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199 results for “reference genome”
Virus+ Sequence Masked Mouse Reference Genome (GRCm38)
<p>A version of the mouse genome (<a href="https://www.ncbi.nlm.nih.gov/assembly/327618">GRCm38</a>) masked for all possible viral sequences.</p> <p>See <a href="https://zenodo.org/record/4116107#.X5B7ti9h3UI">Virus+ Masked Human Genome</a> for a masked human reference database.</p> <p>The following commands were used to generate the additional virus sequence masked reference database:</p> <p><strong>1) Download all RefSeq and Neighbor nucleotide records:</strong></p> <p><a href="https://www.ncbi.nlm.nih.gov/nuccore/?term=Viruses[Organism]%20NOT%20cellular%20organisms[ORGN]%20NOT%20wgs[PROP]%20NOT%20gbdiv%20syn[prop]%20AND%20(srcdb_refseq[PROP]%20OR%20nuccore%20genome%20samespecies[Filter])">https://www.ncbi.nlm.nih.gov/nuccore/?term=Viruses[Organism]%20NOT%20cellular%20organisms[ORGN]%20NOT%20wgs[PROP]%20NOT%20gbdiv%20syn[prop]%20AND%20(srcdb_refseq[PROP]%20OR%20nuccore%20genome%20samespecies[Filter])</a></p> <p><strong>2) Shred the downloaded viral genomes using shred.sh from the <a href="https://jgi.doe.gov/data-and-tools/bbtools/">bbtools</a> package</strong></p> <p>shred.sh in=refseq_virus_reformated.fasta out=virus_shred.fasta.gz length=85 minlength=75 overlap=30</p> <p><strong>3) Map shredded virus sequence to the GRCm38</strong><strong> genome using bbmap.sh from the <a href="https://jgi.doe.gov/data-and-tools/bbtools/">bbtools</a> package</strong></p> <p>bbmap.sh ref=GRCm38.fa.gz in=virus_shred.fasta.gz outm=map_mouse_all_viruses.sam minid=0.90</p> <p><strong>4) Mask virus sequenced mapped regions from the GRCm38 genome using bbmask.sh from the <a href="https://jgi.doe.gov/data-and-tools/bbtools/">bbtools</a> package</strong></p> <p>bbmask.sh in=GRCm38.fa.gz out=GRCm38_virus_masked.fasta.gz sam=map_mouse_all_viruses.sam</p> <p><strong>5) Remove all N's to further reduce file size using <a href="https://bioinf.shenwei.me/seqkit/">seqkit</a></strong><br> seqkit -is replace -p "n" -r "" GRCm38_virus_masked.fasta.gz > mouse_virus_masked.fasta_Ns_removed.gz</p> <p><strong>Additional References:</strong></p> <ol> <li><a href="https://jgi.doe.gov/data-and-tools/bbtools/">bbtools</a></li> <li><a href="https://bioinf.shenwei.me/seqkit/">seqkit</a></li> <li><a href="https://www.ncbi.nlm.nih.gov/genome/viruses/">NCBI Virus Genome RefSeq</a></li> </ol>
Virus+ Sequence Masked Human Reference Genome (hg19)
<p>A version of the human genome (hg19) originally masked for ribosomal, plant, animal, fungal and low-entropy sequences by Brian Bushnell (<a href="https://zenodo.org/record/1208052#.X5BuTy9h3UI">Bushnell Masked Human Genome</a>) additionally masked for all possible viral sequences.</p> <p>The following commands were used to generate the additional virus sequence masked reference database:</p> <p><strong>1) Download all RefSeq and Neighbor nucleotide records:</strong></p> <p><a href="https://www.ncbi.nlm.nih.gov/nuccore/?term=Viruses[Organism]%20NOT%20cellular%20organisms[ORGN]%20NOT%20wgs[PROP]%20NOT%20gbdiv%20syn[prop]%20AND%20(srcdb_refseq[PROP]%20OR%20nuccore%20genome%20samespecies[Filter])">https://www.ncbi.nlm.nih.gov/nuccore/?term=Viruses[Organism]%20NOT%20cellular%20organisms[ORGN]%20NOT%20wgs[PROP]%20NOT%20gbdiv%20syn[prop]%20AND%20(srcdb_refseq[PROP]%20OR%20nuccore%20genome%20samespecies[Filter])</a></p> <p><strong>2) Shred the downloaded viral genomes using shred.sh from the <a href="https://jgi.doe.gov/data-and-tools/bbtools/">bbtools</a> package</strong></p> <p>shred.sh in=refseq_virus_reformated.fasta out=virus_shred.fasta.gz length=85 minlength=75 overlap=30</p> <p><strong>3) Map shredded virus sequence to the hg19-masked human genome using bbmap.sh from the <a href="https://jgi.doe.gov/data-and-tools/bbtools/">bbtools</a> package</strong></p> <p>bbmap.sh ref=hg19_main_mask_ribo_animal_allplant_allfungus.fa.gz in=virus_shred.fasta.gz outm=map_human_all_viruses.sam minid=0.90</p> <p><strong>4) Mask virus sequenced mapped regions from the hg19-masked human genome using bbmask.sh from the <a href="https://jgi.doe.gov/data-and-tools/bbtools/">bbtools</a> package</strong></p> <p>bbmask.sh in=hg19_main_mask_ribo_animal_allplant_allfungus.fa.gz out=human_virus_masked.fasta.gz sam=map_human_all_viruses<br> .sam</p> <p><strong>5) Remove all N's to further reduce file size using <a href="https://bioinf.shenwei.me/seqkit/">seqkit</a></strong><br> seqkit -is replace -p "n" -r "" human_virus_masked.fasta.gz > human_virus_masked.fasta_Ns_removed.gz</p> <p><strong>Additional References:</strong></p> <ol> <li><a href="http://seqanswers.com/forums/showthread.php?t=42552">http://seqanswers.com/forums/showthread.php?t=42552</a> for additional information on the original masking of hg19</li> <li><a href="https://jgi.doe.gov/data-and-tools/bbtools/">bbtools</a></li> <li><a href="https://bioinf.shenwei.me/seqkit/">seqkit</a></li> <li><a href="https://www.ncbi.nlm.nih.gov/genome/viruses/">NCBI Virus Genome RefSeq</a></li> </ol>
