1 项目概述

广州基迪奥生物科技有限公司

2 技术介绍

宏基因组测序是一种利用高通量测序技术完成微生物群落所有物种基因组的检测和功能分析的方法。 宏基因组测序技术无需微生物的分离纯化培养，能够快速有效地获得整个微生物群落的基因信息，可以更加深入地对群落结构、物种分类、系统进化、基因功能及代谢网络等方面进行研究。此类方法不需要对微生物进行分离纯化培养，尤其适用于环境微生物、肠道微生物等样本的研究。

2.1 实验流程

Fig 2-1-1 实验流程图

2.2 分析流程

Fig 2-2-1 信息分析流程图

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3 数据处理

3.1 数据过滤

测序完成之后获得原始数据（raw data）在正常情况下会存在一部分低质量数据，这些低质量数据会影响后续分析结果的准确性。因此我们会根据一定的标准过滤掉低质量数据，从而获得用于后续准确分析的高质量数据（clean data）。
数据过滤的标准如下：

• 去除含adapter的reads；
• 去除N的比例大于10%的reads；
• 去除低质量reads（质量值Q≤20的碱基数占整个read的50％以上）；

Tab 3-1-1 数据过滤统计表

Sample	Rawreads	Cleanreads(%)	Adapter(%)	LowQuality(%)	polyA(%)	N(%)
F-3	68663090	68526930 (99.80%)	30706 (0.04%)	207064 (0.15%)	0 (0.0%)	3844 (0.0%)
F-4	72155062	72003126 (99.79%)	31220 (0.04%)	231280 (0.16%)	0 (0.0%)	10152 (0.01%)
F-5	68876222	68756650 (99.83%)	22020 (0.03%)	191168 (0.14%)	0 (0.0%)	3936 (0.0%)
F-6	70430554	70294040 (99.81%)	35404 (0.05%)	192124 (0.14%)	0 (0.0%)	10096 (0.01%)
G-2	70665654	70529454 (99.81%)	29390 (0.04%)	200644 (0.14%)	0 (0.0%)	12976 (0.01%)
G-4	65631282	65497078 (99.80%)	25712 (0.04%)	213268 (0.16%)	0 (0.0%)	3716 (0.0%)
G-5	66654320	66466480 (99.72%)	32438 (0.05%)	307528 (0.23%)	0 (0.0%)	3276 (0.0%)
G-6	70276890	70103678 (99.75%)	39056 (0.06%)	257332 (0.18%)	0 (0.0%)	10980 (0.01%)

Fig 3-1-1 数据预处理分布图（百分比）		Fig 3-1-2 数据预处理分布图（数值）

3.2 碱基质量分析

数据经过过滤后，我们将分析碱基的组成及质量分布，以直观展示数据质量情况。碱基组成越平衡，质量越高，后续分析则越准确。

Tab 3-2-1 过滤前后碱基信息统计表

Sample	RawData(bp)	BF_Q20(%)	BF_Q30(%)	BF_N(%)	BF_GC(%)	CleanData(bp)	AF_Q20(%)	AF_Q30(%)	AF_N(%)	AF_GC(%)
F-3	10299463500	9993944910 (97.03%)	9465326967 (91.9%)	193188 (0.0%)	5216314828 (50.64%)	10261977261	9964697107 (97.1%)	9439740968 (91.99%)	164746 (0.0%)	5195899500 (50.64%)
F-4	10823259300	10468860149 (96.73%)	9878770979 (91.27%)	323304 (0.0%)	5410541082 (49.99%)	10791132428	10445617444 (96.8%)	9859139775 (91.36%)	172924 (0.0%)	5393133246 (49.98%)
F-5	10331433300	9995149257 (96.75%)	9429336703 (91.27%)	195341 (0.0%)	5320552875 (51.5%)	10301616881	9972739741 (96.81%)	9410164154 (91.35%)	166477 (0.0%)	5304212894 (51.49%)
F-6	10564583100	10230573448 (96.84%)	9666715357 (91.5%)	323923 (0.0%)	5151257722 (48.76%)	10532195019	10207147983 (96.91%)	9646949221 (91.59%)	172239 (0.0%)	5134097258 (48.74%)
G-2	10599848100	10302104514 (97.19%)	9776550923 (92.23%)	380456 (0.0%)	5446545493 (51.38%)	10566414210	10276029120 (97.25%)	9753679888 (92.31%)	172419 (0.0%)	5428627622 (51.38%)
G-4	9844692300	9505992364 (96.56%)	8953934569 (90.95%)	186818 (0.0%)	5066197778 (51.46%)	9812233057	9481993083 (96.63%)	8933606112 (91.05%)	159546 (0.0%)	5048577787 (51.45%)
G-5	9998148000	9654188365 (96.56%)	9095462182 (90.97%)	180539 (0.0%)	5127872541 (51.29%)	9964204920	9630488454 (96.65%)	9075754142 (91.08%)	155924 (0.0%)	5109396306 (51.28%)
G-6	10541533500	10241841278 (97.16%)	9718340579 (92.19%)	338064 (0.0%)	5416351405 (51.38%)	10492366443	10202518463 (97.24%)	9683481247 (92.29%)	170359 (0.0%)	5389651322 (51.37%)

3.3 宿主序列过滤

如果样本采集来源于肠道等微生物，则不可避免的会存在宿主序列污染。如果宿主参考基因组已经发布，我们会将过滤后数据用 Bowtie2 比对到宿主参考基因组，过滤来源于宿主的reads，得到effective reads进行后续分析。
备注：此分析只在样本存在宿主参考的情况下才会开展。

Tab 3-3-1 宿主序列过滤统计表

Samples	F-3	F-4	F-5	F-6	G-2	G-4	G-5	G-6
Sum Clean Reads	68526930	72003126	68756650	70294040	70529454	65497078	66466480	70103678
Sum Host mapped Reads	89355	110297	97751	111396	92941	78777	74682	104773

Fig 3-3-1 宿主序列过滤统计

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4 序列组装

利用 MEGAHIT 软件对effective reads进行组装
结果在文件夹：02.Assemble下

Tab 4-0-1 各样本组装统计结果

Sample	Contigs Num	Total length	Average length	Max length	N50	N90
F	1361185	2184597799	1604.92	619133	2326	645
G	1576316	2206043563	1399.49	331676	1748	616

广州基迪奥生物科技有限公司

5 基因预测

5.1 基因预测

利用 MetaGeneMark 对>500bp的contigs进行基因预测，然后采用 CD-HIT 软件（95% identity、90% coverage）对所预测基因进行聚类，选取最长的基因作为每类代表序列，构建初始非冗余基因集合。

结果在文件夹：03.Genes下

Tab 5-1-1 非冗余基因集样本基因数目统计表

Sample	GeneNumber	TotalLength	AverageLength	GC%
F-3	461162	515203104	1117	53.79%
F-4	537898	580964919	1080	53.63%
F-5	400314	460464543	1150	53.70%
F-6	395609	452996859	1145	53.30%
G-2	388715	427116321	1098	54.20%
G-4	293558	353490087	1204	54.12%
G-5	415056	460258407	1108	54.58%
G-6	567078	576597696	1016	54.10%

使用柱形图展示每个样本的基因数目分布，便于比较样本间基因数量差异。

Fig 5-1-1 各样本基因数目分布

使用小提琴图可直观反映组内样本基因数目分布和组间基因数目的差异。

Fig 5-1-2 分组基因数分布小提琴图

5.2 基因丰度统计

利用 bowtie2 将 clean reads重新比对到初始非冗余基因集上，并基于比对结果，使用pathoscope软件重新将reads分配给最佳基因。（备注：Bowtie比对时可能出现一条reads比对上多个基因，而pathoscope可以基于算法将这些多重比对的reads分配给最佳基因，优化基因定量结果，也是文献认可推荐的方法）。过滤掉在各个样品中reads支持数目≤2的基因，获得最终用于后续分析的基因集合。
从分配给基因的reads 数目、基因长度、测序深度出发，计算得到各基因在各样品中的相对丰度信息。前10行示例如下：

Tab 5-2-1 各样本基因丰度表

GeneID	F-3_count	F-4_count	F-5_count	F-6_count	G-2_count	G-4_count	G-5_count	G-6_count	F-3_RelativeAbundance	F-4_RelativeAbundance	F-5_RelativeAbundance	F-6_RelativeAbundance	G-2_RelativeAbundance	G-4_RelativeAbundance	G-5_RelativeAbundance	G-6_RelativeAbundance
Unigene1	13.0	0	0	0	0	0	0	0	9.038851272516904e-07	0	0	0	0	0	0	0
Unigene4	0	0	0	3.0	0	0	0	16.0	0	0	0	2.527775465885085e-07	0	0	0	1.5335500503915718e-06
Unigene13	0	0	0	283.0	0	0	0	0	0	0	0	1.4873831280945607e-05	0	0	0	0
Unigene14	18.0	0	7.0	0	0	0	0	0	8.871162176510935e-07	0	3.363301974977882e-07	0	0	0	0	0
Unigene16	0	0	3.0	4.0	0	30.0	0	0	0	0	1.8493628110390513e-07	2.4037713864265717e-07	0	2.967263527620739e-06	0	0
Unigene17	11.0	0	0	0	0	0	0	0	8.155886563458923e-07	0	0	0	0	0	0	0
Unigene18	0	15.0	0	0	0	0	0	0	0	1.5778178350403477e-06	0	0	0	0	0	0
Unigene19	0	0	0	28.0	0	0	0	0	0	0	0	3.1181789663085946e-06	0	0	0	0
Unigene20	0	0	0	16.0	0	0	0	4.0	0	0	0	1.6545439413066012e-06	0	0	0	4.705210381883232e-07
Unigene22	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

结果在文件夹：03.Genes

• 基因CDS序列：Unigenes.final.fna
• 基因编码蛋白序列：Unigenes.final.faa
• 基因在各个样本中的丰度：Unigenes.expression.final.xls

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6 基因功能注释

获得非冗余基因集后，我们基于各种数据库比对注释结果分析预测样本中微生物群落的功能特征。将Unigenes通过DIAMOND软件（阈值evalue<=1e-5）比对到KEGG、eggNOG、CAZy、CARD、VFDB、PHI等多个数据库，同时集合基因丰度表格计算不同数据库比对结果的丰度信息，以进行系统丰富的组间功能差异分析和比较。
结果在文件夹：04.Annotation下

Tab 6-0-1 数据库注释统计表

Database	GeneCount	GenePercent(%)
KEGG	1633079	71.92%
eggNOG	1676538	73.83%
CAZy	271550	11.96%
VFDB	203451	8.96%
PHI	231736	10.20%
CARD	63610	2.80%

6.1 KEGG功能注释

KEGG，全称Kyoto Encyclopedia of Genes and Genomes，是一个关于基因功能注释方面的综合性数据库，包括基因的功能、分类、代谢通路（KEGG Pathway数据库， 是KEGG最核心的功能注释数据库）等诸多方面的信息。
KEGG Pathway数据库将生物代谢通路划分为7大类（A级分类，level 1），分别为：新陈代谢（Metabolism）、遗传信息处理（Genetic Information Processing）、 环境信息处理（Environmental Information Processing）、细胞过程（Cellular Processes）、生物体系统（Organismal Systems）、 人类疾病（Human Diseases）、药物相关代谢（Drug developmennt）。每大类又被逐步细分更具体的B、C、D3个层级。目前B级分类（level 2）共有 59个子分类。C级分类（level 3）即为代谢通路图（pathway，map）；D级分类为每个代谢通路图中具体的酶、同源基因、化合物等信息。
我们基于KEGG的层级分类注释结果，可以获得样本/分组间不同深度的功能特征，还可以基于pathway注释信息系统了解群落内基因间的潜在关联、代谢网络等。
Pathway注释信息展示如下：

Tab 6-1-1 Pathway 注释信息

KEGG_A_class	KEGG_B_class	Pathway	Count (453974)	Pathway ID	...
Metabolism	Nucleotide metabolism	Purine metabolism	37930	ko00230	...
Environmental Information Processing	Membrane transport	ABC transporters	33855	ko02010	...
Metabolism	Nucleotide metabolism	Pyrimidine metabolism	33616	ko00240	...
Environmental Information Processing	Signal transduction	Two-component system	27270	ko02020	...
Cellular Processes	Cellular community - prokaryotes	Quorum sensing	24892	ko02024	...
Metabolism	Carbohydrate metabolism	Amino sugar and nucleotide sugar metabolism	24328	ko00520	...
Metabolism	Carbohydrate metabolism	Starch and sucrose metabolism	23047	ko00500	...
Genetic Information Processing	Replication and repair	Homologous recombination	20545	ko03440	...
Genetic Information Processing	Translation	Aminoacyl-tRNA biosynthesis	20316	ko00970	...
Genetic Information Processing	Replication and repair	Mismatch repair	17826	ko03430	...

