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114 protocols using casava

1

Transcriptome Assembly and Analysis

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The raw reads were assessed using CASAVA (v1.8, Illumina Inc.) and filtered to produce clean reads. First, the adaptors were removed. Second, the reads with an N ratio of more than 10% were removed. Finally, low-quality reads (Qphred value of <20 and >50% bases) were trimmed, with a Qphred cut-off value of −10 log10(e). Short reads obtained by sequencing were assembled using Trinity software (Grabherr et al., 2011 (link)) and the unigenes used for subsequent analysis. TransDecoder was used to identify candidate coding regions based on the following criteria: (1) An ORF that meets the minimum limit length (200 bp) can be found in the transcript sequence. (2) The logarithm likelihood score was greater than 0. (3) The logarithm likelihood score of the first open reading frame (ORF) is the maximum compared with the other 5. (4) If the candidate ORF was completely involved in other ORFs, we only report the longest ORF.
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2

RNA-seq Analysis of Mouse Transcriptome

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cDNA libraries were sequenced on the Illumina HiSeq 2000 as 101-bp single-end reads. Base calling was performed using Illumina RTA (version 1.13.48), and conversion to FASTQ was performed using CASAVA (version 1.8.2, Illumina). Reads were then trimmed to 44 bases, discarding the first 4 bases and then keeping the next 44 bases. Trimmed reads were aligned to the mm9 reference genome using Bowtie software (version 1.0.0) allowing up to three mismatches and requiring best unique matches. Custom R scripts were used to count tags that aligned to the exons of University of California at Santa Cruz (UCSC) RefSeq gene models. DESeq2 software was used for differential gene expression analysis.
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3

RNA-seq of Sorted ILC2 and ILC3 Cells

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ILC2 and ILC3 were sort-purified from small intestine of Rorc(γt)-GfpTG mice or BMAL1fl/fl and BMAL1ΔRorc littermates. Sorted cells were used to prepare RNA-seq libraries by the Epigenomics Core at Weill Cornell Medicine using the Clontech SMARTer Ultra Low Input RNA Kit V4 (Clontech Laboratories). Sequencing was performed on an Illumina HiSeq 2500, yielding 50 bp single-end reads.
Raw sequencing reads were demultiplexed with Illumina CASAVA (v1.8.2). Adapters were trimmed from reads using FLEXBAR (v2.4) and reads were aligned to the NCBI GRCm38/mm10 mouse genome using the STAR aligner (v2.5.2b) with default settings. Reads per gene were counted using Rsubread. Genes with at least 50 or more counts in at least 2 samples were tested for differential expression. Differential expression was assessed using DESeq2 version 1.22.2 with default parameters and with a false discovery rate (FDR) of 0.1. Principal component analysis (PCA) was performed after applying the DESeq2 varianceStabilizingTransformation function, using the 500 genes with highest variance.
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4

Targeted Genomic Sequencing of Mimulus guttatus

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To carry out targeted genomic sequencing, we designed probes using the M. guttatus genome version 1.1 (www.phytozome.net, based on a North American accession of M. guttatus). We randomly chose coding genic and untranslated regions in a ratio of 3:1 for a total of 1198 regions of 450 bp each (540 kbp total) across the whole genome. For these target regions, we designed Agilent SureSelect RNA baits using the SureDesign software (Agilent Sure Select XT Enrichment Protocol version 1.6; Agilent Technologies, Stockport, Cheshire, UK). The final design yielded 20,385 probes with a total size of 488,076 bp. We extracted DNA from dried leaf tissue using DNeasy Plant Mini Kits (Qiagen, Crawley, West Sussex, UK) and used 1.5–7.9 μg of DNA for hybridization with the SureSelect RNA baits. The captured DNA was sequenced in a 100 bp pair‐end run in a MiSeq desktop sequencer (Illumina, Little Chesterford, Essex, UK) at the NERC Biomolecular Analysis Facility‐Edinburgh (Genepool, Edinburgh, UK). Fastq files were obtained using the Illumina pipeline CASAVA version 1.8.3.
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5

