Projects

Projects

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Projects

The tappAS application is project based: you create a project, input your data, and work with it. Each project has a corresponding file folder where all its data and analyses results are stored. All the necessary project management functions – create, open, rename, and delete – are provided in the application. To create a project, you must provide the following information:

  • A unique project name
  • The biological species associated with the RNA-seq data
  • The file location for the annotation features file or select one of the application provided annotation files
  • The experiment type
  • The file location for your experiment design file
  • The file location for your transcript level raw counts expression matrix file
  • Optionally, but recommended, the low count and coefficient of variation filtering parameter
  • Optionally, the inclusion or exclusion transcripts list file location for filtering
Input Data and Filtering

There are three input data files required to create a project: an experiment design file, a transcript level raw counts expression matrix, and a corresponding annotation file. The input data and optional filtering block diagram is shown below:

A. Experiment Design
An experiment design file defining the experimental groups, time slots, for time course experiments, and replicates. The first experimental group is considered the control group. See Experiment Design File Format for details.
B. Expression Matrix
A data file containing transcript level raw counts for one or more experimental groups and one or more time points with at least two replicates each. You must provide raw counts in the expression matrix; they are required for some statistical analyses. Internally, the application maintains a copy of the original raw counts matrix as well as a normalized copy. See Expression Matrix File Format for details.
C. Annotation Features

A data file containing annotation features for all expressed transcripts. Any transcript in the expression matrix that is not included in this file will be filtered out. You may use one of the annotation files provided by the application or use your own. The application currently provides the following annotation files:

  • Homo sapiens – Ensembl and RefSeq
  • Mus musculus – Ensembl and RefSeq
  • Arabidopsis thaliana – Ensembl
  • Zea mays – Ensembl

See Annotation Features File Format for details.

D. Low Counts and Coefficient of Variation Filter
An optional filter for removing transcripts with low expression levels and inconsistent expression values across samples.
E. Transcripts Filter
An optional transcripts filter for removing unwanted transcripts. You may provide an inclusion list, for transcripts to include, or an exclusion list for transcripts to filter out. You may, for example, initially bring in all the data into a project and then use the application’s ad hoc queries, or analysis results, to generate, and export, a transcripts list. You may then reinput the data into the project applying the exported transcript list as a filter.
F. Project Data
The project data consists of all the transcripts that remain after filtering, along with their corresponding annotation features. Transcripts that are filtered out are no longer part of the project data. For example, if a gene contains 5 isoforms and two of them are filtered out, the application data will only have 3 isoforms for the gene. If all isoforms for a gene are filtered out, the gene will no longer be part of the project data. It is important that you understand that from the application’s perspective, the data included in the project represents the ‘universe’ for the project. Genes and transcripts that are not part of the project data are not taken into account in any way by the application. For example, when using ‘All genes’ in a data analysis, it refers to all genes in the project data not all genes for the species or all genes in the annotation file. You may reinput the data for a project at any time; however, all existing analysis results will be cleared.

Expression Matrix Data Normalization

As previously stated, the application keeps a copy of the original raw counts expression matrix and also creates a new matrix using normalized counts. The Trim Mean of M (TMM) normalization procedure by Robinson and Oshlack, provided in the R package NOISeq, is used to normalize the data.

You may view the NOISeq documentation and installation instructions at:


Experiment Design File Format

The experiment design file defines the relationship between the expression matrix data and the various experimental groups, time slots, and replicates. There are three experiment types supported by the application:

  • Case-Control
  • Time-Course Single Series
  • Time-Course Multiple Series

The design file will change depending on the experiment type. However, regardless of experiment type, it is possible to use the same expression matrix and just modify the design file. By doing so, you have the option to run case-control analysis, and time-course single series analysis using the data from a time-course multiple series experiment. You may also, leave out replicates, time slots, etc. without having to make any changes to the expression matrix.

Regardless of what data you use from the expression matrix, the first experimental group is treated as the control group where relevant. The following format rules apply to all design files:

  • The data must be in Tab Separated Values (TSV) format and must contain a single line header
  • Comment lines are not allowed
  • The first experimental group is considered the control group where relevant
  • All samples for an experimental group must be grouped together
  • All samples for a given time slot, within an experimental group, must be grouped together
  • All time slots for a given group must be specified in chronological order
  • Time values must be specified using numbers only – no time units
  • Sample column names must be unique
  • Sample column names are case-sensitive and must match the expression matrix
Case-Control Design File

The case-control design file must contain two experimental groups. Each group must contain at least two replicates.

Sample design file:

sample group
CASE1 CASE
CASE2 CASE
CONTROL1 CONTROL
CONTROL2 CONTROL
Single Series Time-Course Design File

The single series time-course design file must contain a single experimental group. The group must contain at least two time slots with a minimum of two replicates per time slot.