我们统计所有样本中注释到pathway数据库的基因总数，并绘制条形图，直观展示不同分类层级群落的基因数量分布情况

Fig 6-1-1 所有样本中pathway注释到的基因数目

我们用热图展示各样本中KEGG不同层级的功能丰度特征，直观呈现每个样本的功能丰度信息，以初步呈现样本/分组间功能分布规律。并挑选pathway（所有样本中丰度之和排名前25的pathway）丰度特征展示如下。

Fig 6-1-2 Top 25 pathway Heatmap

6.2 eggNOG功能注释

eggNOG（evolutionary genealogy of genes: Non-supervised Orthologous Groups）数据库是利用 Smith-Waterman 比对算法构建的基因直系同源簇 （Orthologous Groups，Ogs），当前最新版本5.0（2019.01），涵盖了5090个物种（4445个代表性细菌、168个古菌、477个真核生物）、2502个病毒，首先基于所有基因组蛋白信息，聚类获得约4.4M的OGs（C层级），然后基于KEGG等各类数据库进行注释，最终构建成25个功能分类（A层级）。
使用eggNOG数据库基于直系同源（orthology）进行基因、蛋白序列的功能预测被认为比传统的同源搜索更准确，常应用于新基因组、宏基因组等基因集。我们使用Diamond进行eggNOG注释，并以柱形图展示25个功能分类的基因数目统计情况，便于对比群落中各功能分类的基因数量分布。

Tab 6-2-1 eggNOG注释详细信息

GeneID	eggNOG_OG	Best_Description	Best_COG_Cat	F-3	F-4	F-5	F-6	G-2	G-4	G-5	G-6
Unigene1	COG0345;1TP1E;27JFY;247SR	Catalyzes the reduction of 1-pyrroline-5-carboxylate (PCA) to L-proline	E	9.038851272516904e-07	0	0	0	0	0	0	0
Unigene13	COG0577;2FPEN;4NDUK;22X01	ABC transporter permease	V	0	0	0	1.4873831280945607e-05	0	0	0	0
Unigene14	2J5C6;COG0527;COG0460	Amino acid kinase family	E	8.871162176510935e-07	0	3.363301974977882e-07	0	0	0	0	0
Unigene16	COG2217	Heavy metal translocating P-type atpase	P	0	0	1.8493628110390513e-07	2.4037713864265717e-07	0	2.967263527620739e-06	0	0
Unigene17	4E7E2;2GQPQ;COG0681	Peptidase S24-like	U	8.155886563458923e-07	0	0	0	0	0	0	0
Unigene19	1TNYD;247QZ;COG1126;4BXFR	ATPases associated with a variety of cellular activities	E	0	0	0	3.1181789663085946e-06	0	0	0	0
Unigene20	COG3152	Membrane	L	0	0	0	1.6545439413066012e-06	0	0	0	4.705210381883232e-07
Unigene22	1ZBDP;COG0557;1TQ1G;4HBBH	3'-5' exoribonuclease that releases 5'-nucleoside monophosphates and is involved in maturation of structured RNAs	K	0	0	0	0	0	0	0	0
Unigene37	33MU2;24W74;1VQ3S;2DTVE	-	-	0	8.560410042685029e-07	0	0	0	0	0	0
Unigene44	247XY;27J0H;COG0090;1TP9X	One of the primary rRNA binding proteins. Required for association of the 30S and 50S subunits to form the 70S ribosome, for tRNA binding and peptide bond formation. It has been suggested to have peptidyltransferase activity	J	0	0	0	0	0	0	0	0

Fig 6-2-1 eggNOG注释统计图

热图展示总丰度排名前25的Ogs在所有样本中的丰度分布特征，便于初步查看各样本/分组功能分布规律。

Fig 6-2-2 Top 25 eggNOG Family Heatmap

6.3 CAZy功能注释

CAZy 全称Carbohydrate-Active enZYmes Database，是碳水化合物酶相关的专业数据库，包括催化碳水化合物生物合成、降解以及修饰的相关酶系家族，对生物质转化等工业微生物领域、生境内碳循环相关功能研究有重要参考价值。
其包含6个主要分类（level A）：糖苷水解酶（Glycoside Hydrolases, GHs）、糖基转移酶（Glycosyl Transferases, GTs）、多糖裂解酶（Polysaccharide Lyases, PLs）和糖类酯解酶（Carbohydrate Esterases, CEs）、辅助氧化还原酶(Auxiliary Activities , AAs)。此外，还包含与碳水化合物相关的modules（Carbohydrate-Binding Modules，CBMs）。其中每一个大类有可以分类很多小的家族（level B），比如CE1，CE2等等，注释结果中的CE0表示没有小家族分类的结果。
使用 Diamond 将基因序列与数据库比对注释。