Genomes and full-length 16S reference sequences for 27 Alpha- and Gamma-Proteobacterial isolates from Red Sea Acropora corals
<p>Coral-associated bacteria contribute to the biology of their host, but the underlying molecular interactions are largely unknown. To further our functional understanding, we obtained 27 alpha- and gamma-proteobacterial isolates, many of which are Rhodobacteraceae, from three coral species of the genus <em>Acropora </em>and assembled/annotated their genomes as a resource for further functional studies. Our results reveal the immense taxonomic and genetic diversity of common alpha- and gamma-proteobacterial coral-associated bacteria. We hope these data provide a framework to study the function of specific bacteria in the coral holobiont. Isolates are available upon request.</p>
The complete reference genome for grapevine (Vitis vinifera L.) genetics and breeding
<div>PN40024, a highly homozygous inbred line originating from ‘Helfensteiner’, was used for T2T genome assembly. In total, 21 Gb (21 024 461 524 bp, ∼42× coverage) HiFi reads were generated by the PacBio platform. For the preliminary assembly, hifiasm was used to assemble the HiFi reads. We then used MUMmer and the 12X.v0 genome version (V. vinifera genome assembly 12X.v0 to order the 38 contigs into 19 chromosomes.</div> <p> The PN_T2T genome size was finally generated (494.87 Mb), being 69 Mb longer than 12X.v0 using the same statistical method. The k-mer metric was used to evaluate genomic homozygosity, estimated at 99.8%. The BUSCO for this genome is up to 98.5%.</p> <p>The PN40024.T2T genome assembly: PN.fa</p> <p>The PN40024.T2T gene annotation: PN_T2T.v5.1.gff3</p> <p>The PN40024.T2T TE annotation: PN_T2T_TE.gff</p> <p>The PN40024.T2T centromere annotation: PN.trf.gff3</p> <p>The PN40024.T2T protein sequence: PN_protein.fa</p> <p>The PN40024.T2T cds sequence: PN40024.cds.fa</p> <p>Comparison of gene annotation among PN_T2T and PN_T2T.v5.1, 12X.v0, 12X.v2, PN40024.v4, PN40024.v4.1: correlation.list.txt</p> <p>Mitochondrial assembly sequence of PN40024: PN_T2T_mit.fa</p> <p>Annotation of mitochondrial assembly for PN40024:PN_T2T_mit.gff3</p> <p>Chloroplast assembly sequence of PN40024: PN_T2T_chl.fa</p> <p>Annotation of chloroplast assembly for PN40024: PN_T2T_chl.gff3</p> <p>Citation: </p> <p>Please cite this paper when using the data of PN_T2T for your publications.</p> <p>Xiaoya Shi, Shuo Cao, Xu Wang, Siyang Huang, Yue Wang, Zhongjie Liu, Wenwen Liu, Xiangpeng Leng, Yanling Peng, Nan Wang, Yiwen Wang, Zhiyao Ma, Xiaodong Xu, Fan Zhang, Hui Xue, Haixia Zhong, Yi Wang, Kekun Zhang, Amandine Velt, Komlan Avia, Daniela Holtgräwe, Jérôme Grimplet, José Tomás Matus, Doreen Ware, Xinyu Wu, Haibo Wang, Chonghuai Liu, Yuling Fang, Camille Rustenholz, Zongming Cheng, Hua Xiao, Yongfeng Zhou, The complete reference genome for grapevine (<em>Vitis vinifera</em> L.) genetics and breeding, <em>Horticulture Research</em>, Volume 10, Issue 5, May 2023, uhad061, <a href="https://doi.org/10.1093/hr/uhad061">https://doi.org/10.1093/hr/uhad061</a></p>
A termite genome reference and its Bowtie2 index
<p>This dataset contains a fasta file and its Bowtie2 index. The fasta file includes publicly available genomes of 5 termite species, namely <em>Zootermopsis nevadensis </em>(Terrapon, N., Li, C., Robertson, H. M., Ji, L., Meng, X., Booth, W., ... & Liebig, J. (2014). Molecular traces of alternative social organization in a termite genome. Nature communications, 5(1), 1-12.), <em>Cryptotermes secundus</em> (Harrison, M. C., Jongepier, E., Robertson, H. M., Arning, N., Bitard-Feildel, T., Chao, H., ... & Bornberg-Bauer, E. (2018). Hemimetabolous genomes reveal molecular basis of termite eusociality. Nature ecology & evolution, 2(3), 557-566.), <em>Macrotermes natalensis</em> (Poulsen, M., Hu, H., Li, C., Chen, Z., Xu, L., Otani, S., ... & Zhang, G. (2014). Complementary symbiont contributions to plant decomposition in a fungus-farming termite. Proceedings of the National Academy of Sciences, 111(40), 14500-14505.), <em>Coptotermes formosanus</em> (Draft genome sequence of the termite, Coptotermes formosanus: Genetic insights