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List of intron retention associated variants from Sequence Read Archive

List of intron retention associated variants via <a href="https://github.com/friend1ws/iravnet">IRAVNet</a> applied to 219,615 transcriptome sequence data from Sequence Read Archive

opencc-by-4.0Feb 2022View details →

Data and scripts for the manuscript of svaRetro and svaNUMT: modular packages for annotating retrotransposed transcripts and nuclear integration of mitochondrial DNA in genome sequencing data

This upload include data and scripts supporting the results described in the manuscript of svaRetro and svaNUMT: modular packages for annotating retrotransposed transcripts and nuclear integration of mitochondrial DNA in genome sequencing data. Detailed description of the contents can be found in README.txt.

Genome-resolved metagenomics using short-, long-read and metaHiC sequencing

Reference-quality metagenome-assembled genomes (MAGs) are the key to exploring microbial compositions and microbe-phenotype associations. They can be recovered by different sequencing technologies and computational tools, which need an unbiased and comprehensive assessment to identify best practices. This work systematically evaluates 40 distinct strategies to recover high-quality MAGs generated by eight assemblers, eight metagenomics binners, and four sequencing technologies, including short-, long-read and metaHiC sequencing. We notice that the hybrid assemblies of short- and long-reads outperform either short- or long-read assemblies and generate more contigs with high contiguity. When the hybrid assemblies are combined with metaHiC-based binning (Hybrid-HiC), more high-quality MAGs with higher taxonomic diversity are recovered, and more tRNA and rRNA genes, phages, plasmids and antibiotic resistance genes are identified in the mock, simulated and real datasets.

opencc-zeroAug 2022View details →

Ultra-short response-guided Hepatitis C treatment with sofosbuvir and daclatasvir: the SEARCH study HCV sequence data

Background WHO has called for research into predictive factors for selecting persons who could be successfully treated with shorter durations of antiviral therapy for Hepatitis C. We evaluated early virological response as a means of shortening treatment and explored host, viral and pharmacokinetic contributors to treatment outcome. Methods Duration of sofosbuvir and daclatasvir (SOF/DCV) was determined according to day 2 (D2) virologic response for HCV genotype (gt) 1- or 6-infected adults in Vietnam with mild liver disease. Participants received 4 or 8 weeks of treatment according to whether D2 HCV RNA was above or below 500 IU/ml (standard duration is 12 weeks). Primary endpoint was sustained virological response (SVR12). Those failing therapy were retreated with 12 weeks SOF/DCV. Host IFNL4 genotype and viral sequencing was performed at baseline, with repeat viral sequencing if virological rebound was observed. Levels of SOF, its inactive metabolite GS-331007 and DCV were measured on day 0 and 28. Findings Of 52 adults enrolled, 34 received 4 weeks SOF/DCV, 17 got 8 weeks and one withdrew. SVR12 was achieved in 21/34 (62%) treated for 4 weeks, and 17/17 (100%) treated for 8 weeks. Overall, 38/51 (75%) were cured with first-line treatment (mean duration of 37 days). Despite a high prevalence of putative NS5A-inhibitor resistance-associated substitutions (RAS), all first-line treatment failures were cured after retreatment (13/13). We found no evidence treatment failure was associated with host IFNL4 genotype, viral subtype, baseline RAS or DCV levels. SOF metabolite levels were higher in those failing 4-week therapy. Interpretation Shortened SOF/DCV therapy with retreatment if needed, reduces DAA use while maintaining high cure rates. D2 virologic response alone does not adequately predict SVR12 with 4 weeks of treatment.

