SFB genomes and annotations

This dataset contains sequence files for a Metagenome Assembled Genome (MAG) from human metagenomes, as well as 5 SFB reference genomes: GCF_000270205 Candidatus Arthromitus sp. SFB-mouse-Japan GCF_000283555 Candidatus Arthromitus sp. SFB-rat-Yit GCF_000284435 Candidatus Arthromitus sp. SFB-mouse-Yit GCF_000709435 Candidatus Arthromitus sp. SFB-mouse-NL GCF_001655775 Candidatus Arthromitus sp. SFB-turkey isolate UMNCA01 The dataset consists of 8 gzipped tar archives. Here's brief summary of their contents: <strong>sfb_abundance</strong>: Counts of mapped reads and normalized counts for each contig in 825 samples (see <strong>sfb_map</strong>) Files named 'raw_counts' are number of reads assigned to each contig while files named 'tpm' are counts normalized to Transcripts Per Million. The 'percontig' files show numbers per contig while raw_counts.tab and tpm.tab files have counts summed for each genome. <strong>sfb_abundance.cds</strong>: Counts of mapped reads and normalized counts as above but only for reads mapping to protein-coding regions. <strong>sfb_annotations</strong>: Annotation files, from running the prokka pipeline on the genomes and subsequently eggnog-mapper, pfam_scan and dbCAN. <strong>sfb_checkm</strong>: Results from running 'checkm lineage_wf' on the genomes. <strong>sfb_collated</strong>: Collated counts of annotations in each genome. <strong>sfb_fastani</strong>: Results from running fastANI on the genomes, with subsequent clustering of genomes based on 75% overlap and 95% ANI. <strong>sfb_gtdb</strong>: Results from the 'gtdbtk classify_wf' on the genomes. This shows how the genomes are classified against the Genome Taxonomy Database (release86). <strong>sfb_gtdb_denovo</strong>: Phylogeny as created using the following command on the genomes. <pre><code class="language-bash">gtdbtk de_novo_wf --bac120_ms --outgroup_taxon p__Patescibacteria -x .fna --cpus 20 --rnd_seed 123</code></pre> <strong>sfb_map</strong>: Results from mapping reads from 825 samples to the 6 genomes. Reads were aligned using bowtie2 with '--very-sensitive --no-unal' settings and '--score-min C,0,0' to only report reads aligning without mismatches.Output was sorted by position and duplicates removed using MarkDuplicates of the picard tools suite. The archive contains a single merged bam file ('sfb.bam') where each sample has been assigned a ReadGroup inferred from its file name. Note that this mapping step was performed to investigate the presence of the SFB MAG in other metagenomes and was not part of the actual binning step.本数据集包含源自人类宏基因组的宏基因组组装基因组（Metagenome Assembled Genome, MAG）序列文件，以及5株分段丝状菌（Segmented Filamentous Bacteria, SFB）参考基因组，具体如下： GCF_000270205 *Candidatus Arthromitus* sp. SFB-mouse-Japan GCF_000283555 *Candidatus Arthromitus* sp. SFB-rat-Yit GCF_000284435 *Candidatus Arthromitus* sp. SFB-mouse-Yit GCF_000709435 *Candidatus Arthromitus* sp. SFB-mouse-NL GCF_001655775 *Candidatus Arthromitus* sp. SFB-turkey isolate UMNCA01 数据集共包含8个压缩tar归档文件，各归档内容简要说明如下： 1. **sfb_abundance**：涵盖825个样本中各重叠群（contig）的比对读段计数与标准化计数（详见**sfb_map**）。命名为`raw_counts`的文件为分配至各重叠群的读段数量，命名为`tpm`的文件为归一化至每百万转录本（Transcripts Per Million, TPM）的计数。`percontig`文件为各重叠群的单独计数结果，而`raw_counts.tab`与`tpm.tab`文件则为各基因组的汇总计数。 2. **sfb_abundance.cds**：格式与上述一致的比对读段计数与标准化计数，但仅针对比对至蛋白质编码区域的读段。 3. **sfb_annotations**：注释文件，通过对基因组运行prokka分析流程，后续辅以eggnog-mapper、pfam_scan及dbCAN工具完成全流程注释。 4. **sfb_checkm**：对基因组执行`checkm lineage_wf`分析得到的结果。 5. **sfb_collated**：各基因组的注释信息汇总计数结果。 6. **sfb_fastani**：对基因组运行fastANI得到的分析结果，后续基于75%序列重叠度与95%平均核苷酸一致性（Average Nucleotide Identity, ANI）完成基因组聚类。 7. **sfb_gtdb**：对基因组运行`gtdbtk classify_wf`得到的结果，展示了各基因组相对于基因组分类数据库（Genome Taxonomy Database, GTDB）release86版本的分类归属情况。 8. **sfb_gtdb_denovo**：通过如下命令对基因组构建的系统发育树： bash gtdbtk de_novo_wf --bac120_ms --outgroup_taxon p__Patescibacteria -x .fna --cpus 20 --rnd_seed 123 9. **sfb_map**：将825个样本的读段比对至6个基因组得到的结果。读段比对采用bowtie2工具，参数设置为`--very-sensitive --no-unal`与`--score-min C,0,0`，仅保留无错配的比对读段。输出结果按基因组位置排序，并使用picard工具套件的MarkDuplicates去除重复读段。该归档包含单个合并后的BAM文件（`sfb.bam`），其中每个样本的读段组（ReadGroup）根据其文件名推断得到。请注意，该比对步骤旨在探究SFB MAG在其他宏基因组中的存在情况，并非实际分箱（binning）流程的组成部分。