into the pyruvate dehydrogenase complex of the termite) and <em>Reticulitermes speratus </em>(Shigenobu, S., Hayashi, Y., Watanabe, D., Tokuda, G., Hojo, M. Y., Toga, K., Saiki, R., Yaguchi, H., Masuoka, Y., Suzuki, R., Suzuki, S., Kimura, M., Matsunami, M., Sugime, Y., Oguchi, K., Niimi, T., Gotoh, H., Hojo, M. K., Miyazaki, S., … Maekawa, K. (2022). Genomic and transcriptomic analyses of the subterranean termite Reticulitermes speratus: Gene duplication facilitates social evolution. Proceedings of the National Academy of Sciences, 119(3), e2110361119.). These genomic sequences have been classified with Kraken 2 v2.1.2 (Wood, D. E., Lu, J., & Langmead, B. (2019). Improved metagenomic analysis with Kraken 2. Genome Biology, 20(1), 1–13 and Wood, D. E., & Salzberg, S. L. (2014). Kraken: Ultrafast metagenomic sequence classification using exact alignments. Genome Biology, 15(3).) to remove all microbial sequences. This cleaned fasta file was indexed using the bowtie2-build command from Bowtie2 (Langmead, B., & Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nature Methods, 9(4), 357–359.) and can be used to perform alignments.</p>
Four Reference Quality Genome Assemblies of Pyrenophora teres f. maculata: A Resource for Studying the Barley Spot Form Net Blotch Interaction
<p>Updated draft genome assembly (FASTA) and annotation (GFF) for the <em>P. teres </em>f.<em> maculata </em>isolate FGOB10Ptm-1. </p>
Four Reference Quality Genome Assemblies of Pyrenophora teres f. maculata: A Resource for Studying the Barley Spot Form Net Blotch Interaction
<p>Updated draft genome assembly (FASTA) and annotation (GFF) for the <em>P. teres </em>f.<em> maculata </em>isolate P-A14. </p>
Comprehensive 100-bp resolution genome-wide epigenomic profiling data for the hg38 human reference genome
<p>This is a comprehensive collection of diverse epigenomic profiling data in 100-bp resolution with full genome-wide coverage. The datasets are processed from raw read count data collected from five types of sequencing-based assays collected by the Encyclopedia of DNA Elements (ENCODE, <a href="http://www.encodeproject.org">http://www.encodeproject.org</a>) consortium. A total of 6,305 alignment profiles from various high-throughput sequencing assays available on the ENCODE database were preprocessed and filtered according to ENCODE’s data standard</p>
Lepidoptera genomics based on 88 chromosomal reference sequences informs population genetic parameters for conservation
<p>This repository contains (1) germline mutations called by the DeepVariant (v1.1.0) pipeline in VCF format; (2) rejected substitution scores calculated by the Genomic Evolutionary Rate Profiling (GERP++) software on each species and chromosome; and (3) the phylogenetic tree used as guide tree in the Cactus alignment.</p>
ZymoBIOMICS reference genomes
<p>All these reference genomes were independently sequenced by Zymo Research Corporation (Irvine, CA, USA). More information about the mock communities can be found at:</p> <p>- ZymoBIOMICS™Microbial Community Standard (Catalog No. D6300): https://bit.ly/3gDUHC9</p> <p>- ZymoBIOMICS™Microbial Community Standard II (Log Distribution) (Catalog No. D6310): https://bit.ly/2ZRjlbs</p>
Liftover of DGRP D.melanogaster genotypes to reference genome assembly v6.0, with QC graph
<p>Output are vcf and plink-format genotype files. Also provided are the run code in bash and R, the logs, summary statistics, and a graph showing how the positions of SNPs have changed.</p>
The Helicobacter pylori Genome Project (HpGP) Phase1 dataset and 255 H. pylori population reference dataset
<p>This repository holds the HpGP Phase 1 genomic dataset for Hp26695 and 1011 study samples. All 1012 genomic sequences were annotated using the NCBI Prokaryotic Genome Annotation Pipeline(PGAP). Also, it has 255 curated public available H. pylori genomic sequences used for population structure analysis in Thorell et al. Nature Communications, 14:8184 (2023).</p> <p>You can check the NCBI BioProject website for the latest annotation and sequence updates.</p> <p>https://www.ncbi.nlm.nih.gov/bioproject/?term=HpGP</p> <p>Please cite the above-mentioned paper if you use the data.</p>
Genomic Analysis of Public Klebsiella Reference Strains
<p>A genomic resource of <em>Klebsiella </em>reference strains from ATCC, NCTC and BEI Resources MRSN Diversity Panel.</p>
Reference genome choice and filtering thresholds jointly influence phylogenomic analyses