Whole Genome Sequencing of Common Bean

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DNA of the 17 common bean varieties was extracted from seeds and digested with dsDNA fragmentase (Linnarsson 2010 (link)). Index sequences 6 bp in length were ligated to the resulting fragments and 350–800 bp fragments were size selected on a 1.0% agarose gel, purified, and prepared for Illumina GAIIx sequencing (Illumina Inc, San Diego, CA). The Off-line Basecaller Software (v1.7; Illumina Inc) was used for base calling and CASAVA (v 1.7; Illumina Inc) was used for mapping the paired-end reads to the common bean 14× genome sequence assembly generated by the Joint Genome Institute and to identify SNPs. Parameters of a minimum of three reads at the SNP position and a SNP quality score >10 were used for SNP allele calling.
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6

Somatic Variant Identification Workflow

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Real-time analysis and base calling was performed using Ilumina’s software packages HSC2.0.2/RTA1.17.21.3 and raw reads were processed with Illumina CASAVA (v 1.8.2) to filter out low-quality reads. Variants present in the 1000 Genomes Project or gnomAD ≥ 0.01 were filtered out. Cut-off was set at alternative allele frequency > 10% and coverage 100. Sequence reads were aligned to the human reference genome (NCBI build 37) using BWA. As matched normal samples were not available, the following criteria were used to remove germline variants; > 1% frequency in the 1000 Genomes Project or gnomAD, variants found as germline in the 419-gene panel, variants found with VAF 0.4–0.6 or 0.8–1.0 in two samples from the same patient. All potential rare germline mutations are therefore not filtered out.
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7

Transcriptome Profiling of Gastric Cancer Tissue

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RNA of 32 GCT samples was sequenced on Illumina HiSeq2000 according to the manufacturer’s protocol (Illumina). 100-bp paired-end reads were assessed for quality and reads were mapped using CASAVA (Illumina). The generated FASTQ files were aligned by Bowtie261 (link) and TopHat262 (link). Cufflinks63 (link),64 (link) was used to assemble and estimate the relative abundances of transcripts at the gene and transcript level. DEFUSE35 (link) was used for fusion gene discovery.
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8

RNA-seq Data Processing and Assembly

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Raw data processing, base calling, and quality control were performed using RTA, OLB, and CASAVA (Illumina), according to the manufacturer’s pipeline. The output sequence quality was inspected using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/), and the reads were cleaned using cutadapt (version 1.8.1) [73 (link)] to trim low-quality ends (link)], yielding 49,239 contigs that clustered into 39,426 subcomponents (i.e., unigenes). The unigene sizes were 201 to 10,772 bp, with a mean length of 427 bp, N50 length of 1228 bp, and total combined length of 29,260,585 bp (Additional file 1: Table S1).
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9

RNA-Seq Analysis of Human Skin Tissues

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Total RNA was extracted from human skin tissues using TRIZOL Lysis Reagent (Life Technologies) and the RNeasy® kit (Qiagen Inc.) and was processed by the MUSC Genomics core for 1 × 50 cycles, using single-end RNA sequencing on an Illumina HiSeq2500. The RNA integrity was verified on an Agilent 2200 TapeStation (AgilentTechnologies, Palo Alto, CA, USA). A total of 100 ng of total RNA was used to prepare RNA-Seq libraries using the TruSeq RNA Sample Prep kit following the protocol described by the manufacturer (Illumina, San Diego, CA, USA). Sequencing was performed on an Illumina HiSeq2500. Samples were demultiplexed using CASAVA (Illumina).
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10

Genomic Integration Site Analysis

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Amplification of genomic DNA junctions was performed by linear amplification-mediated PCR, and bioinformatic analysis of integration sites was performed as described previously.10 (link)
To analyze the sequencing data, sample-specific barcoded sequencing reads were demultiplexed using CASAVA, an Illumina software package. The quality of sequencing runs of resulting fastq files was evaluated using FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc). Reads starting with the barcode 5′-GTATGTAAACTTCCGACTTCAACTG-3′ that follows the TA dinucleotide, which is characteristic of SB integration, were aligned against the latest version of mouse reference genome (GRCm38/mm10 [December 2011]) using Bowtie2.49 (link) Only reads that mapped exactly to a unique position in the reference genome were kept for further analysis. To analyze the distribution integrations, annotations of exons, and coding DNA sequence (CDS) of the corresponding reference, genome were downloaded and the percentage of integration sites overlapping with the given genomic coordinates was analyzed using BEDTools.50 (link) We have indexed and created 142 normal, shuffled, and randomized windows of mouse genome and counted the number of integrations for each window and plotted the density.
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