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## Iso-Seq analysis | ||
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Demultiplexed hifi reads (Q20, single-molecule resolution) from lima [https://github.com/pacificbiosciences/barcoding/ https://github.com/pacificbiosciences/barcoding/] were | ||
further processed using Isoseq3 (v3.2.2) [https://github.com/PacificBiosciences/IsoSeq] refinement and clustering steps to generate | ||
the HQ (Full-length high quality i.e., predicted accuracy ≥Q20) transcripts [Table 1]. | ||
Next, we mapped these transcripts against GRCh38 (v33 p13) [2] using Minimap2 long read alignment tools [1] | ||
(v2.24-r1122; commands: minimap2 -t 8 -ax splice:hq -uf --secondary=no -C5 -O6,24 -B4 GRCh38.v33p13.primary_assembly.fa sample.polished.hq.fastq.gz). | ||
The table 2 shows the basic statistics of the alignment of each sample [HG002: NA27730, NA24385 and NA26105]. | ||
Next, we performed cDNA_cupcake v28.0.0 [https://github.com/Magdoll/cDNA_Cupcake] workflow to collapse the redundant isoforms from bam, | ||
followed by filtering the low counts isoforms by 10 and filter away 5' degraded isoforms as they are not biologically significant. Next, sqanti3 v5.0 [3] tool was | ||
used to generate the final corrected fasta transcripts and gff [Table 3] along with the isoform classification reports. The external databases including reference data set of transcription start sites (refTSS), | ||
list of polyA motif, tappAS-annotation and Genecode GRCh38 annotation were utilized during the isoform classification by Sqanti3. Finally, IsoAnnotLite (v2.7.3) [https://isoannot.tappas.org/isoannot-lite/] | ||
analysis was performed to annotate the gtf file from sqanti3. | ||
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Table 1. Statistics of HQ fastq reads. | ||
Samples num_seqs min_len avg_len max_len N50 Q20(%) Q30(%) | ||
NA26105 (HG002.3) 205,590 51 3298.8 14887 3817 99.95 99.92 | ||
NA27730 (HG002.2) 205,884 52 3093.6 12524 3695 99.96 99.93 | ||
NA24385/HG002 (HG002.1) 411,349 50 2171.2 10767 2675 99.96 99.93 | ||
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Table 2. Statistics of isoforms mapped with Minimap2. | ||
Samples Total Reads AlnPerc (%) Mapped Reads Unmapped reads | ||
NA26105 MM2 99.04 203607 1983 | ||
NA27730 MM2 99.35 204553 1331 | ||
NA24385 MM2 99.65 409905 1444 | ||
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Table 3. Basic Statistics of transcripts discovered by Sqanti3 filtered. | ||
Sample # of Gene # of transcript # of exon | ||
NA26105 5433 7632 72940 | ||
NA27730 5459 7765 74906 | ||
NA24385/HG002 5656 9710 51196 | ||
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Reference: | ||
1. Heng Li, Minimap2: pairwise alignment for nucleotide sequences, Bioinformatics, Volume 34, Issue 18, September 2018, Pages 3094–3100, https://doi.org/10.1093/bioinformatics/bty191 | ||
2. Adam Frankish and others, GENCODE 2021, Nucleic Acids Research, Volume 49, Issue D1, 8 January 2021, Pages D916–D923, https://doi.org/10.1093/nar/gkaa1087 | ||
3. Pardo-Palacios FJ, Arzalluz-Luque A et al. SQANTI3: curation of long-read transcriptomes for accurate identification of known and novel isoforms. doi: 10.1101/2023.05.17.541248. PMID: 37398077; PMCID: PMC10312485. | ||
![image](https://github.com/collaborativebioinformatics/isocomp/assets/41694905/60b9790a-3caf-499c-b799-bcd819ec0e6c) |