA-seq pipeline: RNA-seq.analysisSteps.txt

Stat 18 0 – Git Integration With Finder Username

You are highly encouraged to use the following pipeline scripts rather than the individual commands for RNA-seq:

  • unpaired reads: runStandardAnalysis.sh
  • unpaired reads, stranded: runStrandedAnalysis.sh
  • paired reads (assumes on network partition): runRNAPairedAnalysis.sh
  • expressed SNP analysis: runSNPAnalysis.sh

Please note that ERANGE3.X is a major departure from the bed-based formats used in ERANGE2.0 and requires re-importing read mappings into sqlite based read datasets (RDS). However, we suggest that you run v3.X instead of v2.X for production purposes.

Interim Erange3.3 release

An interim build of Erange is available that includes support for analysis using self organizing maps. This will be incorporated into Erange4.0 shortly, but is being made available early as an interim release. ERANGE3.3.tgz To use this you will also need an updated version of Cistematic's analyzego.py which should replace the version located in your $CISTEMATIC_ROOT/cistematic/stat/ in order to support the bonferroni map correction.

Dual-use E-RANGE

Stat 18 0 – Git Integration With Finder User Interface

E-RANGE is our Python package for doing RNA-seq and ChIP-seq (hence the 'dual-use'), and is a descendant of the ChIPSeq mini peak finder (Johnson, 2007).

To use it for RNA-seq, first go through the RNA-seq README, then read the file analysisSteps.txt and take a look at the pipeline shell script runStandardAnalysis.sh.

Note that E-RANGE assumes the following requirements: Python 2.5, Linux / Mac OS X (preferably with the Python Psyco compiler), and Cistematic 2.0 (all scripts with a command line genome specification rely on Cistematic!), which you can get here.

If you want to rerun our entire analysis starting with either the raw data (eland files) or the bed files, you will need the following files:

  • ERANGE2.tgz (the code)

  • mm9splices_spikes.tgz (the files for building the exapnded genomes and remapping splices)

  • RNAFAR.tgz (the consolidated RNAFAR analysis, includes repeat library from UCSC - large!)

To use it for ChIP-seq follow the instructions in README.chip-seq to create an RDS file and then run the peakfinder script findall.py.

The Mouse Reference data

Briefly, each tissue has two replicates, the second of which was done with spike-ins, as described in the paper. For each replicate we provide:
Infinite jump for roblox mac 2018.

  • Normalized wigglegrams of the unique reads to display them on UCSC (mm9)
  • Bed files of all of the reads (uniques, splices, multireads, spikes) - note that only the splice bed files are small enough for loading onto UCSC
  • RPKM counts for each of the major steps of E-RANGE
  • ELAND results files run with the --multi option on the expanded genomes for those who want to look at the raw data (these files are *huge* - up to 1GB)
  • bigBed / bigWig files for usage with the UCSC genome browser

Tissue Table

Spike-Ins?Tissuewigbeds.tgzrpkms.tgzcomb.eland2.gzbigbed.tgz
No Spike-InBrainmm9Brainmm9Brain1mm9Brain1mm9Brain1mm9Brain1
Livermm9Livermm9Liver1mm9Liver1mm9Liver1mm9Liver1
Musclemm9Musclemm9Muscle1mm9Muscle1mm9Muscle1mm9Muscle1
Spike-InBrainmm9Brain2mm9Brain2mm9Brain2mm9Brain2mm9Brain2
Livermm9Liver2mm9Liver2mm9Liver2mm9Liver2mm9Liver2
Musclemm9Muscle2mm9Muscle2mm9Muscle2mm9Muscle2mm9Muscle2

Help

For assistance with Erange please contact Sean Upchurch (sau AT caltech.edu) Airradar 5 2 5.

Stat 18 0 – Git Integration With Finder User Guide

Last Modified: 7 Jun 2011 by Sean Upchurch Mocks 2 6 8 – create mockups of ios applications.





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