<p>Molecular phylogenies are a cornerstone of modern comparative biology and are commonly employed to investigate a range of biological phenomena, such as diversification rates, patterns in trait evolution, biogeography, and community assembly. Recent work has demonstrated that significant biases may be introduced into downstream phylogenetic analyses from processing genomic data; however, it remains unclear whether there are interactions among bioinformatic parameters or biases introduced through the choice of reference genome for sequence alignment and variant-calling. We address these knowledge gaps by employing a combination of simulated and empirical data sets to investigate to what extent the choice of reference genome in upstream bioinformatic processing of genomic data influences phylogenetic inference, as well as the way that reference genome choice interacts with bioinformatic filtering choices and phylogenetic inference method. We demonstrate that more stringent minor allele filters bias inferred trees away from the true species tree topology, and that these biased trees tend to be more imbalanced and have a higher center of gravity than the true trees. We find the greatest topological accuracy when filtering sites for minor allele count > 3–4 in our 51-taxa data sets, while tree center of gravity was closest to the true value when filtering for sites with minor allele count > 1-2. In contrast, filtering for missing data increased accuracy in the inferred topologies; however, this effect was small in comparison to the effect of minor allele filters and may be undesirable due to a subsequent mutation spectrum distortion. The bias introduced by these filters differs based on the reference genome used in short read alignment, providing further support that choosing a reference genome for alignment is an important bioinformatic decision with implications for downstream analyses. These results demonstrate that attributes of the study system and dataset (and their interaction) add important nuance for how best to assemble and filter short read genomic data for phylogenetic inference.</p>
reference genome used for scRNA-seq mapping with CellRanger in the method spatial-scERA
<p>The modified <em>Drosophila </em>melanogaster (dm6) reference genome used for the mapping with CellRanger in the method paper about spatial-scERA</p> <p>The genome is composed of the original genome from EnsembleMetazo website (BDGP6.46.110). An addition of 26 chromosomes (one for the plasmid construct and 25 for the tested enhancer sequences) is also present to allow for the mapping of mRNAs comming from our constructs. </p>
bin3C - GTDB metadata associated with reference genomes selected for the simulated community
<p>Supplementary data table S1 from the manuscript</p> <p>bin3C : Exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes (MAGs)</p> <p>A simulated community was constructed for ground truth validation of bin3C results. This table lists the GTDB metadata associated with each of the 63 selected genomes.</p>
hg19KIndel: Ethnicity normalized human reference genome
<p>The above zip files (hg19KIndel_Resource.zip) contains the following folders. Specific Details about how each file within the below mentioned folders were derived are present in individual README files for each folder</p> <p>1) hg19Kindel</p> <p> -hg19Kindel.fa - fasta file representing the modified assembly</p> <p>2) Gene Annotations</p> <p> -hg19_refGene.txt - RefSeq gene annotation downloaded from UCSC table browser (for hg19)<br> -hg19Kindel_refGene.txt - RefSeq gene annotation corresponding to hg19Kindel Genome</p> <p>3) SnpEff_Database</p> <p> -snpEffectPredictor.bin - Binary file used by SnpEff to annotate variants</p> <p>4) LiftOver_and_Chain_File</p> <p> -hg19Kindeltohg19.over.chain - UCSC chain file for lifting coordinates from hg19Kindel to hg19<br> -convert_cordinates_vcf.py - Python script to liftover variants(vcf) (only point coordinates) called on hg19Kindel to hg19 coordinate frame</p> <p> </p>
ATCC 20 Composite Reference Genome
<p>This is a reference containing the genomes matching the <a href="https://www.atcc.org/products/all/MSA-1002.aspx">ATCC 20 Strain</a> reference material. It includes the following organisms:</p> <ul> <li>Acinetobacter baumannii ATCC 17978</li> <li>Bacillus cereus ATCC 10987</li> <li>Bacteroides vulgatus ATCC 8482</li> <li>Bifidobacterium adolescentis ATCC 15703</li> <li>Clostridium beijerinckii ATCC 35702</li> <li>Cutibacterium acnes subsp. defendens ATCC 11828</li> <li>Deinococcus radiodurans R1</li> <li>Enterococcus faecalis OG1RF</li> <li>Escherichia coli str. K-12 substr. MG1655</li> <li>Helicobacter pylori 26695</li> <li>Lactobacillus gasseri ATCC 33323 = JCM 1131</li> <li>Neisseria meningitidis MC58 serogroup: B source</li> <li>Porphyromonas gingivalis ATCC 33277</li> <li>Pseudomonas aeruginosa PAO1</li> <li>Rhodobacter sphaeroides ATCC 17029</li> <li>Schaalia odontolytica ATCC 17982</li> <li>Staphylococcus aureus subsp. aureus USA300 FPR3757</li> <li>Staphylococcus epidermidis</li> <li>Streptococcus agalactiae 2603V/R</li> <li>Streptococcus mutans UA159</li> </ul>