Simulated data from: Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2

Long-read sequencing technologies have improved significantly since their emergence. Their read lengths, potentially spanning entire transcripts, is advantageous for reconstructing transcriptomes. Existing long-read transcriptome assembly methods are primarily reference-based and to date, there is little focus on reference-free transcriptome assembly. We introduce RNA-Bloom2, a reference-free assembly method for long-read transcriptome sequencing data. RNA-Bloom2 is available on GitHub at: <a href="https://github.com/bcgsc/RNA-Bloom">https://github.com/bcgsc/RNA-Bloom</a>. We benchmarked the assembly quality and the computational performance of RNA-Bloom2 on simulated data. We prepared two mouse simulated datasets with Trans-NanoSim for the cDNA and dRNA sequencing protocols model on experimental ONT data. The datasets were simulated based on the mouse ENSEMBL annotation for GRCm39. To investigate the effect of sequencing depth, we subsampled each dataset to 2, 10, and 18 million reads, resulting in a total of six sets of reads for our benchmarking experiments. Using the simulated data, we showed that the transcriptome assembly quality of RNA-Bloom2 is competitive to those of reference-based methods.

opencc-by-4.0Feb 2023View details →

T-cell receptor Vβ (TCRVB) deep sequencing on human T cells isolated from humanized mice engrafted with human PBMC and treated or not with PTCy post-transplantation

Nucleotide sequence data of  TCRVB sequencing performed on T cells isolated from the pre-transplantation hPBMC (donor T cells) or from mice organs at day 21 post-transplantation (injected or not with PTCy at day 3) to determine the impact of PTCy on the T cell V beta (TCRVB) receptor repertoire diversity. NSG mice were engrafted with human PBMC to develop xeno-GVHD and treated or not with 100 mg/kg PTCy. Spleens and lungs from 10 NSG mice per group were pooled and stained to sorted  human CD4+ and CD8+ . DNA of human CD4+ and CD8+ T cells sorted from each organ and  from the PBMC donor was extracted. One hundred fifty µg from each sample were used for T-cell receptor Vβ (TCRVB) deep sequencing performed by Adaptive Biotechnologies.

Reduced representation sequencing to understand the evolutionary history of Torrey pine (Pinus torreyana Parry) with implications for rare species conservation

Understanding the contribution of neutral and adaptive evolutionary processes to population differences is often necessary for better-informed management and conservation of rare species. In this study, we focused on Pinus torreyana Parry (Torrey pine), one of the world's rarest pines, endemic to one island and one mainland population in California. Small population size, low genetic diversity, and susceptibility to abiotic and biotic stresses suggest Torrey pine may benefit from inter-population genetic rescue to preserve the species' evolutionary potential. We leveraged reduced representation sequencing to tease apart the respective contributions of stochastic and deterministic evolutionary processes to population differentiation. We applied these data to model spatial and temporal demographic changes in effective population sizes and genetic connectivity, to assess loci possibly under selection, and to evaluate genetic rescue as a potential conservation strategy. Overall, we observed exceedingly low standing variation reflecting consistently low effective population sizes across time and limited genetic differentiation suggesting maintenance of gene flow following divergence. However, genome scans identified more than 2000 candidate SNPs for divergent selection. Combined with previous observations indicating population phenotypic differentiation, this indicates natural selection has likely contributed to the evolution of population genetic differences. Thus, while reduced genetic diversity, small effective population size, and genetic connectivity between populations suggest genetic rescue could mitigate the adverse effects of rarity, divergent selection suggests genetic mixing could disrupt adaptation. Further work evaluating the fitness consequences of inter-population admixture is necessary to empirically evaluate the trade-offs associated with genetic rescue in Torrey pine.

