English to Russian Science Biology (-tech,-chem,micro-) секвенирование

For TCR analysis, we developed a new bioinformatic pipeline rpsTCR for reconstructing and extracting TCR sequences, especially TCR-CDR3 sequences from random priming short RNA sequencing reads. The rpsTCR took paired- and single-end short reads and maps these reads to mouse or human genomes and transcriptomes, but not TCR gene loci and transcripts using TopHat (Bioinformatics 25, 1105–1111 (2009)) with default parameters. Mapped reads were discarded and unmapped reads are recycled for extraction of TCR sequences. Low quality nucleotides in the unmapped reads were trimmed. Then reads with length less than 35bp were filtered out using HTQC toolkit (Bioinformatics 14, 33 (2013). QC passed short reads was assembled into longer reads using iSSAKE (Bioinformatics 25, 458–464 (2009)) default setting. TCRklass (J Immunol 194, 446–454 (2015)) was used to identify CDR3 sequences with Scr (conserved residue support score) ***set from default 1.7 to 2***. A targeted TCR-seq data from a healthy human PBMC samples was used as a positive control to evaluate whether the extra steps introduced to the pipeline resulted in higher false positive or false negative rates comparing to TCRklass alone.