inst/markdown/methods/BCR.markdown

In CRI-iAtlas/iatlas-app: What the Package Does (One Line, Title Case)

Title: BCR Inference from Tumor RNA-Seq Data

Description: We used the VDJer tool (Mose et al., 2016), running on the ISB Cancer Genomics Cloud , to reconstruct the immunoglobulin heavy chain for all tumor samples. Paired end mRNASeq FASTQ data were aligned to human reference genome hg38 using STAR version 2.4.2a (Dobin et al., 2013). FASTQ files containing more than one read length were truncated to the shorter length. STAR was configured to emit unmapped reads within the output BAM files and samtools was used to generate BAM indices. An estimated insert size for each sample was calculated by using bwa version 0.7.12 (Li and Durbin, 2009) to align the first 1,000,000 read pairs of each sample to a reference human transcriptome and identifying the median bwa computed insert length. BCR heavy chain contigs and read alignments were generated using V'DJer version 0.12 run in standard mode. RSEM version 1.2.21 (Li and Dewey, 2011) was then used to quantify the BCR contigs. The RSEM reference was generated by running rsem-prepare-reference against the BCR contig fasta file and quantification was performed using rsem-calculate-expression. Expression counts were normalized to the total mRNASeq count for each sample. Isotypes for each contig were identified by mapping the trailing 48 bases to the hg38 reference and using the resultant alignment coordinates to call the isotype. IMGT/HighV-Quest (Lefranc et al., 2009) (http://www.imgt.org/IMGTindex/IMGTHighV-QUEST.php) was used to identify V and J gene segments, CDR3 sequence and V region identity for each contig. IgH diversity scores (Shannon Entropy, Evenness, and Richness) are provided in Table S1 of the manuscript and in this tool.

Reference Listing

Contributors: Joel Parker, Lisle E. Mose, Sheila M. Reynolds, Benjamin Vincent

CRI-iAtlas/iatlas-app documentation built on Feb. 7, 2025, 9:02 p.m.