Skip to content

Running FastprojectR An Example

Jump to bottom
mattjones315 edited this page Aug 18, 2017 · 1 revision

Here a brief demo of running FastProject on data from Patel and Tirosh et al 2014, the example used in the FastProject publication

Required Files - Can be downloaded here

First gather the expression matrix file - expression_matrix.txt

The top of the file will look like this:

	MGH264_A01	MGH264_A02	MGH264_A03	MGH264_A04	MGH264_A05	MGH264_A06	MGH264_A07	MGH264_A08	MGH264_A10
A2M		0.00	0.00	0.00	0.00	0.00	1.81	0.00	0.00	0.00	0.00	0.00
AAAS	0.00	0.00	0.00	0.00	7.63	0.00	0.00	0.00	0.00	8.21	1.14
AAK1	0.00	0.83	5.72	2.32	1.82	8.68	6.64	2.07	4.47	5.81	1.49
AAMP	8.47	8.18	0.00	9.33	0.00	1.81	8.03	8.24	0.00	7.96	0.00
AARS	8.21	0.00	0.00	0.00	8.14	2.59	0.00	9.20	0.00	0.00	0.00
AARSD1	1.15	3.64	3.12	0.00	7.72	8.01	7.94	0.00	0.00	7.42	6.09
AASDH	7.28	6.08	0.00	6.98	8.01	6.48	3.19	0.00	0.00	5.95	6.09
AASS	6.30	8.74	6.56	9.48	9.05	6.84	9.12	8.46	2.65	1.63	8.96
AATF	6.19	9.43	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00	0.00
ABAT	6.71	6.56	0.00	8.32	7.45	9.48	8.75	0.00	7.31	9.85	8.03
ABCA1	0.00	0.00	5.91	9.64	0.00	0.00	8.11	7.01	0.00	4.32	7.50
ABCA8	1.61	0.00	0.00	3.02	0.00	0.00	3.19	0.00	0.00	0.00	0.00

More information on requirements for the expression file can be found here: Gene Expression Matrix

Then some signature files are needed. For this demo, two are used, tcga_sigs.txt and h.all.v5.1.symbols.gmt

The first, tcga_sigs.txt was obtained from Verhaak et al, 2010

TCGA Proneural	Plus	CDKN1B
TCGA Proneural	Plus	EPB41
TCGA Proneural	Plus	CLGN
TCGA Proneural	Plus	PDE10A
TCGA Proneural	Plus	RALGPS2
.
.
TCGA Proneural	Minus	TTPA
TCGA Proneural	Minus	SIRT5
TCGA Proneural	Minus	CASQ1
TCGA Proneural	Minus	AKR7A3
TCGA Proneural	Minus	MRPL49
.
.
TCGA Neural	Plus	TTPA
TCGA Neural	Plus	SIRT5
TCGA Neural	Plus	CASQ1
TCGA Neural	Plus	AKR7A3
TCGA Neural	Plus	MRPL49
.
.

The second, h.all.v5.1.symbols.gmt, can be downloaded from MSigDB and represents their collection of Hallmark gene sets. Below is a preview of this type of .gmt signature file:

HALLMARK_TNFA_SIGNALING_VIA_NFKB	http://www.broadinst...	JUNB	CXCL2	ATF3	NFKBIA	TNFAIP3	PTGS2	CXCL1	IER3	CD83	CCL20	CXCL3	MAFF	NFKB2	
HALLMARK_HYPOXIA	http://www.broadinst...	PGK1	PDK1	GBE1	PFKL	ALDOA	ENO2	PGM1	NDRG1	HK2	ALDOC	GPI	MXI1	SLC2A1	
HALLMARK_CHOLESTEROL_HOMEOSTASIS	http://www.broadinst...	FDPS	CYP51A1	IDI1	FDFT1	DHCR7	SQLE	HMGCS1	NSDHL	LSS	MVD	LDLR	TM7SF2	ALDOC	
HALLMARK_MITOTIC_SPINDLE	http://www.broadinst...	ARHGEF2	CLASP1	KIF11	KIF23	ALS2	ARF6	MYO9B	MYH9	TUBGCP3	CKAP5	RACGAP1	PREX1	ARHGEF3	
HALLMARK_WNT_BETA_CATENIN_SIGNALING	http://www.broadinst...	MYC	CTNNB1	JAG2	NOTCH1	DLL1	AXIN2	PSEN2	FZD1	NOTCH4	LEF1	AXIN1	NKD1	WNT5B	
HALLMARK_TGF_BETA_SIGNALING	http://www.broadinst...	TGFBR1	SMAD7	TGFB1	SMURF2	SMURF1	BMPR2	SKIL	SKI	ACVR1	PMEPA1	NCOR2	SERPINE1	JUNB	
HALLMARK_IL6_JAK_STAT3_SIGNALING	http://www.broadinst...	IL4R	IL6ST	STAT1	IL1R1	CSF2RB	SOCS3	STAT3	OSMR	IL2RG	IFNGR1	TYK2	IL13RA1	TLR2

More information on valid signature file formats can be found here: Signatures

Unless you are running the analysis with the paramter nomodel set to False, a housekeeping gene file is required. If using the Gene Name Housekeeping file available from the input file download page, a preview looks like such:

RPL10
ACTN4
GPAA1
.
.
RPS15
H2AFY

Lastly, it can be helpful to include some meta-data for the samples. This is incorporated into the output visualization. In this case, a pre-computed signature file is included with information on which patient each tumor cell was donated from.

For this example, this file will be called precomputed_signatures.txt

A preview of precomputed_signatures.txt

        Type    MGH264_A01  MGH264_A02  MGH264_A03  MGH28_C12  MGH28_D01  MGH28_D03
Patient Factor	264         264         264         28         28         28

More information on the precomputed-signature file format here: Sample Meta-Data (a.k.a "Pre-computed Signatures")*

Running FastProject

Once the required files have been gathered, and FastProject has been installed (Installation Instructions) the analysis can be run by entering this command in your terminal:

fp <- FastProject("expression_matrix.txt", "housekeeping_genes/Gene Name Housekeeping.txt", c("tcga_sigs.txt", "h.all.v5.1.symbols.gmt"), precomputed="precomputed.txt")
fpo <- Analyze(fp)

For more documentation on object parameters, see this page: FastProjectR Parameters

Opening the results report

After the analysis, a FastProjectOutput object will be created. You can either view the report without saving the object first with

viewResults(fpo)

or view the report while saving the object as an RDS file first:

saveFPOutAndViewResults(fpo)

It is recommended to use Google Chrome for best viewing results.

Clone this wiki locally