Project description:Full-Length cDNA transcriptome (Iso-Seq) data sequenced on the PacBio Sequel system using 2.1 chemistry. Multiplexed cDNA library of 12 samples (3 tissues x 4 strains). Tissues: root, embryo, endosperm. Strains: B73, Ki11, B73xKi11, Ki11xB73.
Project description:BACKGROUND:PacBio sequencing is an incredibly valuable third-generation DNA sequencing method due to very long read lengths, ability to detect methylated bases, and its real-time sequencing methodology. Yet, hitherto no tool was available for analyzing the quality of, subsampling, and filtering PacBio data. RESULTS:Here we present SequelTools, a command-line program containing three tools: Quality Control, Read Subsampling, and Read Filtering. The Quality Control tool quickly processes PacBio Sequel raw sequence data from multiple SMRTcells producing multiple statistics and publication-quality plots describing the quality of the data including N50, read length and count statistics, PSR, and ZOR. The Read Subsampling tool allows the user to subsample reads by one or more of the following criteria: longest subreads per CLR or random CLR selection. The Read Filtering tool provides options for normalizing data by filtering out certain low-quality scraps reads and/or by minimum CLR length. SequelTools is implemented in bash, R, and Python using only standard libraries and packages and is platform independent. CONCLUSIONS:SequelTools is a program that provides the only free, fast, and easy-to-use quality control tool, and the only program providing this kind of read subsampling and read filtering for PacBio Sequel raw sequence data, and is available at https://github.com/ISUgenomics/SequelTools .
Project description:We used PacBio data to identify more reliable transcripts from hESC, based on which we can estimate gene/transcript abundance better from Illumina data. PacBio long reads and Illumina short reads were generated from the same hESC cell line H1. PacBio reads were error-corrected by Illumina reads to identify transcripts. rSeq is used to estimate gene/transcript abundance of the identified transcriptome.