Tab 6-3-1 CAZy注释详细信息

LevelA	LevelA_full_name	LevelB	Activities	Count	Genes
AA	Auxiliary Activities	AA0	-	171	Unigene2417013;Unigene4778820;Unigene246502;Unigene833634;Unigene142581;Unigene916912;Unigene3839417;Unigene317618;Unigene4380675;Unigene3067376;Unigene328007;Unigene368754;Unigene691405;Unigene3059373;Unigene4897004;Unigene4894757;Unigene606610;Unigene2468769;Unigene368637;Unigene115203;Unigene1828892;Unigene4209982;Unigene2247671;Unigene1564168;Unigene2820379;Unigene4403997;Unigene2087114;Unigene2034919;Unigene2490462;Unigene725027;Unigene1596940;Unigene3984534;Unigene3301920;Unigene1326868;Unigene3502815;Unigene3567017;Unigene2614586;Unigene1972655;Unigene2070955;Unigene2371071;Unigene4796683;Unigene2806240;Unigene3000077;Unigene134863;Unigene402242;Unigene1316062;Unigene2443483;Unigene843210;Unigene3958112;Unigene143576;Unigene745049;Unigene2650200;Unigene217947;Unigene3306214;Unigene3361296;Unigene2857693;Unigene3611334;Unigene3642107;Unigene1094225;Unigene2700547;Unigene306101;Unigene3019758;Unigene1393796;Unigene1458813;Unigene620060;Unigene1711777;Unigene3638039;Unigene1308691;Unigene1736090;Unigene3243624;Unigene1801610;Unigene4922574;Unigene1421439;Unigene568012;Unigene1168374;Unigene3589332;Unigene2272739;Unigene3389935;Unigene1467990;Unigene4646187;Unigene2206278;Unigene110666;Unigene4753258;Unigene1759591;Unigene682281;Unigene852983;Unigene4944682;Unigene4762264;Unigene1419572;Unigene3638242;Unigene478735;Unigene55173;Unigene4816488;Unigene4090779;Unigene1108793;Unigene210682;Unigene945538;Unigene2842192;Unigene502881;Unigene844310;Unigene2317398;Unigene2761303;Unigene1973477;Unigene67928;Unigene2047526;Unigene4333266;Unigene3034547;Unigene3844637;Unigene2613560;Unigene155801;Unigene1134610;Unigene211071;Unigene4402777;Unigene1715536;Unigene3957792;Unigene4904180;Unigene3424598;Unigene3854360;Unigene4069762;Unigene1235721;Unigene1084220;Unigene4146426;Unigene1579755;Unigene237597;Unigene1711780;Unigene805712;Unigene2975806;Unigene1273474;Unigene4398328;Unigene655064;Unigene3832025;Unigene4803528;Unigene160764;Unigene4288945;Unigene1719210;Unigene49538;Unigene1777645;Unigene972542;Unigene3842619;Unigene101965;Unigene354799;Unigene1737327;Unigene4646331;Unigene546618;Unigene1923986;Unigene3952161;Unigene4730928;Unigene4625935;Unigene3268823;Unigene1552035;Unigene4843696;Unigene4832689;Unigene2073225;Unigene2138771;Unigene3886949;Unigene1899510;Unigene1950996;Unigene1222079;Unigene633048;Unigene4506458;Unigene1905972;Unigene1003257;Unigene4099943;Unigene1480089;Unigene3592139;Unigene1629245;Unigene2529922;Unigene3511261;Unigene3256265;Unigene2244553;Unigene4009537
AA	Auxiliary Activities	AA1	Laccase / p-diphenol:oxygen oxidoreductase / ferroxidase (EC 1.10.3.2); ; ferroxidase (EC 1.10.3.-); Laccase-like multicopper oxidase (EC 1.10.3.-)	1340	Unigene4494904;Unigene2650398;Unigene109960;Unigene1595068;Unigene3387598;Unigene217586;Unigene2379411;Unigene1460983;Unigene2399477;Unigene1911754;Unigene2635994;Unigene387835;Unigene3477056;Unigene2844139;Unigene2832383;Unigene4304991;Unigene4501005;Unigene253985;Unigene1485511;Unigene3336199;Unigene4748107;Unigene1463220;Unigene3480967;Unigene2355287;Unigene3875581;Unigene2434751;Unigene4245199;Unigene4694710;Unigene3551672;Unigene537855;Unigene290631;Unigene4130369;Unigene4299887;Unigene1666324;Unigene362023;Unigene2878761;Unigene4021706;Unigene4329;Unigene2661212;Unigene4402177;Unigene3756402;Unigene3012241;Unigene2251939;Unigene4735655;Unigene665704;Unigene630508;Unigene3744199;Unigene1420447;Unigene1240468;Unigene3693717;Unigene1513208;Unigene3516185;Unigene946701;Unigene2717828;Unigene71417;Unigene3566059;Unigene1090300;Unigene1096005;Unigene3128241;Unigene424910;Unigene2919977;Unigene3095034;Unigene2088920;Unigene2941628;Unigene918055;Unigene28869;Unigene103815;Unigene2114584;Unigene1859574;Unigene820788;Unigene844105;Unigene3627710;Unigene3024214;Unigene4757114;Unigene1170715;Unigene3546555;Unigene206537;Unigene3607501;Unigene4440215;Unigene4339078;Unigene4753594;Unigene3328575;Unigene64371;Unigene1040502;Unigene3024784;Unigene2108827;Unigene4508782;Unigene3376344;Unigene17262;Unigene43688;Unigene1407532;Unigene3075855;Unigene605246;Unigene4167177;Unigene3177563;Unigene1185303;Unigene4356617;Unigene1640118;Unigene4583837;Unigene3739161;Unigene693562;Unigene1865518;Unigene2000996;Unigene4281161;Unigene1022087;Unigene345851;Unigene1319312;Unigene43964;Unigene1077501;Unigene2733004;Unigene3520293;Unigene1833160;Unigene818192;Unigene3602451;Unigene3204235;Unigene527734;Unigene2908343;Unigene4084609;Unigene1299267;Unigene420865;Unigene3771942;Unigene1719151;Unigene2997691;Unigene2644273;Unigene3912460;Unigene2077689;Unigene4867915;Unigene1715527;Unigene2891130;Unigene165010;Unigene2244776;Unigene916966;Unigene365348;Unigene2169862;Unigene3450392;Unigene2374365;Unigene1688345;Unigene4187345;Unigene1074436;Unigene4325804;Unigene4386949;Unigene224901;Unigene2681722;Unigene2101431;Unigene1969778;Unigene1422248;Unigene1141211;Unigene2567;Unigene917747;Unigene2719602;Unigene3484943;Unigene3542843;Unigene2393396;Unigene4696534;Unigene3873544;Unigene1644328;Unigene1000235;Unigene4587059;Unigene144260;Unigene462427;Unigene4905580;Unigene2575532;Unigene4735510;Unigene951591;Unigene3158591;Unigene1417771;Unigene414140;Unigene718315;Unigene1681641;Unigene3857042;Unigene1438598;Unigene4203831;Unigene4078539;Unigene425913;Unigene1465848;Unigene2268451;Unigene2397087;Unigene611685;Unigene1801693;Unigene219604;Unigene4093384;Unigene98047;Unigene1716438;Unigene4581348;Unigene3865184;Unigene2357716;Unigene3938577;Unigene1882215;Unigene2126165;Unigene4298537;Unigene856284;Unigene36001;Unigene923552;Unigene3076166;Unigene2024005;Unigene1495644;Unigene1947136;Unigene1287387;Unigene3019898;Unigene1755033;Unigene614395;Unigene4713268;Unigene2820117;Unigene3636644;Unigene4524447;Unigene4361858;Unigene4696217;Unigene451891;Unigene4298660;Unigene4860877;Unigene651140;Unigene1255863;Unigene2712810;Unigene714021;Unigene3845994;Unigene3131592;Unigene2518195;Unigene2762224;Unigene1022367;Unigene1751303;Unigene3349790;Unigene162163;Unigene3772048;Unigene1251860;Unigene504918;Unigene401732;Unigene3844653;Unigene3698682;Unigene3823752;Unigene2133776;Unigene1504541;Unigene887552;Unigene4676684;Unigene3493152;Unigene2639631;Unigene804994;Unigene1094811;Unigene424265;Unigene2236702;Unigene750014;Unigene1032916;Unigene2681268;Unigene4320963;Unigene1610154;Unigene162102;Unigene251582;Unigene941689;Unigene1389636;Unigene1311935;Unigene2011318;Unigene3331311;Unigene362320;Unigene4368588;Unigene4861482;Unigene3131676;Unigene142038;Unigene1795414;Unigene493342;Unigene1861681;Unigene3312625;Unigene2198750;Unigene3273130;Unigene1978770;Unigene924277;Unigene2746313;Unigene815311;Unigene830616;Unigene1383440;Unigene4481957;Unigene2893464;Unigene3938085;Unigene1269755;Unigene1640174;Unigene1348473;Unigene1447911;Unigene3340297;Unigene1641397;Unigene2617896;Unigene4689720;Unigene1684416;Unigene3885101;Unigene4823704;Unigene3375387;Unigene4328461;Unigene4169828;Unigene67021;Unigene4256362;Unigene3421763;Unigene223354;Unigene1830226;Unigene3533193;Unigene3301845;Unigene1211877;Unigene2548734;Unigene3303257;Unigene367537;Unigene1597642;Unigene950846;Unigene1676102;Unigene1513841;Unigene3708624;Unigene4378966;Unigene1059123;Unigene4356255;Unigene1586407;Unigene2359567;Unigene1951572;Unigene3044161;Unigene2250146;Unigene95412;Unigene3658059;Unigene1228748;Unigene4379429;Unigene1645738;Unigene1885497;Unigene1769428;Unigene714415;Unigene4480579;Unigene1468504;Unigene2830394;Unigene622191;Unigene1917940;Unigene888704;Unigene1438882;Unigene2014981;Unigene36176;Unigene236559;Unigene3671203;Unigene3950955;Unigene3664290;Unigene2059338;Unigene3470916;Unigene2549547;Unigene2330343;Unigene2855193;Unigene388881;Unigene854069;Unigene2307910;Unigene84699;Unigene4429499;Unigene2029958;Unigene579229;Unigene2684387;Unigene2178587;Unigene3643856;Unigene1668409;Unigene1337681;Unigene1143183;Unigene1766290;Unigene44986;Unigene4898273;Unigene1924218;Unigene4615570;Unigene2767628;Unigene1391220;Unigene1902462;Unigene4033752;Unigene3892259;Unigene2390741;Unigene406758;Unigene4366642;Unigene2848650;Unigene2552545;Unigene649892;Unigene4020926;Unigene3121405;Unigene2440875;Unigene3545278;Unigene1460915;Unigene220098;Unigene4627472;Unigene4623163;Unigene9928;Unigene4720271;Unigene468346;Unigene351273;Unigene4381241;Unigene3042600;Unigene1281628;Unigene257619;Unigene4655016;Unigene1249286;Unigene1400459;Unigene3472994;Unigene4861967;Unigene2470552;Unigene2336487;Unigene1743558;Unigene3485227;Unigene1162792;Unigene3713726;Unigene4184712;Unigene3807377;Unigene4250812;Unigene1032209;Unigene2077515;Unigene1004853;Unigene409637;Unigene1291803;Unigene1814817;Unigene1417356;Unigene2577855;Unigene969632;Unigene2470553;Unigene3132922;Unigene78553;Unigene4648040;Unigene1611681;Unigene1803224;Unigene4521959;Unigene1499675;Unigene3281435;Unigene2364774;Unigene1927204;Unigene3271890;Unigene1821620;Unigene211492;Unigene557363;Unigene625100;Unigene492167;Unigene1216422;Unigene4609894;Unigene1636045;Unigene267294;Unigene893019;Unigene1398429;Unigene2287559;Unigene1036964;Unigene824976;Unigene1138136;Unigene1732625;Unigene3157136;Unigene839119;Unigene482126;Unigene1686774;Unigene1122936;Unigene1107978;Unigene1952314;Unigene2411400;Unigene4793831;Unigene493691;Unigene2115978;Unigene3430496;Unigene2032201;Unigene4851219;Unigene1567800;Unigene2864782;Unigene2946008;Unigene357362;Unigene3414649;Unigene3480995;Unigene4824505;Unigene4306201;Unigene4536023;Unigene4347616;Unigene4886766;Unigene443213;Unigene1076343;Unigene1132352;Unigene2733460;Unigene997751;Unigene1161707;Unigene430867;Unigene4701663;Unigene783745;Unigene3253741;Unigene133197;Unigene904536;Unigene3259877;Unigene242529;Unigene3922870;Unigene2392676;Unigene612457;Unigene1291802;Unigene2756384;Unigene1640623;Unigene2734935;Unigene1661982;Unigene626345;Unigene4745282;Unigene434563;Unigene4843078;Unigene3467891;Unigene4523805;Unigene1473355;Unigene3751955;Unigene159742;Unigene221011;Unigene3777474;Unigene2299460;Unigene2910618;Unigene2771419;Unigene742441;Unigene3423909;Unigene1624762;Unigene2670060;Unigene2181951;Unigene2053668;Unigene3883520;Unigene4533354;Unigene1552206;Unigene823040;Unigene3527005;Unigene3959054;Unigene1861876;Unigene792235;Unigene2667938;Unigene428944;Unigene954283;Unigene991585;Unigene2893556;Unigene532228;Unigene2634557;Unigene1200177;Unigene1481250;Unigene2610286;Unigene4144897;Unigene894786;Unigene1395655;Unigene72699;Unigene4580359;Unigene3640040;Unigene3462357;Unigene4134628;Unigene2572142;Unigene1774260;Unigene3415882;Unigene1303318;Unigene177756;Unigene2525807;Unigene1680243;Unigene2753570;Unigene1097573;Unigene432307;Unigene2183146;Unigene4484146;Unigene3524616;Unigene1133843;Unigene2505068;Unigene1995802;Unigene472007;Unigene2561519;Unigene814363;Unigene1220869;Unigene85279;Unigene694436;Unigene671037;Unigene4057058;Unigene2289363;Unigene619357;Unigene1602887;Unigene114478;Unigene2398323;Unigene1734389;Unigene2454448;Unigene1103047;Unigene243700;Unigene958863;Unigene1135706;Unigene4433188;Unigene1205610;Unigene4183763;Unigene4743316;Unigene3208088;Unigene1474856;Unigene1078041;Unigene252882;Unigene764206;Unigene3922528;Unigene2301184;Unigene980074;Unigene1000715;Unigene4137455;Unigene3998619;Unigene3150753;Unigene602755;Unigene2424176;Unigene173692;Unigene1516304;Unigene450647;Unigene3185093;Unigene3848465;Unigene505368;Unigene3879214;Unigene1625690;Unigene3461210;Unigene3615446;Unigene2996198;Unigene3978482;Unigene3231464;Unigene521236;Unigene4284940;Unigene4384366;Unigene3389736;Unigene1676089;Unigene2756655;Unigene659105;Unigene788130;Unigene1953827;Unigene3589907;Unigene4468484;Unigene103929;Unigene510551;Unigene3171832;Unigene1120605;Unigene932410;Unigene353062;Unigene742847;Unigene154442;Unigene4218582;Unigene2488976;Unigene81333;Unigene1081146;Unigene3669187;Unigene4818030;Unigene4844723;Unigene4837529;Unigene276586;Unigene299880;Unigene2898531;Unigene2652495;Unigene2752868;Unigene4506942;Unigene2360847;Unigene4192350;Unigene289661;Unigene2186638;Unigene2779521;Unigene3130928;Unigene28790;Unigene2826241;Unigene3505727;Unigene4700448;Unigene26062;Unigene4102988