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Sadasivam, S.

Publications and source records attributed to Sadasivam, S..

2 recordsLinked to original sources

Taxonomic classification cost tracks neither sequencing depth nor community richness at single-sample scale: a measured resource protocol for 16S rRNA amplicon pipelines

Marker-gene amplicon workflows are routinely run on shared compute, yet the cores, memory and wall time they are given are chosen by convention and not by measurement. We present a protocol for measuring them, applied to the two dominant stages of a QIIME 2 16S rRNA pipeline, DADA2 denoising and Naive Bayes taxonomic classification, across nine upper-respiratory samples from a paediatric otitis media cohort. The two stages do not consume the same input: denoising reads every sequence, classification only those surviving it. Subsampling one library across a 27-fold range of sequencing depth, denoising wall time rose 14.3-fold while classification changed by 1% and its peak memory not at all (3.11 GiB). Amplicon sequence variant (ASV) richness rose 2.8-fold over that range, so this is not richness saturating: the stage is dominated by a fixed per-invocation cost. Across a body-site gradient of 5 to 70 ASVs, denoising followed read count (exponent 0.75) while classification followed neither: a 5-ASV effusion and a 70-ASV adenoid community cost 40.81 s and 40.79 s. One ASV took 36.20 s and 218 took 37.27 s, 97% fixed cost. Thread-level parallelism offered little benefit. Denoising peaked at 1.18x near 8 threads and then declined; classification was slower at every setting above one job, consuming 10.5 times the CPU at 40. Representative sequences and their taxonomic assignments were identical at 1, 4 and 40 threads, so a reduced allocation changes what the analysis costs, not what it reports. Extending the query set to 10,000 sequences located two distinct boundaries: eight jobs first beat one at roughly 5,000 queries, and fitted fixed and per-query costs become equal at 15,248. Both lie roughly two orders of magnitude above the richest single sample measured. Practically: size denoising by read count, calibrate classification once against the reference in use, request one job for classification below a few thousand sequences, and take throughput from sample-level parallelism. Protocol, data and analysis code are released with the pipeline.

bioinformatics↗

In Silico Analysis Reveals a Shared Immune Signature in CASP8-Mutated Carcinomas with Varying Correlations to Prognosis.

BackgroundSequencing studies across multiple cancers continue to reveal the spectrum of mutations and genes involved in the pathobiology of these cancers. Exome sequencing of oral cancers, a subset of Head and Neck Squamous cell Carcinomas (HNSCs) common among tobacco-chewing populations, revealed that ~34% of the affected patients harbor mutations in the CASP8 gene. Uterine Corpus Endometrial Carcinoma (UCEC) is another cancer type where about 10% cases harbor CASP8 mutations. Caspase-8, the protease encoded by CASP8 gene, plays a dual role in programmed cell death, which in turn has an important role in tumor cell death and drug resistance. CASP8 is a protease required for the extrinsic pathway of apoptosis and is also a negative regulator of necroptosis. Using bioinformatics approaches to mine data in The Cancer Genome Atlas, we compared the molecular features and survival of these carcinomas with and without CASP8 mutations.\n\nResultsOur in silico analyses showed that HNSCs with CASP8 mutations displayed a prominent signature of genes involved in immune response and inflammation, and were rich in immune cell infiltrates. However, in contrast to Human Papilloma Virus-positive HNSCs, a subtype that exhibits high immune cell infiltration and better overall survival, HNSC patients with mutant-CASP8 tumors did not display any survival advantage. A similar bioinformatic analyses in UCECs revealed that while UCECs with CASP8 mutations also displayed an immune signature, they had better overall survival, in contrast to the HNSC scenario. On further examination, we found that there was significant up-regulation of neutrophils as well as the cytokine, IL33 in mutant-CASP8 HNSCs, both of which were not observed in mutant-CASP8 UCECs.\n\nConclusionsThese results suggested that carcinomas with mutant CASP8 have broadly similar immune signatures albeit with different effects on survival. We hypothesize that subtle tissue-dependent differences could influence survival by modifying the micro-environment of mutant-CASP8 carcinomas. High neutrophil numbers, which is a well-known negative prognosticator in HNSCs, and/or high IL33 levels may be some of the factors affecting survival of mutant-CASP8 cases.

cancer biology↗