opencc-by-4.0Mar 2022View details →

Single cell whole genome sequencing from Funnell, O'Flanagan, Williams et al

This repository provides the processed data necessary to reproduce the results from: "Single cell genomic variation induced by mutational processes in cancer Funnell, O’Flanagan, Williams et al" This includes the following: <ul> <li>Single cell whole genome sequencing <ul> <li>Allele specific copy number profiles</li> <li>SNV counts per cell</li> <li>Structural variant counts per cell</li> <li>QC metrics</li> <li>clone assignments</li> <li>phylogenetic trees computed with sitka</li> <li>benchmarking results vs other methods</li> </ul> </li> <li>bulk whole genome sequencing <ul> <li>copy number profiles</li> <li>SNVs</li> </ul> </li> <li>10X single cell RNA sequencing <ul> <li>count matrices</li> <li>seurat Rdata objects</li> </ul> </li> <li>analysis tables <ul> <li>downstream processed results used to generate figures</li> </ul> </li> <li>oxford nanopore <ul> <li>phasing results</li> </ul> </li> </ul>   For further information please feel free to get in touch with Marc Williams (william1 [at] mskcc.org)

Mielke & Carvalho 2022 Chimpanzee play sequences are structured hierarchically as games - Data

Data and scripts for the 2022 manuscript 'Chimpanzee play sequences are structured hierarchically as games' - preprint here:  https://doi.org/10.1101/2022.06.14.496075 Dataset and scripts generated on 20/09/2022. For potential changes and all information see: https://github.com/AlexMielke1988/Mielke-Carvalho_Chimpanzee-Play

Niche overlap between two large herbivores across landscape variability using dietary eDNA metabarcoding: Raw sequences of European bison and red deer – Bialowieza

Understanding the trophic ecology of herbivore species is key to assess their environmental requirements and to improve management policies, but measuring their trophic interactions remains challenging. Among the methods available, quantifying the plant composition of a species' diet provides a detailed picture of how species exploit the resources in their environment and their associated niche overlap. Yet, most studies focusing on herbivore trophic ecology ignore the influence that landscape variability may have. Here, we studied how landscape variability influences trophic interactions through niche partitioning. We used eDNA metabarcoding to quantify the diet composition of two large herbivores of the Bialowieza Forest, red deer (Cervus elaphus) and European bison (Bison bonasus, hereafter referred to as bison) to investigate how increasing habitat quality and predation risk in their environment influence their diet composition and niche partitioning. We found red deer to have an overall greater diet variability and lower niche overlap within species compared to bison. Moreover, our findings indicate herbivore interactions are non-homogeneous across the landscape. Higher habitat quality was associated with higher niche overlap only within bison. We also detected an increase in niche overlap with increasing predation risk within red deer, indicating they modify their diet choice as a reaction to wolf predation risk. This study provides evidence of eDNA dietary metabarcoding as a useful tool for wildlife management to assess the status of species in an ecosystem based on known environmental factors. We suggest future studies to integrate the environments' variability when studying trophic ecology of herbivores to capture the whole extent of species interaction in order to improve conservation and management guidelines.

Seismicity modulation due to hydrological loading in a stable continental region: a case study from the Jektvik swarm sequence in Northern Norway

This folder contains earthquake catalog used in "Seismicity modulation due to hydrological loading in a stable continental region: a case study from the Jektvik swarm sequence in Northern Norway" by Shiddiqi et al. (2022) submitted to Geophysical Journal International. note: unrelocated earthquakes are marked with 999 in location errors.

Earthquake catalog for "Seismicity modulation due to hydrological loading in a stable continental region: a case study from the Jektvik swarm sequence in Northern Norway"

PredictION: A predictive model to establish the performance of Oxford sequencing reads of SARS-CoV-2

Dataset (1) that included 1461 samples and a dataset (2) with 471 samples that was a subset of dataset 1 that included Number of sequenced reads per genome, CT (Cycle threshold) value [N2 target gene], mean coverage depth, coverage genome (percentage), and quantification cDNA (ng/µl).