;Unigene4696535;Unigene315006;Unigene4263476;Unigene1454960;Unigene4490095;Unigene4158115;Unigene506021;Unigene376399;Unigene3848532;Unigene674661;Unigene2653475;Unigene394425;Unigene4011097;Unigene959319;Unigene1366988;Unigene4757884;Unigene3882932;Unigene117447;Unigene1111635;Unigene2009138;Unigene4348144;Unigene3803817;Unigene4342015;Unigene380430;Unigene1485837;Unigene2523260;Unigene1196218;Unigene2944468;Unigene4332572;Unigene4121824;Unigene3738883;Unigene4417577;Unigene3143542;Unigene3997978;Unigene3795173;Unigene1506349;Unigene3623877;Unigene2698506;Unigene4643203;Unigene485323;Unigene3021038;Unigene796182;Unigene3500573;Unigene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e126415;Unigene485821;Unigene3823109;Unigene1633994;Unigene2760748;Unigene422493;Unigene504018;Unigene2150907;Unigene3833570;Unigene2940897;Unigene2212613;Unigene1618498;Unigene2864619;Unigene2081004;Unigene1796300;Unigene3879515;Unigene4586273;Unigene4405848;Unigene205129;Unigene447409;Unigene1981395;Unigene221522;Unigene3968386;Unigene2092197;Unigene1966356;Unigene1374533;Unigene3174798;Unigene2848100;Unigene428513;Unigene973633;Unigene4004811;Unigene1408670;Unigene2389797;Unigene788157;Unigene1793317;Unigene3689250;Unigene583071;Unigene250181;Unigene1404700;Unigene72121;Unigene2394133;Unigene336114;Unigene3367151;Unigene3150305;Unigene1413638;Unigene287166;Unigene2388991;Unigene997142;Unigene3535736;Unigene4013531;Unigene3800374;Unigene1494181;Unigene780787;Unigene1271708;Unigene4031264;Unigene2981866;Unigene910829;Unigene581746;Unigene2920935;Unigene2657944;Unigene254563;Unigene3407910;Unigene2528951;Unigene623282;Unigene4110642;Unigene4876763;Unigene2871106;Unigene1596799;Unigene4911220;Unigene1789444;Unigene4090377;Unigene3940573;Unigene839049;Unigene1494115;Unigene1861879;Unigene314108;Unigene1671599;Unigene345355;Unigene837317;Unigene2062465;Unigene2801521;Unigene4363218;Unigene3351866;Unigene2960553;Unigene253467;Unigene563904;Unigene2057916;Unigene3722730;Unigene1228356;Unigene669631;Unigene1136327;Unigene3018346;Unigene3382991;Unigene363806;Unigene3415331;Unigene454802;Unigene51950;Unigene1949115;Unigene2081633;Unigene1804221;Unigene3891922;Unigene429830;Unigene111165;Unigene1773932;Unigene711659;Unigene415847;Unigene3138044;Unigene69658;Unigene2023211;Unigene3835438;Unigene2975542;Unigene2067403;Unigene566867;Unigene1506273;Unigene4686153;Unigene247539;Unigene4242775;Unigene1285650;Unigene4432875;Unigene2184960;Unigene1178268;Unigene2174265;Unigene2845083;Unigene2819996;Unigene2473041;Unigene3716331;Unigene4118631;Unigene3664697;Unigene1034570;Unigene4348319;Unigene4312214;Unigene1383444;Unigene4190220;Unigene2845148;Unigene671929;Unigene4028516;Unigene1538378;Unigene3859139;Unigene555704;Unigene3678244;Unigene91882;Unigene1207560;Unigene1226936;Unigene1903992;Unigene1657715;Unigene4166393;Unigene3227396;Unigene3477931;Unigene619544;Unigene2178090;Unigene4312242;Unigene1129612;Unigene3721642;Unigene2544650;Unigene283282;Unigene915421;Unigene2007586;Unigene202684;Unigene3341580;Unigene4789770;Unigene3131865;Unigene1297666;Unigene2351173;Unigene853527;Unigene1366460;Unigene2069227;Unigene222196;Unigene4395525;Unigene4311697;Unigene62968;Unigene4231180;Unigene2981470;Unigene2170890;Unigene883917;Unigene887841;Unigene1463700;Unigene1791573;Unigene2099664;Unigene3701193;Unigene4636747;Unigene2142867;Unigene2013625;Unigene2874394;Unigene3364564;Unigene4738867;Unigene6885;Unigene3110948;Unigene3870923;Unigene1042836;Unigene3688351;Unigene3523975;Unigene3658858;Unigene1445454;Unigene279069;Unigene2339472;Unigene4429631;Unigene4293687;Unigene1903378;Unigene1228930;Unigene4261481;Unigene2901605;Unigene2298298;Unigene4785059;Unigene4198945;Unigene1869423;Unigene4112893;Unigene2609055;Unigene3793358;Unigene3628561;Unigene2203859;Unigene1938000;Unigene3360716;Unigene1842588;Unigene3457925;Unigene1849653;Unigene860726;Unigene876431;Unigene2540178;Unigene570460;Unigene3836337;Unigene3807730;Unigene3642119;Unigene1529760;Unigene3522997;Unigene4395311;Unigene198023;Unigene47001;Unigene342940;Unigene4944210;Unigene3319182;Unigene1643296;Unigene3143463;Unigene2738315;Unigene1906926;Unigene1439313;Unigene708919;Unigene2454376;Unigene4864156;Unigene2523372;Unigene4318508;Unigene2710439;Unigene242280;Unigene4315984;Unigene2346839;Unigene1464226;Unigene474414;Unigene4112712;Unigene1616068;Unigene556107;Unigene4208557;Unigene2866424;Unigene4058637;Unigene2897332;Unigene4013267;Unigene4951424;Unigene1003852;Unigene3506056;Unigene854188;Unigene3094156;Unigene950694;Unigene3270791;Unigene1845879;Unigene1573923;Unigene4416;Unigene3275922;Unigene281042;Unigene504626;Unigene2547916;Unigene4474511;Unigene29874;Unigene3085250;Unigene201211;Unigene4005307;Unigene4102962;Unigene384078;Unigene3517621;Unigene4928205;Unigene2793154;Unigene497624;Unigene1829840;Unigene577032;Unigene727327;Unigene3840135;Unigene2703506;Unigene1427567;Unigene958330;Unigene553988;Unigene4345302;Unigene512589;Unigene4830231;Unigene277008;Unigene2101138;Unigene3121571;Unigene4514466;Unigene4307560;Unigene865751;Unigene3985416;Unigene49029;Unigene426667;Unigene4354941;Unigene3005265;Unigene338312;Unigene4304153;Unigene23176;Unigene3914984;Unigene2735015;Unigene4948848;Unigene2111492;Unigene2802200;Unigene2170222;Unigene393943;Unigene558060;Unigene2070108;Unigene3450105;Unigene1454807;Unigene2042078;Unigene3742609;Unigene2643253;Unigene878239;Unigene4285699;Unigene267635;Unigene838685;Unigene401530;Unigene657391
AA	Auxiliary Activities	AA10	AA10 (formerly CBM33) proteins are copper-dependent lytic polysaccharide monooxygenases (LPMOs); some proteins have been shown to act on chitin, others on cellulose; lytic cellulose monooxygenase (C1-hydroxylating) (EC 1.14.99.54); lytic cellulose monooxygenase (C4-dehydrogenating)(EC 1.14.99.56); lytic chitin monooxygenase (EC 1.14.99.53)	80	Unigene1336444;Unigene2779114;Unigene615694;Unigene4789776;Unigene3971533;Unigene1428158;Unigene3127938;Unigene1619422;Unigene210738;Unigene4365491;Unigene114648;Unigene2538497;Unigene4202712;Unigene2183136;Unigene3789908;Unigene487979;Unigene547741;Unigene219971;Unigene1061865;Unigene4756387;Unigene470419;Unigene3702929;Unigene2253288;Unigene2859609;Unigene1244518;Unigene3453626;Unigene3521786;Unigene729878;Unigene3225703;Unigene4356596;Unigene4830395;Unigene4145028;Unigene2259250;Unigene973514;Unigene4710403;Unigene1431077;Unigene719247;Unigene283936;Unigene1412707;Unigene1531288;Unigene3996556;Unigene3218378;Unigene4083558;Unigene1342273;Unigene112211;Unigene1319088;Unigene3670255;Unigene1645165;Unigene3831428;Unigene3174080;Unigene3812608;Unigene2025798;Unigene1924441;Unigene3534355;Unigene4546245;Unigene2659199;Unigene3359250;Unigene2986791;Unigene276214;Unigene1301416;Unigene4830396;Unigene1882924;Unigene991308;Unigene4106892;Unigene56176;Unigene3446134;Unigene4555996;Unigene1556710;Unigene2785304;Unigene3759124;Unigene2986728;Unigene817611;Unigene1140905;Unigene4305080;Unigene3037987;Unigene714729;Unigene352088;Unigene3527243;Unigene3326466;Unigene411142
AA	Auxiliary Activities	AA3	cellobiose dehydrogenase (EC 1.1.99.18); glucose 1-oxidase (EC 1.1.3.4); aryl alcohol oxidase (EC 1.1.3.7); alcohol oxidase (EC 1.1.3.13); pyranose oxidase (EC 1.1.3.10)	14	Unigene3887080;Unigene4031013;Unigene614775;Unigene3367347;Unigene1545151;Unigene16187;Unigene113985;Unigene3295999;Unigene3150810;Unigene3364816;Unigene2140525;Unigene253144;Unigene4770530;Unigene3693298
AA	Auxiliary Activities	AA4	vanillyl-alcohol oxidase (EC 1.1.3.38)	132	Unigene1657095;Unigene1984421;Unigene1322280;Unigene657828;Unigene461217;Unigene2732914;Unigene2195235;Unigene1556358;Unigene79372;Unigene2410796;Unigene4278904;Unigene1481962;Unigene175410;Unigene4879639;Unigene110715;Unigene190021;Unigene2110170;Unigene726874;Unigene2020114;Unigene4052204;Unigene1000261;Unigene1240705;Unigene2732911;Unigene2319642;Unigene1526785;Unigene2000594;Unigene379656;Unigene857619;Unigene957920;Unigene4618211;Unigene499107;Unigene717069;Unigene225700;Unigene133697;Unigene1603421;Unigene1945118;Unigene399925;Unigene3694344;Unigene556231;Unigene1230816;Unigene1406920;Unigene450036;Unigene1406919;Unigene1913662;Unigene3874950;Unigene4385032;Unigene1756537;Unigene1084029;Unigene4438520;Unigene2206424;Unigene4625490;Unigene1943455;Unigene1934765;Unigene3004728;Unigene1871934;Unigene1793535;Unigene304691;Unigene145441;Unigene529818;Unigene1077196;Unigene3591195;Unigene4168305;Unigene555198;Unigene2023782;Unigene910630;Unigene3496129;Unigene2576373;Unigene152662;Unigene4627776;Unigene147356;Unigene430294;Unigene4879058;Unigene40465;Unigene4783104;Unigene1018801;Unigene3308616;Unigene918060;Unigene82972;Unigene2597394;Unigene4785801;Unigene712417;Unigene880324;Unigene2229020;Unigene163512;Unigene2166383;Unigene3143947;Unigene2536265;Unigene2322099;Unigene2714573;Unigene4346401;Unigene850791;Unigene3308618;Unigene4440799;Unigene4470421;Unigene258530;Unigene4219798;Unigene1735067;Unigene122884;Unigene2400788;Unigene4889315;Unigene2732913;Unigene2173423;Unigene2884478;Unigene866729;Unigene1140060;Unigene2624535;Unigene3496130;Unigene3963384;Unigene1210375;Unigene699691;Unigene1350254;Unigene190019;Unigene1894368;Unigene853204;Unigene1589628;Unigene1140439;Unigene632994;Unigene1459196;Unigene898298;Unigene331196;Unigene811611;Unigene4271816;Unigene943547;Unigene2273879;Unigene4107084;Unigene2195243;Unigene4440797;Unigene1630271;Unigene518231;Unigene290530;Unigene177274;Unigene2365540
AA	Auxiliary Activities	AA5	Oxidase with oxygen as acceptor (EC 1.1.3.-); galactose oxidase (EC 1.1.3.9); glyoxal oxidase (EC 1.2.3.15); alcohol oxidase (EC 1.1.3.13)	118	Unigene1319503;Unigene908048;Unigene144854;Unigene4452840;Unigene455511;Unigene1305525;Unigene2554893;Unigene1155881;Unigene722667;Unigene1657919;Unigene1377059;Unigene31302;Unigene2883062;Unigene4594998;Unigene2242292;Unigene164000;Unigene279800;Unigene3621983;Unigene4060887;Unigene4181118;Unigene1935169;Unigene4092916;Unigene638549;Unigene4924052;Unigene2583032;Unigene2728443;Unigene1833627;Unigene4384257;Unigene1468652;Unigene2568943;Unigene628989;Unigene3433055;Unigene3869597;Unigene1905175;Unigene1442848;Unigene836127;Unigene2897736;Unigene668966;Unigene51348;Unigene2804513;Unigene41203;Unigene67006;Unigene2309433;Unigene1772253;Unigene1695644;Unigene132987;Unigene1225370;Unigene3178383;Unigene1975840;Unigene809052;Unigene2476453;Unigene657085;Unigene576994;Unigene768466;Unigene1120178;Unigene2740603;Unigene1124894;Unigene2232523;Unigene799301;Unigene1581420;Unigene4533775;Unigene822461;Unigene3101130;Unigene1665450;Unigene2627624;Unigene1724450;Unigene263074;Unigene918901;Unigene4680561;Unigene8314;Unigene1129241;Unigene530183;Unigene339947;Unigene2848975;Unigene524103;Unigene4502841;Unigene3025468;Unigene256250;Unigene2404723;Unigene1121810;Unigene946136;Unigene1500512;Unigene1503664;Unigene4746890;Unigene1632698;Unigene1124343;Unigene2416854;Unigene540238;Unigene2756887;Unigene772242;Unigene3725579;Unigene954009;Unigene652287;Unigene2069311;Unigene3280879;Unigene616941;Unigene329471;Unigene1167525;Unigene1115709;Unigene290940;Unigene1621559;Unigene327457;Unigene1241855;Unigene92789;Unigene1685388;Unigene1292986;Unigene2914626;Unigene2465691;Unigene1467423;Unigene3495275;Unigene1110342;Unigene547451;Unigene1486382;Unigene2612236;Unigene1759878;Unigene2235522;Unigene189029;Unigene2253928
AA	Auxiliary Activities	AA6	1,4-benzoquinone reductase (EC. 1.6.5.6)	4	Unigene3560931;Unigene304629;Unigene1271565;Unigene615123
AA	Auxiliary Activities	AA7	glucooligosaccharide oxidase (EC 1.1.3.-); chitooligosaccharide oxidase (EC 1.1.3.-)	11	Unigene2001300;Unigene3297112;Unigene12290;Unigene742898;Unigene2695095;Unigene2886105;Unigene110715;Unigene251846;Unigene3416721;Unigene285326;Unigene843749
AA	Auxiliary Activities	AA8	Iron reductase domain	1	Unigene253144
AA	Auxiliary Activities	AA9	AA9 (formerly GH61) proteins are copper-dependent lytic polysaccharide monooxygenases (LPMOs); cleavage of cellulose chains with oxidation of carbons C1 and/or C4 and C-6); lytic cellulose monooxygenase (C1-hydroxylating) (EC 1.14.99.54); lytic cellulose monooxygenase (C4-dehydrogenating) (EC 1.14.99.56)	3	Unigene74575;Unigene3577271;Unigene1041337