Additional annotation, alignment, and results from Ka/Ks analysis for Chromosomal-level reference genome assembly of the African Spiny Mouse (Acomys cahirinus)
<p><strong>Annotation files, alignments, and results summaries from Chromosomal-level reference genome assembly of the African Spiny Mouse (Acomys cahirinus).</strong></p> <p>Pairwise genome alignments contain the .maf suffix</p> <p>FASTA alignments from stitched gene blocks contain the .fasta suffix</p> <p>CSV file containing the Ka/Ks results</p> <p>RepeatMasker .out file</p>
Haplotype-aware reference genome reveals hidden somatic mutations of sweet orange
<p><strong>Filename: </strong>ASE_in_five_fruit_development.txt</p> <p><strong>Description: </strong>Based on our haplotype sequences, we confirmed biallelic genes showed significant expression difference between two alleles in at least one fruit developmental stage. We collected the RNA-seq data from fruit of Newhall navel orange at five developmental stages (90, 120, 150, 180 and 210 days after bloom). RNA-seq data from previous project GSE108930 in NCBI database.</p> <p> </p> <p><strong>Filename: </strong>Biallelic_genes_haplogenomes.tsv</p> <p><strong>Description: </strong>The biallelic genes were identified using the Genespace program.</p> <p> </p> <p><strong>Filename: </strong>Haplogenomes_CENH3_chip_peaks.bw</p> <p><strong>Description: </strong>The CENH3 sequences were collected from BankIt ID 2305947. These reads (including the input library as a control) were aligned to the two assembled haplotypes using Bowtie2 (v2.5.1) with default parameters. MACS2 (v2.2.7.1) with the additional parameters “-f BAM -ghs -B -q 0.01” was used to perform peak calling. The peaks generated from CENH3 chip-seq.</p> <p> </p> <p><strong>Filename: </strong>Haplogenomes_Control_chip_peaks.bw</p> <p><strong>Description:</strong> The peaks generated from Control chip-seq.</p> <p> </p> <p><strong>Filename: </strong>Haplotype_based_79accessions_somatic_variations.vcf</p> <p><strong>Description: </strong>The small somatic variations generated based on the haplotype-based method. The derived somatic mutations were identified based on nine samples from the outgroup (Earlier Clade I).</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_CuteSV.vcf</p> <p><strong>Description: </strong>The HiFi reads were mapped to haplotype A. We called SVs using the CuteSV program.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_gene_function_annotation.tsv</p> <p><strong>Description: </strong>The gene annotations of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_gene_model.gff3</p> <p><strong>Description:</strong> The gene structure model of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_genome.fa</p> <p><strong>Description:</strong> The genome sequences of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_PEPPER_OUTPUT.zip</p> <p><strong>Description: </strong>The small variations of sweet orange using the haplotype A as the reference genome.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_TEs_annotation.gff3</p> <p><strong>Description:</strong> The TE annotations of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_gene_function_annotation.tsv</p> <p><strong>Description:</strong> The gene annotations of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_gene_model.gff3</p> <p><strong>Description:</strong> The gene structure model of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_genome.fa</p> <p><strong>Filename: </strong>ASE_in_five_fruit_development.txt</p> <p><strong>Description: </strong>Based on our haplotype sequences, we confirmed biallelic genes showed significant expression difference between two alleles in at least one fruit developmental stage. We collected the RNA-seq data from fruit of Newhall navel orange at five developmental stages (90, 120, 150, 180 and 210 days after bloom). RNA-seq data from previous project GSE108930 in NCBI database.</p> <p> </p> <p><strong>Filename: </strong>Biallelic_genes_haplogenomes.tsv</p> <p><strong>Description: </strong>The biallelic genes were identified using the Genespace program.