Row fastq files generated by 16S rRNA sequencing for the metabarcoding analysis of Hidalgo-Villeda et al. paper

Fastq files used for the microbiome profiling of the terminal ileal and caecum content. Sequencing of the terminal ileal content was performed at the Institute Hospitalo-Universitaire Méditerannée Infection, Marseille, France. Sequencing of the caecum content was performed at Genoscreen, Lille, France The sequencing methodology is described on the methods part of the paper "A physiological mouse model of severe acute malnutrition reveals prolonged dysbiosis and altered immunity under nutritional intervention, Hidalgo-Villeda et al.". The metadata.xlsx table present the description and correspondance of each fastq files.

opencc-by-4.0Aug 2022View details →

Code and Data for "Real-time dynamic single-molecule protein sequencing on an integrated semiconductor device"

Code and Data for "Real-time dynamic single-molecule protein sequencing on an integrated semiconductor device". <pre>Code to analyze data produced by the Quantum-Si benchtop device and semiconductor chip is provided in a Python library qsi_algo under several submodules: - rs_caller.py: Algorithm for calling RS segments (also called ROI segments throughout code). - rs_caller_controller.py: Code framework for executing RS calling and property computation in a distributed manner - rs_properties: Code for computing properties of identified RS - rs_classifier: Algorithms for identifying peptide states (i.e. residue calls) associated with an RS - utils.py: shared helper code - pulse_reader: reader for binary pulse file - filters: ROI and pulse filtering utilities - plotting: functions for visualization of data relevant to the analyses presented Jupyter notebooks (.ipynb) files are named according to the manuscript figure they are associated with. Analysis code inside uses provided RS (recognition segment) data to demonstrate filtering and residue-calling techniques required to replicate analyses shown in manuscript figures. Please note: several methods rely on randomization for model initialization and/or data sampling which can cause small deviations from equivalent analyses in published figures. The raw data produced from the Quantum-Si benchtop device and semiconductor chip for the assays presented in the accompanying study is presented in a pulse-called binary file format. Pulses can be used as input for RS identification and peptide state identification. Pre-segmented (RS-identified) files are included for convenience. The data contained in the files include: {run_id}.bin: Binary format for storing pulse info. The reader provided in qsi_algo.pulse_reader produces the following columns: - aperture_index: unique aperture index on chip - start_f: index of first frame in pulse, counted from the beginning of the run - end_f: index of last frame in pulse, counted from the beginning of the run - dur_f: duration of pulse in frames - dur_s: duration of pulse in seconds - ipd_f: interpulse duration in frames (number of frames since end of preceding pulse) - ipd_s: interpulse duration in seconds (time in seconds elapsed since end of preceding pulse) - snr: signal-to-noise ratio (bin1_intensity / bin1_bg_std) - intensity: intensity of pulse (counts above baseline in bin1) - bin0_intensity: counts above baseline in bin0 - intensity_display: bin1_intensity + bin1_bg_mean - binratio: bin0_intensity / bin1_intensity - bg_mean: bin1 background mean in region of pulse - bg_std: bin1 background standard deviation in region pulse - bin0_bg_mean: bin0 background mean in region of pulse - bin0_bg_std: bin0 background standard deviation in region pulse {run_id}.csv.gz: Compressed comma-separated value file containing RS/ROI properties computed from raw pulses.bin file by included RS caller (example in rs_caller.py). - ap: unique aperture index on chip - ROI: ordinal ROI number in the aperture, 0-indexed - start_p: index (.loc) of first pulse in the ROI (inclusive) in pulse dataframe - end_p: index (.loc) of last pulse in the ROI (inclusive) in pulse dataframe - start_f: first frame of the first pulse in the ROI (inclusive) - end_f: Last frame of the last pulse in the ROI (exclusive) - start_s: Time (in seconds elapsed from beginning of run) of the start of the ROI - end_s: Time (in seconds elapsed from beginning of run) of the end of the ROI - dur_f: Duration in frames of the ROI - dur_s: Duration in seconds of the ROI - num_pulses: Number of pulses in the ROI (that also passed filtering during ROI-calling) - pw_mean: Mean pulse duration (in seconds) of pulses in the ROI - ipd_mean: Mean inter-pulse duration (in seconds) of pulses in the ROI - snr_mean: Mean signal-to-noise ratio of pulses in the ROI - intensity_mean: Mean intensity above baseline of pulses in the ROI - binratio_norm: Estimated pulse bin ratio of pulses in the ROI, according to the following equation: sum(bin0_intensity*dur_f) / np.sum(bin1_intensity*dur_f) - ROI_score: ROI quality score (0-1 from least to most likely to contain recognizer-peptide recognition pulsing) - binratio_skew: bin ratio correction factor accounting for binning signal timing differences across the chip. This factor has already been applied to the binratio_norm column</pre>

