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lncRNApipe: Reference annotation based automated pipeline to identify non-coding RNAs.

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@biocoder biocoder released this 04 Oct 21:15
· 3 commits to master since this release

lncRNApipe is a reference annotation based automated pipeline to identify non-coding RNAs, both known and novel from RNA-Seq reads. It takes FASTQ / FASTA reads as input, trims reads, assembles transcripts, and identifies any possible known and novel ncRNAs, categorizes them into 5 catgories: Long intergenic lncRNAs (LincRNAs), Intronic contained lncRNAs (Incs), Partially overlapping lncRNAs (Poncs), Completely overlapping lncRNAs (Concs) and Exonic overlaps (LncRNAs with sense or antisense overlap with reference exon) and annotates the novel ncRNAs, where possible.

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Release 1.3.1

  • Bug fix: gen_infernalHits.pl was generating cmscan hits GTF file for the model search in a spliced out exonic sequence and subsequently producing incorrect chromosome coordinates. This release fixes that issue.

Release 1.3.0

  • Updated lncRNApipe core to work with CPC 2.0. Reinstall lncRNApipe by typing lncRNApipe --setup at the location where you previously installed the pipeline and then do a test run as directed in README.pod to make sure everything works.

Release 1.2.3

  • Bug fix: Fixed issue #9.
  • Updated sand-boxed cuffcompare to v2.2.1 and sambamba to v0.6.6.

Release 1.2.2

  • Bug fix: 49ba266. Fixed a small bug with get_unique_features.pl, where non BED or GTF lines are now skipped.
  • Updated sand-boxed INFERNAL CM models to latest Rfam release.

Release 1.2.1

  • Added: ISSUE TEMPLATE and CODE OF CONDUCT
  • Bug fix: 9960977. Support for creating GTF records for Infernal hits spanning mulitple introns has been added. It is still EXPERIMENTAL.

Cite lncRNApipe:

Assessment of Histone Tail Modifications and Transcriptional Profiling During Colon Cancer Progression Reveals a Global Decrease in H3K4me3 Activity Karen Triff; Mathew W McLean; Kranti Kranti; Jiahui Pang; Evelyn Callaway; Beiyan Zhou; Ivan Ivanov; Robert S. Chapkin Molecular Basis of Disease 2017

Cheers,

BioCoder