</p> <p> </p> <p><strong>Filename: </strong>Haplogenomes_CENH3_chip_peaks.bw</p> <p><strong>Description: </strong>The CENH3 sequences were collected from BankIt ID 2305947. These reads (including the input library as a control) were aligned to the two assembled haplotypes using Bowtie2 (v2.5.1) with default parameters. MACS2 (v2.2.7.1) with the additional parameters “-f BAM -ghs -B -q 0.01” was used to perform peak calling. The peaks generated from CENH3 chip-seq.</p> <p> </p> <p><strong>Filename: </strong>Haplogenomes_Control_chip_peaks.bw</p> <p><strong>Description:</strong> The peaks generated from Control chip-seq.</p> <p> </p> <p><strong>Filename: </strong>Haplotype_based_79accessions_somatic_variations.vcf</p> <p><strong>Description: </strong>The small somatic variations generated based on the haplotype-based method. The derived somatic mutations were identified based on nine samples from the outgroup (Earlier Clade I).</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_CuteSV.vcf</p> <p><strong>Description: </strong>The HiFi reads were mapped to haplotype A. We called SVs using the CuteSV program.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_gene_function_annotation.tsv</p> <p><strong>Description: </strong>The gene annotations of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_gene_model.gff3</p> <p><strong>Description:</strong> The gene structure model of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_genome.fa</p> <p><strong>Description:</strong> The genome sequences of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_PEPPER_OUTPUT.zip</p> <p><strong>Description: </strong>The small variations of sweet orange using the haplotype A as the reference genome.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_TEs_annotation.gff3</p> <p><strong>Description:</strong> The TE annotations of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_gene_function_annotation.tsv</p> <p><strong>Description:</strong> The gene annotations of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_gene_model.gff3</p> <p><strong>Description:</strong> The gene structure model of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_genome.fa</p> <p><strong>Description:</strong> The genome sequences of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_TEs_annotation.gff3</p> <p><strong>Description:</strong> The TE annotations of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>Single_reference_87accessions_somatic_variations.vcf</p> <p><strong>Description:</strong> The small somatic variations generated based on the single reference genome (Haplotype A).</p> <p> </p> <p><strong>Filename: </strong>Somatic_material_RNA_seq_matrix.txt</p> <p><strong>Description: </strong>The expression matrix of BT_3 and BT_5 (a set of somatic mutation material).</p> <p> </p> <p><strong>Filename: </strong>ASE_in_five_fruit_development.txt</p> <p><strong>Description: </strong>Based on our haplotype sequences, we confirmed biallelic genes showed significant expression difference between two alleles in at least one fruit developmental stage. We collected the RNA-seq data from fruit of Newhall navel orange at five developmental stages (90, 120, 150, 180 and 210 days after bloom). RNA-seq data from previous project GSE108930 in NCBI database.</p> <p> </p> <p><strong>Filename: </strong>Biallelic_genes_haplogenomes.tsv</p> <p><strong>Description: </strong>The biallelic genes were identified using the Genespace program.</p> <p> </p> <p><strong>Filename: </strong>Haplogenomes_CENH3_chip_peaks.bw</p> <p><strong>Description: </strong>The CENH3 sequences were collected from BankIt ID 2305947. These reads (including the input library as a control) were aligned to the two assembled haplotypes using Bowtie2 (v2.5.1) with default parameters. MACS2 (v2.2.7.1) with the additional parameters “-f BAM -ghs -B -q 0.01” was used to perform peak calling. The peaks generated from CENH3 chip-seq.</p> <p> </p> <p><strong>Filename: </strong>Haplogenomes_Control_chip_peaks.bw</p> <p><strong>Description:</strong> The peaks generated from Control chip-seq.</p> <p> </p> <p><strong>Filename: </strong>Haplotype_based_79accessions_somatic_variations.vcf</p> <p><strong>Description: </strong>The small somatic variations generated based on the haplotype-based method. The derived somatic mutations were identified based on nine samples from the outgroup (Earlier Clade I).</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_CuteSV.vcf</p> <p><strong>Description: </strong>The HiFi reads were mapped to haplotype A. We called SVs using the CuteSV program.