Release notes - October 30, 2023

Recently published apps

The pRESTO 0.7.1. toolkit is the latest new toolkit addition in our Public Apps gallery. It includes the following apps: 

  • ParseLog - Parses pRESTO log records and outputs values in TAB-separated tables. 
  • BuildConsensus - Builds consensus sequences. 
  • ClusterSets - Clusters sequences into groups. 
  • CollapseSeq- Removes duplicates sequences from input FASTA/FASTQ files. 
  • PairSeq - Sorts and matches sequences across input files. 
  • ConvertHeaders - Converts sequence headers to pRESTO format. 
  • AlignSets - Aligns sequences using different methods. 
  • FilterSeq - Filters input sequences. 
  • ParseHeaders - Manipulates sequence headers. 
  • SplitSeq - Splits and samples sequence files. 
  • UnifyHeaders - Reassigns or deletes sequence header fields. 
  • AssemblePairs - Assembles paired-end reads to a single sequence. 
  • MaskPrimers - Removes primers and annotates sequences with primers and barcodes. 
  • EstimateError - Estimates annotation set error rates.  

We also published the following new tools: 

  • ComBat-seq (sva 3.35.2), an R tool used for batch effect adjustment in bulk RNA-seq data. Some additional improvements to the tool wrapper were developed, like removing more than one batch by dataset and adapting outputs to be compatible with downstream analyses (DeSeq). 
  • GffRead (0.12.7) GFF/GTF utility tool providing format conversions, filtering, FASTA sequence extraction, and more. 

Recently updated apps

We published the following updates in our Public Apps gallery: 

  • RNA-seq alignment - STAR (2.7.10a), a workflow that performs the first step of RNA-seq analysis - alignment of the reads to a reference genome. It is used to generate aligned BAM files (in genome and transcriptome coordinates) from RNA-seq data, which can later be used in further RNA studies, like gene expression analysis. 
  • Trim Galore! (0.6.10) is a wrapper around adapter trimming and quality control tools Cutadapt and FastQC with extra functionality for RRBS data.