使用柱形图展示每个功能分类的基因数目，便于对比微生物群体中各功能分类的基因数量分布情况。

Fig 6-3-1 CAZy注释统计图

我们使用circos软件绘制circos图展示每个功能分类的丰度分布，便于了解各样本功能分布规律。

Fig 6-3-2 CAZy功能分布circos图

6.4 CARD注释

微生物抗性及毒性基因的研究，是微生物研究中极具应用价值和实际应用意义的一项研究，目前我们常用的方法大多是依赖相关抗性毒性基因数据库进行分析。
CARD（Comprehensive Antibiotic Resistance Database）以Antibiotic Resistance Ontology（ARO）为分类单位（term）构建，用于关联抗生素模块及其目标、抗性机制、基因变异等信息。通过该数据库的注释，可以找到耐药性相关基因的名称，所耐受的抗生素种类等信息。
我们使用 Diamond 将预测基因序列比对至数据库进行注释

Tab 6-4-1 CARD注释表

GeneID	ARO_Name	ARO_Accession	AMR_Gene_Family	Drug_Class	Resistance_Mechanism	F-3	F-4	F-5	F-6	G-2	G-4	G-5	G-6
Unigene60	YojI	ARO:3003952	ATP-binding cassette (ABC) antibiotic efflux pump	peptide antibiotic	antibiotic efflux	3.556833891525611e-07	3.192848354869383e-07	3.85283918966469e-07	0	0	0	1.222359715024187e-07	0
Unigene148	TaeA	ARO:3003986	ATP-binding cassette (ABC) antibiotic efflux pump	pleuromutilin antibiotic	antibiotic efflux	0	5.455598110104968e-07	0	0	0	0	0	0
Unigene219	tetA(58)	ARO:3003980	major facilitator superfamily (MFS) antibiotic efflux pump	tetracycline antibiotic	antibiotic efflux	0	1.7589275704065382e-06	0	0	0	0	0	0
Unigene413	vanSF	ARO:3002936	glycopeptide resistance gene cluster;vanS	glycopeptide antibiotic	antibiotic target alteration	7.479896509593455e-06	0	0	0	0	0	0	0
Unigene414	vanRF	ARO:3002925	glycopeptide resistance gene cluster;vanR	glycopeptide antibiotic	antibiotic target alteration	6.132217069531436e-06	0	0	0	0	0	0	0
Unigene433	Streptomyces rishiriensis parY mutant conferring resistance to aminocoumarin	ARO:3003318	aminocoumarin resistant parY	aminocoumarin antibiotic	antibiotic target alteration	1.7962707146585014e-07	8.522954737313404e-07	0	0	0	0	0	3.46766079062987e-06
Unigene483	vanG	ARO:3002909	glycopeptide resistance gene cluster;van ligase	glycopeptide antibiotic	antibiotic target alteration	1.7835037269058013e-06	0	0	0	4.1285748068600216e-07	0	0	0
Unigene712	vanSE	ARO:3002935	glycopeptide resistance gene cluster;vanS	glycopeptide antibiotic	antibiotic target alteration	6.488473254415475e-06	5.296696246067359e-06	6.960216761679971e-06	3.0931989253593805e-06	0	5.255303825025871e-07	3.247371673999093e-07	0
Unigene792	bcrA	ARO:3002987	ATP-binding cassette (ABC) antibiotic efflux pump	peptide antibiotic	antibiotic efflux	1.7200524161226133e-06	0	0	0	0	0	0	0
Unigene793	bcrA	ARO:3002987	ATP-binding cassette (ABC) antibiotic efflux pump	peptide antibiotic	antibiotic efflux	2.992257083346942e-06	0	0	0	0	0	0	0

我们使用circos软件绘制circos图展现丰度排名前10的ARO功能分布规律，便于初步比较样本间抗性基因功能分布差异等信息。

Fig 6-4-1 CARD注释Circos图

6.5 VFDB注释

VFDB，Virulence Factors of Pathogenic Bacteria，毒力因子数据库，由中国医学科学院研发，收集整理了重要医学病原菌中74个属951个菌株的1080个已知毒力因子的组成、结构、功能、致病机理、毒力岛、序列和基因组信息等内容。毒力因子数据库能够为病原菌的入侵机理研究提供关键证据，可以研究群落中不同病原菌的毒力因子构成等特征，被广泛应用于毒力因子基因鉴定。
我们使用 Diamond 与数据库进行比对注释

Tab 6-5-1 VFDB注释表

GeneID	Subject	Description	Organism	VFs	VF_FullName	Function	VFID	F-3	F-4	F-5	F-6	G-2	G-4	G-5	G-6
Unigene1	VFG022639(gi:333989135)	(proC) pyrroline-5-carboxylate reductase ProC [Proline synthesis (CVF307)] [Mycobacterium sp. JDM601]	-	-	-	-	-	9.038851272516904e-07	0	0	0	0	0	0	0
Unigene16	VFG031407(gi:433630073)	(ctpV) Putative metal cation transporter P-type ATPase CtpV [Copper exporter (CVF658)] [Mycobacterium canettii CIPT 140070010]	-	-	-	-	-	0	0	1.8493628110390513e-07	2.4037713864265717e-07	0	2.967263527620739e-06	0	0
Unigene60	VFG044172(gb|NP_756180)	(chuV) ATP-binding hydrophilic protein ChuV [Chu (VF0227)] [Escherichia coli CFT073]	Escherichia coli (UPEC)	Chu	E. coli hemin uptake	Iron uptake: the ability to use heme and/or hemoglobin might be especially advantageous to pathogenic bacteria. These pathogens often secrete cytotoxins, which gain access to the intracellular heme reservoir besides initiating tissue invasion. Cytotoxin production coupled with the capability to utilize heme and/or hemoglobin could serve as an effective iron acquisition strategy during the progression of infection	VF0227	3.556833891525611e-07	3.192848354869383e-07	3.85283918966469e-07	0	0	0	1.222359715024187e-07	0
Unigene144	VFG031084(gi:433644988)	(zmp1) endothelin-converting enzyme [Zn++ metallophrotease (CVF655)] [Mycobacterium smegmatis JS623]	-	-	-	-	-	2.4816795455809075e-05	2.1444175455707123e-05	1.8403891096352753e-05	1.0683850988088986e-05	3.628834343687883e-05	6.83472219294583e-05	9.362398618977449e-05	2.465023983293573e-06
Unigene148	VFG007913(gi:145223975)	(ddrA) daunorubicin resistance ABC transporter ATPase subunit [PDIM (phthiocerol dimycocerosate) and PGL (phenolic glycolipid) biosynthesis and transport (CVF288)] [Mycobacterium gilvum PYR-GCK]	-	-	-	-	-	0	5.455598110104968e-07	0	0	0	0	0	0
Unigene171	VFG014970(gi:148545464)	(algR) two component transcriptional regulator, LytTR family [Alginate regulation (CVF523)] [Pseudomonas putida F1]	-	-	-	-	-	0	2.6159762366466053e-07	0	3.461953355451312e-07	0	0	0	0
Unigene211	VFG009927(gi:118617353)	(relA) GTP pyrophosphokinase RelA [(p)ppGpp synthesis and hydrolysis (CVF335)] [Mycobacterium ulcerans Agy99]	-	-	-	-	-	0	1.8113238601911703e-06	0	0	0	0	0	0
Unigene219	VFG044173(gi:28901507)	(pvuE) iron-dicitrate transporter ATP-binding subunit [vibrioferrin (IA038)] [Vibrio parahaemolyticus RIMD 2210633]	-	-	-	-	-	0	1.7589275704065382e-06	0	0	0	0	0	0
Unigene236	VFG037640(gi:169794956)	(bap) hypothetical protein [Biofilm-associated protein (CVF771)] [Acinetobacter baumannii AYE]	-	-	-	-	-	5.098870247118811e-06	0	0	0	0	0	0	0
Unigene253	VFG016390(gi:42784429)	(BCE_5384) NAD dependent epimerase/dehydratase family protein [Polysaccharide capsule (CVF567)] [Bacillus cereus ATCC 10987]	-	-	-	-	-	1.4613348546578092e-07	2.6235808187298805e-07	0	0	0	0	0	0

我们挑选丰度排名前10的毒力因子，以热图展示其在各样本间的分布规律：

Fig 6-5-1 毒力因子丰度热图

6.6 PHI注释

PHI-base（Pathogen Host Interactions），病原宿主互作数据库，是一个免费开放的数据库，收录了经过实验验证或文献报道的能够感染植物、动物、真菌和昆虫的真菌、卵菌、细菌等病原菌的致病基因、毒力基因和效应蛋白基因。另外，数据库还收录了抗真菌化合物及其靶基因。
最新版本为4.6，共收录6438个基因、11340对互作关系、263个病原菌、194个宿主、510种疾病。数据库包含核酸序列、蛋白序列、功能注释、其他外部数据库（NCBI taxonomy）的注释信息。
我们使用 Diamond 与数据库进行比对注释