Shallow shotgun sequencing of the microbiome recapitulates 16S amplicon results and provides functional insights

Prevailing 16S rRNA gene-amplicon methods for characterizing the bacterial microbiome of wildlife are economical, but result in coarse taxonomic classifications, are subject to primer and 16S copy number biases, and do not allow for direct estimation of microbiome functional potential. While deep shotgun metagenomic sequencing can overcome many of these limitations, it is prohibitively expensive for large sample sets. We evaluated the ability of shallow shotgun metagenomic sequencing to characterize taxonomic and functional patterns in the fecal microbiome of a model population of feral horses (Sable Island, Canada). Since 2007, this unmanaged population has been the subject of an individual-based, long-term ecological study. Using deep shotgun metagenomic sequencing, we determined the sequencing depth required to accurately characterize the horse microbiome. In comparing conventional versus high-throughput shotgun metagenomic library preparation techniques, we validate the use of more cost-effective lab methods. Finally, we characterize similarities between 16S amplicon and shallow shotgun characterization of the microbiome and demonstrate that the latter recapitulates biological patterns first described in a published amplicon dataset. Unlike amplicon data, we further demonstrate how shallow shotgun metagenomic data provide useful insights about microbiome functional potential which support previously hypothesized diet effects in this study system.

opencc-by-4.0Sep 2021View details →

Summary of sequence variations in strains of Sars-CoV-2

This entry collects JSON files specifying sequence variations of different strains (aka variants) of SARS-CoV-2 based on data retrieved from <a href="https://outbreak.info/">outbreak.info</a> and/or <a href="https://covariants.org/variants/">covariants.org</a>. These JSON files are formatted to match the <a href="https://docs.google.com/document/d/1wFJjdyl1OASnsBNkUzUx4ME8YhVybhIWCTr3Z1fBEWQ/pub">Feature API</a> of <a href="http://aquaria.ws/covid">aquaria.ws</a>.  File names match the <a href="https://www.who.int/en/activities/tracking-SARS-CoV-2-variants/">linage names</a> of VOCs and VOIs. In the case of omicron we have added a version (omicron_charge) that highlights charge changing residues in magenta, as well as an extra file (omicron_BA2) for the <a href="https://cov-lineages.org/lineage.html?lineage=BA.2">BA.2</a>/21K sister clade and a file (omicron_BA1_BA2_diff) highlighting the differences between the lineages (coloring variations in only BA.1 red, only BA.2 blue, in both magenta). <a href="https://zenodo.org/record/5792281/files/CovidVariants.pdf">CovidVariants.pdf</a> lists SARS-CoV-2 proteins together with links that show how to map variations onto the structures.

Exploring cell diversity and fidelity in crustacean limb regeneration using single-nucleus RNA sequencing

R objects containing datasets generated by snRNA-seq on Parhyale hawaiensis limbs. These datasets have been generated during my Phd thesis.

opencc-zeroOct 2022View details →

Cytb gene sequences of Fejervarya species from Lesser Sunda, Indonesia and other Asian countries

Cyt b gene sequences of Fejervarya species were done and later submitted to DDBJ. Then, we received accession number which are used in our manuscript "Postmating isolation and evolutionary relationships among Fejervarya species from Lesser Sunda, Indonesia and other Asian countries revealed by crossing experiments and mtDNA Cytb sequences analyses". These are genuine data. There is no conflict of interest of these data.