Sample design file:

sample time group
CASE1 0 CASE
CASE2 0 CASE
CASE3 3 CASE
CASE4 3 CASE
Multiple Series Time-Course Design File

The multiple series time-course design file must contain at least two experimental groups. Each group must contain at least two time slots with a minimum of two replicates per time slot.

Sample design file:

sample time group
CASE1 0 CASE
CASE2 0 CASE
CASE3 3 CASE
CASE4 3 CASE
CONTROL1 0 CONTROL
CONTROL2 0 CONTROL
CONTROL3 3 CONTROL
CONTROL4 3 CONTROL
Expression Matrix File Format

The expression matrix file must contain raw expression counts for one or more experimental groups. Each group may have one or more time slots with each time slot having at least two replicates. The following format rules apply:

  • The data must be in Tab Separated Values (TSV) format and must contain a single line header
  • A unique transcript id identifies each row and must match one of the transcripts provided in the annotation file or it will be discarded
  • Sample column names must be unique
  • Sample column names are case-sensitive and must match the experiment design file
  • The columns do not need to be in any specific order – the experiment design file will provide grouping information

Expression matrix file partial contents sample:

NPC1 NPC2 OLD1 OLD2
Transcript.1 7275 3602 3707 3485
Transcript.2 358.64 206.58 2056.72 2094.65
Transcript.2 332.44 329.38 1529.46 1318.57
Transcript.4 46.92 13.03 20.82 33.78
Annotation Features File Format

The annotation file must follow the basic Generic Feature Format 3 (GFF3). However, it has been slightly modified to suit the application: the “score” and “phase” columns are not used and some of the attributes may not fully abide by the formal specifications. The file consists of a set of annotation features for each transcript. Each set of features is divided into sections as follows:

Transcript 1
Transcript Level Feature Annotations – basic transcript information, UTR motifs, microRNAs, etc.
Genomic Level Feature Annotations – exons, splice junctions, etc.
Protein Level Feature Annotations – gene ontology features, domains, phosphorylation sites, etc.
Transcript 2
…
Transcript 3
…

Some of the annotation features must be named as expected by the application, see sample annotation file below:

Source Feature Description
tappAS transcript Start of transcript features
tappAS gene Gene information
tappAS CDS CDS information
tappAS genomic Start of genomic features
tappAS exon Exon
tappAS splice_junction Splice junction
tappAS protein Start of protein features

In addition, the following attributes must be named as required by the application, see sample annotation file below:

Attribute Description
ID Feature ID
Name Feature name
Desc Feature description
Chr Feature chromosome

Annotation file partial contents sample (header should not be included):

SeqName Source Feature Start End Score Strand Phase Attributes
PB.3189.4 tappAS transcript 1 1399 . + . ID=XM_006524897.1; primary_class=full_splice_match; PosType=T
PB.3189.4 tappAS gene 1 1399 . + . ID=Qpct; Name=Qpct; Desc=glutaminyl-peptide cyclotransferase (glutaminyl cyclase); PosType=T
PB.3189.4 tappAS CDS 10 951 . + . ID=XP_006524960.1; PosType=T
PB.3189.4 UTRsite 3’UTRmotif 1288 1295 . + . ID=U0023; Name=K-BOX; Desc=K-Box; PosType=T
PB.3189.4 UTRsite PAS 1380 1399 . + . ID=U0043; Name=PAS; Desc=Polyadenylation Signal; PosType=T
PB.3189.4 mirWalk miRNA 986 993 . + . ID=mmu-miR-495-5p; Name=mmu-miR-495-5p; Desc=UTR3; PosType=T
PB.3189.4 tappAS genomic 1 1 . + . Chr=chr17; PosType=G
PB.3189.4 tappAS exon 79052257 79052388 . + . Chr=chr17; PosType=G
PB.3189.4 tappAS exon 79070673 79070951 . + . Chr=chr17; PosType=G
PB.3189.4 tappAS exon 79077482 79077658 . + . Chr=chr17; PosType=G
PB.3189.4 tappAS exon 79079467 79079566 . + . Chr=chr17; PosType=G
PB.3189.4 tappAS exon 79081747 79081863 . + . Chr=chr17; PosType=G
PB.3189.4 tappAS exon 79089623 79090216 . + . Chr=chr17; PosType=G
PB.3189.4 tappAS splice_junction 79052388 79070673 . + . ID=known_canonical; Chr=chr17; PosType=G
PB.3189.4 tappAS splice_junction 79070951 79077482 . + . ID=known_canonical; Chr=chr17; PosType=G
PB.3189.4 tappAS splice_junction 79077658 79079467 . + . ID=known_canonical; Chr=chr1; PosType=G
… … … … … … … … …
PB.3189.4 tappAS protein 1 313 . + . ID=NP_001303658.1; PosType=P

Generating an annotation file is not a trivial task and it’s not recommended unless you have a good programming background and knowledge of annotation features. If possible, use one of the annotation files provided by the application. If no annotation file is provided for the species you are interested in, you may contact us .

Category: Overview