Tab 6-6-1 PHI注释表

GeneID	Subject	PHI-baseAccession	GeneName	Pathogen_NCBI_Taxonomy_ID	PathogenSpecies	Disease	HostDescription	Host_NCBI_Taxonomy_ID	HostSpecies	Phenotype	GeneFunction	F-3	F-4	F-5	F-6	G-2	G-4	G-5	G-6
Unigene16	A0A0D5YKF1	PHI:8812|PHI:8812	CopA (ABUW_2707)|CopA (ABUW_2707)	-|-	Acinetobacter baumannii|Acinetobacter baumannii	Nosocomial infections|Nosocomial infections	Rodents|Rodents	10090|10090	Mus musculus (related: house mouse)|Mus musculus (related: house mouse)	unaffected pathogenicity|reduced virulence	Copper-translocating P-type ATPase|Copper-translocating P-type ATPase	0	0	1.8493628110390513e-07	2.4037713864265717e-07	0	2.967263527620739e-06	0	0
Unigene44	I1RCH5	PHI:1569	GzOB009	449239	Fusarium graminearum	Fusarium ear blight	Monocots	4564	Triticum (related: wheat)	lethal	transcription factor	0	0	0	0	0	0	0	0
Unigene51	Q5KN74	PHI:7207	msh2	-	Cryptococcus neoformans	Fungal meningitis	Rodents	10090	Mus musculus (related: house mouse)	unaffected pathogenicity	DNA mismatch repair protein	5.625020382828881e-07	0	0	1.9695211668821954e-07	0	4.630888308713168e-07	0	0
Unigene60	Q8ZQE4	PHI:3928	MacB	1299114	Salmonella enterica	Food poisoning; enteritis	Rodents	10090	Mus musculus (related: house mouse)	reduced virulence	ABC-Type Efflux Pump	3.556833891525611e-07	3.192848354869383e-07	3.85283918966469e-07	0	0	0	1.222359715024187e-07	0
Unigene63	A6QHK8	PHI:3004	ClpX	93061	Staphylococcus aureus	Skin infections; food poisoning; respiratory diseases	Rodents	10090	Mus musculus (related: house mouse)	reduced virulence	Part of proteolytic complex	9.383718213376012e-07	0	1.7425107375123505e-07	4.246662782686943e-07	0	0	0	0
Unigene68	Q839C1	PHI:4139|PHI:4139	ldh-1|ldh-1	226185|226185	Enterococcus faecalis|Enterococcus faecalis	Nosocomial infections|Nosocomial infections	Rodents|Rodents	10090|10090	Mus musculus (related: house mouse)|Mus musculus (related: house mouse)	unaffected pathogenicity|reduced virulence	Redox Balance|Redox Balance	0	0	4.415145449777915e-07	0	0	0	0	0
Unigene144	Q8DNW9	PHI:6096	PepO	373153	Streptococcus pneumoniae	Pneumococcal pneumonia	Rodents	10090	Mus musculus (related: house mouse)	increased virulence (hypervirulence)	Endopeptidase	2.4816795455809075e-05	2.1444175455707123e-05	1.8403891096352753e-05	1.0683850988088986e-05	3.628834343687883e-05	6.83472219294583e-05	9.362398618977449e-05	2.465023983293573e-06
Unigene148	G4NDE1	PHI:1017|PHI:2067	ABC4|ABC4	-|-	Magnaporthe oryzae|Magnaporthe oryzae	Rice blast|Rice blast	Monocots|Monocots	4513|4513	Hordeum vulgare (related: barley)|Hordeum vulgare (related: barley)	reduced virulence|loss of pathogenicity	ABC Transporter|multidrug resistance	0	5.455598110104968e-07	0	0	0	0	0	0
Unigene154	Q882L6	PHI:3350	bifA	223283	Pseudomonas syringae	Bacterial speck	Eudicots	4081	Solanum lycopersicum (related: tomato)	reduced virulence	c-di-GMP phosphodiesterase	0	5.228455178859191e-07	0	0	0	0	0	0
Unigene171	A4VXN7	PHI:6897	1910RR (ssu05 1910)	391295	Streptococcus suis	Meningitis	Even-toed ungulates	9823	Sus scrofa (related: pig)	reduced virulence	virulence related two-component system	0	2.6159762366466053e-07	0	3.461953355451312e-07	0	0	0	0

Tab 6-6-2 PHI 数据库表型信息统计

Phenotype Classificatin	chemistry target: resistance to chemical	chemistry target: sensitivity to chemical	effector (plant avirulence determinant)	increased virulence (hypervirulence)	lethal	loss of pathogenicity	reduced virulence	unaffected pathogenicity
Num	8	9	42	195	60	188	1359	634

Fig 6-6-1 表型分类统计柱形图

广州基迪奥生物科技有限公司

7 物种组成分析

除了丰富特色的功能分析，宏基因组的另一大特色就是将物种研究推向了更精细的层面。相对于16S，宏基因组可以获得更丰富的属、种水平物种，因而通常用于对16S的拓展补充。基于各层级的物种丰度表，可以结合堆叠图、Circos图、热图等进行物种分布特征的初步展示，即物种组成分析。

7.1 物种注释

当前主流的物种注释有两种方法，即基于reads或基于基因。不同方法各有特色，在文章中也都有广泛应用：
1）基于reads进行物种注释：不受样本复杂度、组装结果的影响，在物种定性定量研究中更准确，使用率较高。
方法：使用Kaiju软件将reads比对Nr微生物库（包含细菌、真菌、古细菌、病毒、微小动植物）进行物种注释。
2）基于基因进行物种注释：受样本、组装影响，定性定量不一定准确，但可基于数据库找到功能-物种的对应关系，用于特定功能的物种分析。
方法：使用DIOMAND软件将非冗余基因集的unigene序列比对Nr微生物库，使用MEGAN（MEtaGenome Analyzer）软件的LCA算法，获得物种注释信息。
注：我们提供两种注释方案可选，若无选择，则默认第一种基于reads注释的方法。两种注释方法详细的比较见
各层级物种总注释信息统计如下：

Tab 7-1-1 物种注释总表

ID	F-3_tagNumber	F-4_tagNumber	F-5_tagNumber	F-6_tagNumber	G-2_tagNumber	G-4_tagNumber	G-5_tagNumber	G-6_tagNumber	F-3_relativeAbundance	F-4_relativeAbundance	F-5_relativeAbundance	F-6_relativeAbundance	G-2_relativeAbundance	G-4_relativeAbundance	G-5_relativeAbundance	G-6_relativeAbundance
r__root	19583451.0	23774457.0	21561531.0	21978713.0	24193302.0	21887107.0	21640329.0	23204817.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0	1.0
r__root|k__Archaea	156995.0	190165.0	136392.0	190712.0	464969.0	196153.0	103382.0	664393.0	0.00801671778891269	0.007998710548888666	0.006325710358879432	0.008677123178231591	0.019218914392090836	0.008962034132697392	0.004777284116151839	0.02863168453343114
r__root|k__Archaea|p__Archaea_noname	1666.0	2063.0	1676.0	2858.0	1762.0	1716.0	1811.0	2415.0	8.507182927054072e-05	8.677380097471837e-05	7.773102939675295e-05	0.00013003491150732983	7.283007503481749e-05	7.840232151284315e-05	8.368634321594649e-05	0.00010407321893553395
r__root|k__Archaea|p__Archaea_noname|c__Archaea_noname	1666.0	2063.0	1676.0	2858.0	1762.0	1716.0	1811.0	2415.0	8.507182927054072e-05	8.677380097471837e-05	7.773102939675295e-05	0.00013003491150732983	7.283007503481749e-05	7.840232151284315e-05	8.368634321594649e-05	0.00010407321893553395
r__root|k__Archaea|p__Archaea_noname|c__Archaea_noname|o__Archaea_noname	1666.0	2063.0	1676.0	2858.0	1762.0	1716.0	1811.0	2415.0	8.507182927054072e-05	8.677380097471837e-05	7.773102939675295e-05	0.00013003491150732983	7.283007503481749e-05	7.840232151284315e-05	8.368634321594649e-05	0.00010407321893553395
r__root|k__Archaea|p__Archaea_noname|c__Archaea_noname|o__Archaea_noname|f__Archaea_noname	1666.0	2063.0	1676.0	2858.0	1762.0	1716.0	1811.0	2415.0	8.507182927054072e-05	8.677380097471837e-05	7.773102939675295e-05	0.00013003491150732983	7.283007503481749e-05	7.840232151284315e-05	8.368634321594649e-05	0.00010407321893553395
r__root|k__Archaea|p__Archaea_noname|c__Archaea_noname|o__Archaea_noname|f__Archaea_noname|g__Archaea_noname	1666.0	2063.0	1676.0	2858.0	1762.0	1716.0	1811.0	2415.0	8.507182927054072e-05	8.677380097471837e-05	7.773102939675295e-05	0.00013003491150732983	7.283007503481749e-05	7.840232151284315e-05	8.368634321594649e-05	0.00010407321893553395
r__root|k__Archaea|p__Archaea_noname|c__Archaea_noname|o__Archaea_noname|f__Archaea_noname|g__Archaea_noname|s__Candidatus_Geothermarchaeota_archaeon	33.0	106.0	52.0	157.0	27.0	51.0	66.0	76.0	1.6850962580599303e-06	4.4585666036452486e-06	2.4117025827154853e-06	7.143275404706363e-06	1.1160113654597458e-06	2.330138926081003e-06	3.049861210520413e-06	3.2751820451762235e-06
r__root|k__Archaea|p__Archaea_noname|c__Archaea_noname|o__Archaea_noname|f__Archaea_noname|g__Archaea_noname|s__Candidatus_Geothermarchaeota_archaeon_ex4572_27	30.0	26.0	38.0	22.0	38.0	31.0	29.0	21.0	1.5319056891453912e-06	1.0936106763658157e-06	1.7623980412151623e-06	1.0009685280480253e-06	1.5706826624989016e-06	1.416358955068845e-06	1.340090531895333e-06	9.049845124829039e-07
r__root|k__Archaea|p__Archaea_noname|c__Archaea_noname|o__Archaea_noname|f__Archaea_noname|g__Archaea_noname|s__Candidatus_Pacearchaeota_archaeon	169.0	245.0	202.0	216.0	188.0	155.0	167.0	148.0	8.629735382185703e-06	1.0305177527293263e-05	9.368536955933231e-06	9.82769100265334e-06	7.770745803941935e-06	7.081794775344224e-06	7.71707306298347e-06	6.377986087974751e-06

使用 KRONA 对物种注释结果 进行可视化展示。圆圈从内到外依次代表不同的分类级别，扇形的大小代表不同OTU注释结果的相对比例。

KRONA可视化结果

7.2 物种丰度统计

优势物种很大程度决定着微生物群落的生态结构以及功能结构，了解群落在各个水平的物种组成情况能有 效地对群落结构的形成、改变以及生态影响等进行解读。 我们统计了各个层级分类水平上的各样品的物种组成情况

结果在文件夹:05.Taxonomy下

• 界水平上的各样品表达谱总表: /05.Taxonomy/profiling.L1.Kingdom.xls
• 门水平上的各样品表达谱总表: /05.Taxonomy/profiling.L2.Phylum.xls
• 纲水平上的各样品表达谱总表: /05.Taxonomy/profiling.L3.Class.xls
• 目水平上的各样品表达谱总表: /05.Taxonomy/profiling.L4.Order.xls
• 科水平上的各样品表达谱总表: /05.Taxonomy/profiling.L5.Family.xls
• 属水平上的各样品表达谱总表: /05.Taxonomy/profiling.L6.Genus.xls
• 种水平上的各样品表达谱总表: /05.Taxonomy/profiling.L7.Species.xls