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_gene_function_annotation.tsv</p> <p><strong>Description: </strong>The gene annotations of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_gene_model.gff3</p> <p><strong>Description:</strong> The gene structure model of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_genome.fa</p> <p><strong>Description:</strong> The genome sequences of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_PEPPER_OUTPUT.zip</p> <p><strong>Description: </strong>The small variations of sweet orange using the haplotype A as the reference genome.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_TEs_annotation.gff3</p> <p><strong>Description:</strong> The TE annotations of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_gene_function_annotation.tsv</p> <p><strong>Description:</strong> The gene annotations of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_gene_model.gff3</p> <p><strong>Description:</strong> The gene structure model of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_genome.fa</p> <p><strong>Description:</strong> The genome sequences of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_TEs_annotation.gff3</p> <p><strong>Description:</strong> The TE annotations of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>Single_reference_87accessions_somatic_variations.vcf</p> <p><strong>Description:</strong> The small somatic variations generated based on the single reference genome (Haplotype A).</p> <p> </p> <p><strong>Filename: </strong>Somatic_material_RNA_seq_matrix.txt</p> <p><strong>Description: </strong>The expression matrix of BT_3 and BT_5 (a set of somatic mutation material).</p> <p> </p> <p><strong>Filename: </strong>ASE_in_five_fruit_development.txt</p> <p><strong>Description: </strong>Based on our haplotype sequences, we confirmed biallelic genes showed significant expression difference between two alleles in at least one fruit developmental stage. We collected the RNA-seq data from fruit of Newhall navel orange at five developmental stages (90, 120, 150, 180 and 210 days after bloom). RNA-seq data from previous project GSE108930 in NCBI database.</p> <p> </p> <p><strong>Filename: </strong>Biallelic_genes_haplogenomes.tsv</p> <p><strong>Description: </strong>The biallelic genes were identified using the Genespace program.</p> <p> </p> <p><strong>Filename: </strong>Haplogenomes_CENH3_chip_peaks.bw</p> <p><strong>Description: </strong>The CENH3 sequences were collected from BankIt ID 2305947. These reads (including the input library as a control) were aligned to the two assembled haplotypes using Bowtie2 (v2.5.1) with default parameters. MACS2 (v2.2.7.1) with the additional parameters “-f BAM -ghs -B -q 0.01” was used to perform peak calling. The peaks generated from CENH3 chip-seq.</p> <p> </p> <p><strong>Filename: </strong>Haplogenomes_Control_chip_peaks.bw</p> <p><strong>Description:</strong> The peaks generated from Control chip-seq.</p> <p> </p> <p><strong>Filename: </strong>Haplotype_based_79accessions_somatic_variations.vcf</p> <p><strong>Description: </strong>The small somatic variations generated based on the haplotype-based method. The derived somatic mutations were identified based on nine samples from the outgroup (Earlier Clade I).</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_CuteSV.vcf</p> <p><strong>Description: </strong>The HiFi reads were mapped to haplotype A. We called SVs using the CuteSV program.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_gene_function_annotation.tsv</p> <p><strong>Description: </strong>The gene annotations of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_gene_model.gff3</p> <p><strong>Description:</strong> The gene structure model of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_genome.fa</p> <p><strong>Description:</strong> The genome sequences of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_PEPPER_OUTPUT.zip</p> <p><strong>Description: </strong>The small variations of sweet orange using the haplotype A as the reference genome.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_TEs_annotation.gff3</p> <p><strong>Description:</strong> The TE annotations of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_gene_function_annotation.tsv</p> <p><strong>Description:</strong> The gene annotations of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_gene_model.gff3</p> <p><strong>Description:</strong> The gene structure model of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_genome.fa</p> <p><strong>Description:</strong> The genome sequences of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_TEs_annotation.gff3</p> <p><strong>Description:</strong> The TE annotations of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>Single_reference_87accessions_somatic_variations.vcf</p> <p><strong>Description:</strong> The small somatic variations generated based on the single reference genome (Haplotype A).