語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Statistical Analysis of Microbiome D...
~
Xia, Yinglin.
Statistical Analysis of Microbiome Data with R
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Statistical Analysis of Microbiome Data with R/ by Yinglin Xia, Jun Sun, Ding-Geng Chen.
作者:
Xia, Yinglin.
其他作者:
Sun, Jun.
面頁冊數:
XXIII, 505 p. 84 illus., 67 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Statistics . -
電子資源:
https://doi.org/10.1007/978-981-13-1534-3
ISBN:
9789811315343
Statistical Analysis of Microbiome Data with R
Xia, Yinglin.
Statistical Analysis of Microbiome Data with R
[electronic resource] /by Yinglin Xia, Jun Sun, Ding-Geng Chen. - 1st ed. 2018. - XXIII, 505 p. 84 illus., 67 illus. in color.online resource. - ICSA Book Series in Statistics,2199-0980. - ICSA Book Series in Statistics,.
Chapter 1: Introduction to R, RStudio and ggplot2 -- Chapter 2: What are Microbiome Data? -- Chapter 3: Bioinformatic and Statistical Analyses of Microbiome Data -- Chapter 4: Power and Sample Size Calculation in Hypothesis Testing Microbiome Data -- Chapter 5: Microbiome Data Management -- Chapter 6: Exploratory Analysis of Microbiome Data -- Chapter 7: Comparisons of Diversities, OTUs and Taxa among Groups -- Chapter 8: Community Composition Study -- Chapter 9: Modeling Over-dispersed Microbiome Data -- Chapter 10: Linear Regression Modeling metadata -- Chapter 11: Modeling Zero-Inflated Microbiome Data.
This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research. The book also discusses recent developments in statistical modelling and data analysis in microbiome research, as well as the latest advances in next-generation sequencing and big data in methodological development and applications. This timely book will greatly benefit all readers involved in microbiome, ecology and microarray data analyses, as well as other fields of research.
ISBN: 9789811315343
Standard No.: 10.1007/978-981-13-1534-3doiSubjects--Topical Terms:
1253516
Statistics .
LC Class. No.: QA276-280
Dewey Class. No.: 519.5
Statistical Analysis of Microbiome Data with R
LDR
:02918nam a22004095i 4500
001
989071
003
DE-He213
005
20200701031449.0
007
cr nn 008mamaa
008
201225s2018 si | s |||| 0|eng d
020
$a
9789811315343
$9
978-981-13-1534-3
024
7
$a
10.1007/978-981-13-1534-3
$2
doi
035
$a
978-981-13-1534-3
050
4
$a
QA276-280
072
7
$a
UFM
$2
bicssc
072
7
$a
COM077000
$2
bisacsh
072
7
$a
UFM
$2
thema
082
0 4
$a
519.5
$2
23
100
1
$a
Xia, Yinglin.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1209579
245
1 0
$a
Statistical Analysis of Microbiome Data with R
$h
[electronic resource] /
$c
by Yinglin Xia, Jun Sun, Ding-Geng Chen.
250
$a
1st ed. 2018.
264
1
$a
Singapore :
$b
Springer Singapore :
$b
Imprint: Springer,
$c
2018.
300
$a
XXIII, 505 p. 84 illus., 67 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
490
1
$a
ICSA Book Series in Statistics,
$x
2199-0980
505
0
$a
Chapter 1: Introduction to R, RStudio and ggplot2 -- Chapter 2: What are Microbiome Data? -- Chapter 3: Bioinformatic and Statistical Analyses of Microbiome Data -- Chapter 4: Power and Sample Size Calculation in Hypothesis Testing Microbiome Data -- Chapter 5: Microbiome Data Management -- Chapter 6: Exploratory Analysis of Microbiome Data -- Chapter 7: Comparisons of Diversities, OTUs and Taxa among Groups -- Chapter 8: Community Composition Study -- Chapter 9: Modeling Over-dispersed Microbiome Data -- Chapter 10: Linear Regression Modeling metadata -- Chapter 11: Modeling Zero-Inflated Microbiome Data.
520
$a
This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research. The book also discusses recent developments in statistical modelling and data analysis in microbiome research, as well as the latest advances in next-generation sequencing and big data in methodological development and applications. This timely book will greatly benefit all readers involved in microbiome, ecology and microarray data analyses, as well as other fields of research.
650
0
$a
Statistics .
$3
1253516
650
0
$a
Big data.
$3
981821
650
1 4
$a
Statistics and Computing/Statistics Programs.
$3
669775
650
2 4
$a
Statistics for Life Sciences, Medicine, Health Sciences.
$3
670172
650
2 4
$a
Big Data.
$3
1017136
700
1
$a
Sun, Jun.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1209580
700
1
$a
Chen, Ding-Geng.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
848229
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9789811315336
776
0 8
$i
Printed edition:
$z
9789811315350
776
0 8
$i
Printed edition:
$z
9789811346453
830
0
$a
ICSA Book Series in Statistics,
$x
2199-0980
$3
1255207
856
4 0
$u
https://doi.org/10.1007/978-981-13-1534-3
912
$a
ZDB-2-SMA
912
$a
ZDB-2-SXMS
950
$a
Mathematics and Statistics (SpringerNature-11649)
950
$a
Mathematics and Statistics (R0) (SpringerNature-43713)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入