Tab 7-2-1 物种丰度表（门水平）

Level	Phylum	F-3	F-4	F-5	F-6	G-2	G-4	G-5	G-6
2	Archaea_noname	8.507182927054072e-05	8.677380097471837e-05	7.773102939675295e-05	0.00013003491150732983	7.283007503481749e-05	7.840232151284315e-05	8.368634321594649e-05	0.00010407321893553395
2	Candidatus_Aenigmarchaeota	1.6085009736026607e-05	2.2797576407318155e-05	2.1890838827725175e-05	1.938239058856631e-05	1.3474803894069524e-05	1.2884297591271428e-05	1.4047845575730387e-05	1.5169264209237245e-05
2	Candidatus_Bathyarchaeota	0.00017683298005034966	0.00014852074224029597	0.00017276138693490735	0.0001427745109552138	0.0001304493284959614	0.0001498142262474433	0.0001626592645610887	0.00013669575588551292
2	Candidatus_Diapherotrites	4.953161728236765e-06	6.814035752740851e-06	8.162685664575489e-06	1.6015496448768405e-05	9.42409597499341e-06	7.767129753603343e-06	4.2513216873920906e-06	8.144860612346135e-06
2	Candidatus_Heimdallarchaeota	2.251901363043725e-05	2.469036411641284e-05	2.1519807661153562e-05	4.2586661011497805e-05	1.682283799044876e-05	2.2753121278202735e-05	2.7541170931366154e-05	2.3658880826338774e-05
2	Candidatus_Korarchaeota	2.8442382295132762e-05	2.7508514705509362e-05	2.5090982639405336e-05	3.294096428667138e-05	1.7690846830250784e-05	2.6636686155004404e-05	2.647834050951813e-05	3.1976119441062604e-05
2	Candidatus_Lokiarchaeota	1.884243997648831e-05	2.023179751276759e-05	1.2986090830006459e-05	1.5151023629090566e-05	2.095621341807745e-05	1.9098001394154102e-05	1.8345377281463698e-05	2.5511944351899004e-05
2	Candidatus_Marsarchaeota	4.54465354446466e-06	8.706823461835532e-06	4.962541852895326e-06	6.506295432312165e-06	5.745391844403877e-06	4.705966850712613e-06	5.683832255969861e-06	4.007788555281432e-06
2	Candidatus_Micrarchaeota	2.1293489079120936e-05	2.5994284538233618e-05	2.5322877118512596e-05	2.602518172924866e-05	2.463491754866698e-05	1.955489137966018e-05	2.5184459995964017e-05	2.417601483347186e-05
2	Candidatus_Odinarchaeota	1.5829692121169041e-06	1.2197965236387943e-06	1.2522301871791942e-06	1.8654413477258654e-06	1.446681399670041e-06	2.83271791013769e-06	1.1552504585304595e-06	2.1547250297212e-06

7.3 物种分布堆叠图

我们使用堆叠图直观展示各个层级分类水平上各样品的物种丰度情况，初步呈现样本间的物种分布规律，优势物种等信息。由于在堆叠图中无法呈现丰度过低的物种，我们只展示总丰度排名前10的高丰度物种，其余物种统一归类到Other类别，无法注释到该水平的序列则被归类到Unclassified类别。

7.4 物种分布热图

热图比较美观，可以包含的信息量相对较多，我们使用热图展示更多物种的丰度信息。挑选物种总丰度排名前20的物种，使用R语言pheatmap包绘制热图，详细展示各个层级分类水平上各样品的物种丰度高低。

7.5 物种分布Circos图

Circos图以更新颖的形式展示物种丰度分布规律，通过图中连线的粗细展示各样本的优势物种。对各分类水平，我们使用Circos软件绘制Circos图展示前10个高丰度物种。

广州基迪奥生物科技有限公司

8 Alpha 多样性分析

8.1 Alpha 多样性指数

Alpha多样性是指特定生境或者生态系统内物种/功能的丰富程度，它可以指示生境的平衡状态、生存条件情况等。如有研究发现疾病组肠道菌群失衡，alpha多样性会显著下降。 通常基于物种/功能丰富度（种类的数量）和物种均匀度（丰度高低的均匀程度，若所有物种丰度相等，则均匀度最高）两个指标来评估。
我们主要展示Chao1，ACE（Alternating Conditional Expectation），Shannon，Simpson，四个指数以及相关分析结果。
- Chao1、ACE 指数只考虑物种的丰富度，数值越大，多样性越高。
- Shannon、Simpson综合体现物种的丰富度和均匀度，数值越大，样本的均衡性越高。

8.2 Alpha 多样性差异分析

不同生境下的环境驱动因素能引起微生物α多样性差异。结合分组和采样信息，通过对两组或者多组间的α多样性进行假设检验，可以分析组间的物种/功能多样性是否存在显著的差异，从而初步判断驱动群落多样性变化的潜在因素等。我们同时使用以下几种主流的假设检验方法进行差异分析。
- 针对2个分组的比较时，使用weltch’s T-test检验和wilcox秩和检验
- 针对2个以上分组的比较时，使用Kruskal-Wallis秩和检验和Tukey检验 (上述的检验方法均要求每组至少含有3个重复样本)
以属水平Chao1指数为例，基于welch’s t 检验、Tukey HSD检验结果用盒型图展示两组差异如下：

结果在文件夹:06.Alpha 下

9 Beta 多样性分析

Beta 多样性分析可以用来分析样本关系，评估样本的聚类特征与预期分组是否一致，分组是否显著。我们从基因丰度、基因功能（默认KEGG、eggNOG、CAZy丰度表）以及物种丰度多个角度开展样本关系分析，进行组间差异及组间多元统计等分析，并使用韦恩图展示样本间共有、特有的信息。

9.1 样本相关性分析

同时，为了比较样本（分组）之间的相似性，我们基于物种（基因、功能）计算样本之间的Pearson系数，并进行热图展示。

结果在文件夹:07.Beta/Heatmap下

9.2 PCA主成分分析

基于物种（基因、功能）丰度表，可以开展主成分分析（PCA，Principal Component Analysis），从而利用降维的思想研究样本间的距离关系。这种方法借用方差分解可以有效的找出数据中最“主要”的元素和结构，将复杂的样本组成关系反映到横纵坐标的两个特征值上，从而达到简化数据复杂度的效果。分析结果中，样品组成越相似，反映在PCA 图中的距离越近，而且不同环境间的样品往往可能表现出各自聚集的分布情况。

结果在文件夹:07.Beta/PCA下

9.3 PCoA主坐标分析

PCoA主坐标分析是一种展示样本间相似性的分析方式，它的分析思路与PCA分析基本一致，都是通过降维方式寻找复杂样本中的主要样本差异距离。与PCA不同的是，PCoA主要利用Bray-Curtis等信息，因此结果更集中于体现样本间结构的相异性。 基于物种（基因、功能）丰度信息，使用R语言计算样本间的Bray-Curtis矩阵，我们可以绘制PCoA图形。分析结果中，样品越相似，反映在PCoA 图中的距离越近，而且不同环境间的样品往往可能表现出各自聚集的分布情况。

结果在文件夹:07.Beta/PCoA下

9.4 NMDS分析

NMDS是非线性模型，适用于无法获得研究对象间精确的相似性或相异性数据，其设计目的是为了克服线性模型（包括PCA、 PCoA）的缺点，更好地反映生态学数据的非线性结构。我们根据PCoA分析所获得的Bray-Curtis矩阵，进行NMDS分析。其特点是根据样品中包含的物种（基因、功能）信息，以点的形式反映在多维空间上，而对不同样品间的差异程度，则是通过点与点间的距离体现的，最终获得样品的空间定位点图。

结果在文件夹:07.Beta/NMDS下

9.5 UPGMA分类树

在微生物生态研究当中，UPGMA分类树可以用于研究样本间的相似性，解答样本的分类学问题。利用R语言，根据物种（基因、功能）所计算的Bray-Curtis矩阵信息，可以将样本进行UPGMA分类树分类。其中越相似的样本将拥有越短的共同分支。

结果在文件夹:07.Beta/UPGMA 下

9.6 Anosim差异检验

Analysis of Similarity (ANOSIM)分析是一种对微生物群落结构的非参数检验方法，用来检验组间的差异是否显著大于组内差异，从而判断分组是否有意义。
根据物种（基因、功能）所计算的Bray-Curtis矩阵信息，我们开展Anosim分析，以属水平为例展示如下。

结果在文件夹: 07.Beta/Anosim_and_Adonis/Anosim 下

Tab 9-6-1 物种水平Anosim分析结果表

diffs	Rvalue	Pvalue	significant
F-VS-G	-0.0521	0.583

根据分组信息，基于Bray-Curtis距离，利用Mothur软件可以计算两两样本之间距离的轶（Ranks），通过比较组内和组间的轶均值，从而获得分组差异信息。
结合Anosim检验结果，我们基于样本间Bray-Curtis距离的秩（rank），使用盒形图展示检验结果。

9.7 Adonis分析

Adonis是一种基于Bray-Curtis距离矩阵的非参数多元方差分析方法。该方法可分析不同分组因素对样品差异的解释度，并使用置换检验对分组的统计学意义进行显著性分析。根据物种（基因、功能）所计算的Bray-Curtis矩阵信息，我们开展Asonis分析，以属水平示例如下。

结果在文件夹: 06.Comparison/Anosim_and_Adonis/Adonis 下

Tab 9-7-1 基于Bray -Curtis距离的Adonis分析(物种水平)

diffs	Df	SumsOfSqs	MeanSqs	Fvalue	R2	Pvalue	significant
F-VS-G	1	0.0189	0.0189	0.7947	0.117	0.551

广州基迪奥生物科技有限公司

10 常规差异分析

10.1 物种韦恩分析

不同生境下的微生物群落，其物种分布存在一定程度的相似性和特异性。
在多分组（或样本）情况下，为了解不同分组（或样本）之间的物种差异情况，我们基于样本的物种丰度信息开展韦恩图（4组以内）/花瓣图（5组以上）和Upset图分析，以展示不同样本之间的共有特有信息，以种水平展示如下：

结果在文件夹:08.Different/Venn/下

10.2 功能韦恩图分析

类似的，我们也可以统计分组共有、特有的功能特征gene、KEGG、eggNOG、CAZy，辅助了解分组之间的功能差异。
以kegg.B水平示例如下：

10.3 物种差异 Welch’s t 检验

使用Welch's T检验（R语言）进行两个分组间的物种（门到种水平，保留在至少一个样本的相对丰度达到0.1%以上的物种参与分析）差异分析，一般以P-value < 0.05（或0.01）为显著性阈值，P-value越小说明物种差异越显著.

Tab 10-3-1 种水平 F_vs_G Welch’s T检验统计

labels	F	G	fold(G/F)	p-value	significant
Methanobrevibacter_millerae	0.00143635	0.0015162	1.05559479	0.927357199978657	no
Methanobrevibacter_olleyae	0.0002818	0.00088716	3.14822993	0.29134122619155	no
Methanobrevibacter_ruminantium	0.00029661	0.00126429	4.26250422	0.23977526587141	no
Methanobrevibacter_sp._YE315	0.00033607	0.00173199	5.15374671	0.181108438782593	no
Methanobrevibacter_thaueri	0.00055569	0.0020649	3.71590199	0.177588593993751	no
Acidobacteria_bacterium	0.00118907	0.00105044	0.88341273	0.218483551673163	no
Coriobacteriales_bacterium_OH1046	0.00091	0.00121596	1.33621276	0.242712453629302	no
Slackia_heliotrinireducens	0.00082083	0.00099416	1.21116807	0.333886284437545	no
bacterium_F083	0.00366297	0.00374867	1.02339744	0.960365274125692	no
bacterium_P201	0.0017276	0.00183194	1.06039478	0.816154555106317	no

针对比较组间有显著差异（P< 0.05）的物种，我们使用柱形图直观展示其在两个分组中的丰度和差异显著性。（组间无显著差异的物种，则无图形）。

10.4 功能差异 Welch’s t 检验

使用 Welch's T检验（R语言）进行两个分组功能（Gene，KEGG，CAZy，eggNOG各功能层级，取比较组中相对丰度之和在top200的功能参与分析）差异分析，结果以P-value < 0.05（或0.01）为阈值，P-value越小说明差异越显著。