</p> <p> </p> <p><strong>Filename: </strong>Somatic_material_RNA_seq_matrix.txt</p> <p><strong>Description: </strong>The expression matrix of BT_3 and BT_5 (a set of somatic mutation material).</p> <p><strong>Filename: </strong>ASE_in_five_fruit_development.txt</p> <p><strong>Description: </strong>Based on our haplotype sequences, we confirmed biallelic genes showed significant expression difference between two alleles in at least one fruit developmental stage. We collected the RNA-seq data from fruit of Newhall navel orange at five developmental stages (90, 120, 150, 180 and 210 days after bloom). RNA-seq data from previous project GSE108930 in NCBI database.</p> <p> </p> <p><strong>Filename: </strong>Biallelic_genes_haplogenomes.tsv</p> <p><strong>Description: </strong>The biallelic genes were identified using the Genespace program.</p> <p> </p> <p><strong>Filename: </strong>Haplogenomes_CENH3_chip_peaks.bw</p> <p><strong>Description: </strong>The CENH3 sequences were collected from BankIt ID 2305947. These reads (including the input library as a control) were aligned to the two assembled haplotypes using Bowtie2 (v2.5.1) with default parameters. MACS2 (v2.2.7.1) with the additional parameters “-f BAM -ghs -B -q 0.01” was used to perform peak calling. The peaks generated from CENH3 chip-seq.</p> <p> </p> <p><strong>Filename: </strong>Haplogenomes_Control_chip_peaks.bw</p> <p><strong>Description:</strong> The peaks generated from Control chip-seq.</p> <p> </p> <p><strong>Filename: </strong>Haplotype_based_79accessions_somatic_variations.vcf</p> <p><strong>Description: </strong>The small somatic variations generated based on the haplotype-based method. The derived somatic mutations were identified based on nine samples from the outgroup (Earlier Clade I).</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_CuteSV.vcf</p> <p><strong>Description: </strong>The HiFi reads were mapped to haplotype A. We called SVs using the CuteSV program.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_gene_function_annotation.tsv</p> <p><strong>Description: </strong>The gene annotations of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_gene_model.gff3</p> <p><strong>Description:</strong> The gene structure model of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_genome.fa</p> <p><strong>Description:</strong> The genome sequences of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_PEPPER_OUTPUT.zip</p> <p><strong>Description: </strong>The small variations of sweet orange using the haplotype A as the reference genome.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeA_TEs_annotation.gff3</p> <p><strong>Description:</strong> The TE annotations of haplotype A.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_gene_function_annotation.tsv</p> <p><strong>Description:</strong> The gene annotations of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_gene_model.gff3</p> <p><strong>Description:</strong> The gene structure model of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_genome.fa</p> <p><strong>Description:</strong> The genome sequences of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_TEs_annotation.gff3</p> <p><strong>Description:</strong> The TE annotations of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>Single_reference_87accessions_somatic_variations.vcf</p> <p><strong>Description:</strong> The small somatic variations generated based on the single reference genome (Haplotype A).</p> <p> </p> <p><strong>Filename: </strong>Somatic_material_RNA_seq_matrix.txt</p> <p><strong>Description: </strong>The expression matrix of BT_3 and BT_5 (a set of somatic mutation material).</p> <p><strong>Description:</strong> The genome sequences of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>HaplotypeB_TEs_annotation.gff3</p> <p><strong>Description:</strong> The TE annotations of haplotype B.</p> <p> </p> <p><strong>Filename: </strong>Single_reference_87accessions_somatic_variations.vcf</p> <p><strong>Description:</strong> The small somatic variations generated based on the single reference genome (Haplotype A).</p> <p> </p> <p><strong>Filename: </strong>Somatic_material_RNA_seq_matrix.txt</p> <p><strong>Description: </strong>The expression matrix of BT_3 and BT_5 (a set of somatic mutation material).</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.