Tab 10-4-1 KEGG LevelB F_vs_G Welch’s T检验统计

labels	F	G	fold(G/F)	p-value	significant
Carbohydrate metabolism	0.04647864	0.04728229	1.01729071	0.735713042352088	no
Amino acid metabolism	0.03457677	0.03458282	1.00017522	0.996699325734872	no
Metabolism of cofactors and vitamins	0.02541726	0.0261729	1.02972915	0.655394569910569	no
Nucleotide metabolism	0.0240265	0.02453778	1.02128002	0.57338365259418	no
Membrane transport	0.02321069	0.02177247	0.93803621	0.643425047020106	no
Replication and repair	0.01919478	0.01852055	0.96487407	0.405822351877779	no
Translation	0.01800969	0.01603198	0.8901863	0.184060083149889	no
Energy metabolism	0.01457296	0.01459341	1.00140333	0.973348053832285	no
Signal transduction	0.01358768	0.01404621	1.03374597	0.449599716284469	no
Cellular community - prokaryotes	0.01238952	0.01218747	0.98369156	0.896197491569113	no

针对比较组间有显著差异（P< 0.05）的功能，我们使用柱形图直观展示其在两个分组中的丰度和差异显著性。（组间无显著差异的功能，则无图形）。

10.5 物种差异方差分析

使用方差分析（R语言）进行两个分组间的物种（门到种水平，保留在至少一个样本的相对丰度达到0.1%以上的物种参与分析）差异分析，一般以P-value < 0.05（或0.01）为显著性阈值，P-value越小说明物种差异越显著。

针对组间有显著差异（P<0.05）的物种或功能，我们使用盒型图展示每个物种在比较组分组当中的丰度，便于直观对比丰度差异。

10.6 功能差异方差分析

使用方差分析（ANOVA，Analysis of Variance）（R语言）进行两个分组功能（Gene，KEGG，CAZy，eggNOG各功能层级，取比较组中相对丰度之和在top200的功能参与分析）差异分析，结果以P-value < 0.05（或0.01）为阈值，P-value越小说明差异越显著。

针对组间有显著差异（P<0.05）的功能，我们使用盒型图展示每个功能在比较组分组当中的丰度，便于直观对比丰度差异。

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11 个性化差异分析

11.1 物种差异 Metastats 分析

MetaStats 可用于两组间的差异分析。是不同方法的综合。首先进行T检验计算，若组内物种数量少于样本重复数，则基于Fisher精确检验计算P值；若组内物种数大于样本重复数，且重复数大于等于8，则进行单物种的Permutation test 置换检验计算P值，若组内物种数大于样本重复数，且重复数小于8，则混合整个样本基于Permutation test 置换检验计算P值。最后进行多重检验校正计算q值。

结果在文件夹:08.Different/MetaStats下

Tab 11-1-1 Metastats 物种差异分析表(F-VS-G)

Phylum	Mean(F%)	variance(F%)	std.err(F%)	Mean(G%)	variance(G%)	std.err(G%)	P-value	FDR
Candidatus_Saccharibacteria	0.0052733151033589	3.03066539687542e-06	0.000870440319159709	0.00213362022078524	1.39340840826156e-06	0.000590213607150319	0.0113846153846154	0.142307692307692
Tenericutes	0.00398534336174878	3.6553101405306e-07	0.000302295804657069	0.00229076609395827	4.23786334244343e-07	0.000325494367940654	0.00634615384615385	0.142307692307692
Chlamydiae	0.00137304119352609	9.55323228260157e-08	0.000154541517743627	0.00105391181338721	2.95128132716907e-09	2.71628483740617e-05	0.0606923076923077	0.307692307692308
Fusobacteria	0.00213099773071195	1.83858953638619e-07	0.000214393886129373	0.00170046818232271	7.47403154228998e-09	4.32262407059936e-05	0.0738461538461539	0.307692307692308
Lentisphaerae	0.00140427233126215	1.12295252740029e-07	0.000167552419215621	0.000968577423638092	7.27282894093774e-08	0.00013484091497889	0.0618076923076923	0.307692307692308
Viruses_noname	0.00169404607277827	8.50346249512059e-07	0.000461071103386468	0.000706842287509728	1.5409744808716e-07	0.000196276239065736	0.0727307692307692	0.307692307692308
Verrucomicrobia	0.0027240930150824	2.52278387680304e-07	0.000251136610075226	0.00212042235083182	1.69763488428322e-07	0.000206011825163219	0.095	0.339285714285714
Candidatus_Melainabacteria	0.000689823051810787	1.63949934891477e-07	0.000202453658210637	0.000369356783064785	3.28645845598799e-08	9.06429596823161e-05	0.1955	0.382396449704142
Elusimicrobia	0.000823831487350264	3.47778748478986e-07	0.00029486384505352	0.000395614643107053	3.80477483381041e-09	3.08414284437767e-05	0.196615384615385	0.382396449704142
Euryarchaeota	0.00734091277024641	1.04201495822828e-06	0.000510395669610422	0.0156475444075367	0.000131986630691866	0.00574427172694385	0.198846153846154	0.382396449704142

11.2 代谢通路 reporter score 分析

对比较组内pathway，我们基于reporter_score算法，进行精细的差异分析，获得pathway的得分，统计如下

结果在文件夹:08.Different/ReportScore下

Tab 11-2-1 F_vs_G pathway 差异分析 reporter_score

Pathway ID	Pathway	ReporterScore	Sig	F	G	KO Number	...
ko00230	Purine metabolism	0.038570961581914504	ns	0.016964615852905825	0.017348519226301748	37930	...
ko02010	ABC transporters	-1.988922338037288	*	0.017147460514868477	0.016236825403914214	33855	...
ko00240	Pyrimidine metabolism	0.9393183011863767	ns	0.01481074029712802	0.015269980297308408	33616	...
ko02020	Two-component system	-0.03572494608188855	ns	0.013587677201408056	0.014046206593751288	27270	...
ko02024	Quorum sensing	-0.9630553611131618	ns	0.01238952304785125	0.01218746927248724	24892	...
ko00520	Amino sugar and nucleotide sugar metabolism	-0.9956493455424241	ns	0.01068069413225684	0.010584777998041741	24328	...
ko00500	Starch and sucrose metabolism	0.07717280429956615	ns	0.01018990239716327	0.011673325635221084	23047	...
ko03440	Homologous recombination	2.7197871018379054	*	0.00988389172238257	0.009256773657304618	20545	...
ko00970	Aminoacyl-tRNA biosynthesis	3.2822402463154177	*	0.008881198487858056	0.008603023366557166	20316	...
ko03430	Mismatch repair	1.5135848191578274	ns	0.008274938084926976	0.0080526204505079	17826	...

我们挑选显著富集的20条代谢通路，绘制柱形图展示如下：

我们挑选显著富集的20条代谢通路，绘制气泡图展示如下：

11.3 物种差异 LEfSe 分析

通过LDA Effect Size(LefSe)分析组间菌群差异，可以找出各组间特异的主要菌群，有助于开发biomarker等研究。根据物种（基因、功能）在各层级的丰度信息(物种在至少一个样本的相对丰度达到0.1%以上)，我们开展LefSe分析。

结果在文件夹:08.Different/LefSe下

11.4 功能差异 LEfSe 分析

类似的，我们可以将LEfSe的分析方法应用于功能差异，分析原理与物种LEfSe分析一致。我们使用LEfSe软件，针对KEGG、eggNOG、CAZy等主要数据库开展高丰度top200功能的差异分析。图形的分枝树，代表不同功能层级，如KEGG数据库，由内至外，对应Level A、B、C。以KEGG示例如下：

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12 软件版本和参考文献汇总

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13 数据库汇总

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14 目录结构

result                                           结果目录
├── 01.QC                                   质控目录
│   ├── 1_Filter_fq/sample/*.new.png(pdf)             过滤后碱基分布图（矢量图）
│   ├── 1_Filter_fq/sample/*.old.png(pdf)             过滤前碱基分布图（矢量图）
│   ├── 1_Filter_fq/filter.stat.fill.png(pdf)                           数据预处理分布图（百分比）
│   ├── 1_Filter_fq/filter.stat.count.png(pdf)                           数据预处理分布图（数值）
│   ├── 1_Filter_fq/reads_filter.stat.xls                            所有样品过滤信息总表
│   ├── 1_Filter_fq/reads_filter.stat.xls                            所有样品过滤信息总表
│   ├── 1_Filter_fq/reads_info.stat.xls                          所有样品过滤前后碱基质量信息
│   ├── 2_rHost/filter_host.stat.xls                             所有样品宿主过滤信息总表
│   └── 2_rHost/filter_host.stack.png(pdf)                       所有样本宿主过滤分布图
├── 02.Assemble                                       组装结果
│   ├── sample/sample.contigs.length_distribution.png(pdf)                         各样本组装结果统计位图（矢量图）
│   └── assem.contigs.stat.txt                             所有样本组装结果统计
├── 03.Genes                                        基因预测
│   ├── Unigenes.final.fna(faa)                             非冗余基因核酸（蛋白）序列
│   ├── Unigenes.final.gff                             非冗余基因gff文件
│   ├── Unigenes.expression.final.xls                   非冗余基因表达量总表
│   ├── Unigenes.count.final.xls                             非冗余基因counts数
│   ├── Unigenes.abundance.final.xls                             非冗余基因丰度
│   ├── bar*                             各样本非冗余基因数目柱状图
│   ├── violin*                             各分组非冗余基因数目小提琴图
│   └── Core_Pan/*                           Core-Pan分析结果目录
├── 04.Annotation                                          基因注释
│   ├── KEGG/*                             KEGG数据库注释结果
│   ├── eggNOG/*                             eggNOG数据库注释结果
│   ├── CAZy/*                             CAZy数据库注释结果
│   ├── CARD/*                             CARD数据库注释结果
│   ├── VFDB/*                             VFDB数据库注释结果
│   └── PHI/*                             PHI数据库注释结果
├── 05.Taxonomy                                          物种注释
│   ├── profiling.all.xls                                  各lineage比对丰度信息
│   ├── profiling.all.readnumber.xls                       各lineage比对reads number统计
│   ├── profiling.all.relative.xls                         各lineage比对相对丰度统计
│   ├── profiling.L*.*.xls                                 各层级比对相对丰度统计
│   ├── profiling.all.stat.xls                             各层级比对上的reads数目统计
│   ├── stack_plot/*                                       各层级比对信息堆叠图
│   ├── heatmap/*                                          各层级比对信息热图
│   ├── krona/*                                            krona图形化展示结果
│   └── circos/*                                           各层级比对记过Circos图展示
├── 06.Comparison                                          比较分析
│   ├── Venn/*                                  各层级Venn/UpSet结果
│   ├── Heatmap/*                               各层相关性热图结果
│   ├── PCA/*                                   各层级PCA分析结果
│   ├── PCoA/*                                  各层级PCoA分析结果
│   ├── NMDS/*                                  各层级NMDS分析结果
│   ├── UPGMA/*                                 各层级UPGMA分析结果
│   └── Anosim_and_Adonis/*                     各层级Anosim/Adonis分析结果
├── 07.Different                                           差异分析
│   ├── T_test/*                                 各层级各比较组Welch’s T分析结果
│   ├── ANOVA/*                                  各层级各比较组ANOVA分析结果
│   ├── Ternary/*                                各层级各比较组三元图分析结果
│   ├── MetaStats/*                              各层级各比较组MetaStats分析结果
│   └── LefSe/*                                  各比较组LefSe分析结果
├── index.html                                     结题报告
└── src                                            结果报告内容
    ├── content.html                                 结题报告主体
    ├── css                                            结题报告js脚本
    ├── doc                                            结题报告说明文档
    ├── image                                          结题报告图片
    └── js                                             结题报告js脚本


    
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15 附录

15.1 问题解答

• 问题解答

15.2 英文方法

• 英文方法

15.3 中文实验方法

• 实验方法

15.4 引用与致谢

如果您的研究课题使用了基迪奥的测序和分析服务，我们期望您在论文发表时，在Method部分或Acknowledgements部分引用或提及基迪奥公司。
以下语句可供参考:
We are grateful to/thank Guangzhou Genedenovo Biotechnology Co., Ltd for assisting in sequencing and/or bioinformatics analysis.

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