Thank you for your answer! You said "merge each replicates", and I want to know about that point in detail. In ONE sample (in this case, H_G3), there are some differences among multiple fastq files. But now I'm confused what files are reasonable to be merged and what files are not. As you say, is it okay to merge all fastq files for a sample?
Hello, I'm trying to analyze public RNA-seq data obtained from GEO database. But I have a trouble now about how to handle some data.
The representative dataset is GSE88945 (PRJNA349164). The number of samples is just three but the number of data are 47. There are many files that have the same GSM ID and different SRR IDs.
I can describe the first header lines from several fastq files with the same GSM ID like below:
Filename
> Header line
SRR4432915_GSM2355695_H_G3_Homo_sapiens_RNA-Seq_1.fastq.gz
> @SRR4432915.1 HWI-ST959:164:C2KV4ACXX:6:1101:1172:2037/1
SRR4432916_GSM2355695_H_G3_Homo_sapiens_RNA-Seq_1.fastq.gz
> @SRR4432916.1 DF9F08P1:223:D2F1AACXX:7:2115:13996:65512/1
SRR4432917_GSM2355695_H_G3_Homo_sapiens_RNA-Seq_1.fastq.gz
> @SRR4432917.1 DF9F08P1:223:D2F1AACXX:7:2304:18001:55398/1
SRR4432918_GSM2355695_H_G3_Homo_sapiens_RNA-Seq_1.fastq.gz
> @SRR4432918.1 DF9F08P1:223:D2F1AACXX:8:1101:1402:2235/1
In this case, there are three different points to branch. 1) HWI-ST959 vs. DF9F08P1 2) 7 vs. 8 3) 2115 vs. 2304
Many questions in my mind can be summarized like below. I wonder what makes those differences between fastq files and whether I can merge the data or not. If somebody knows, please advise me.
Thanks in advance.
1 answer
They have three samples: H_G3 ( 16 replicates), H_G5 (13 replicates) & H_G14 ( 18 replicates). See below-
esearch -db bioproject -query "PRJNA349164" | elink -target sra | efetch -format runinfo| cut -d "," -f1,30
#Note: SamplesGroup column is added after running the above command
Run SampleName SamplesGroup
SRR4432915 GSM2355695 H_G3
SRR4432916 GSM2355695 H_G3
SRR4432917 GSM2355695 H_G3
SRR4432918 GSM2355695 H_G3
SRR4432919 GSM2355695 H_G3
SRR4432920 GSM2355695 H_G3
SRR4432921 GSM2355695 H_G3
SRR4432922 GSM2355695 H_G3
SRR4432923 GSM2355695 H_G3
SRR4432924 GSM2355695 H_G3
SRR4432925 GSM2355695 H_G3
SRR4432926 GSM2355695 H_G3
SRR4432927 GSM2355695 H_G3
SRR4432928 GSM2355695 H_G3
SRR4432929 GSM2355695 H_G3
SRR4432930 GSM2355695 H_G3
SRR4432931 GSM2355696 H_G5
SRR4432932 GSM2355696 H_G5
SRR4432933 GSM2355696 H_G5
SRR4432934 GSM2355696 H_G5
SRR4432935 GSM2355696 H_G5
SRR4432936 GSM2355696 H_G5
SRR4432937 GSM2355696 H_G5
SRR4432938 GSM2355696 H_G5
SRR4432939 GSM2355696 H_G5
SRR4432940 GSM2355696 H_G5
SRR4432941 GSM2355696 H_G5
SRR4432942 GSM2355696 H_G5
SRR4432943 GSM2355696 H_G5
SRR4432944 GSM2355697 H_G14
SRR4432945 GSM2355697 H_G14
SRR4432946 GSM2355697 H_G14
SRR4432947 GSM2355697 H_G14
SRR4432948 GSM2355697 H_G14
SRR4432949 GSM2355697 H_G14
SRR4432950 GSM2355697 H_G14
SRR4432951 GSM2355697 H_G14
SRR4432952 GSM2355697 H_G14
SRR4432953 GSM2355697 H_G14
SRR4432954 GSM2355697 H_G14
SRR4432955 GSM2355697 H_G14
SRR4432956 GSM2355697 H_G14
SRR4432957 GSM2355697 H_G14
SRR4432958 GSM2355697 H_G14
SRR4432959 GSM2355697 H_G14
SRR4432960 GSM2355697 H_G14
SRR4432961 GSM2355697 H_G14
You may merge each replicates or analyze them separately. It will depend upon what basically you want to achieve. Also, it looks like they have provided raw and normalized data for this study.
May I ask you, what is your plan after merging the files? These are mRNA expression data.
Oh, I'm sorry for my late reply. I'm planning to do processing of those RNA-seq data, and then perform co-expression network analysis (after integrating other datasets). So I'm about to preprocess those data now. But I'm confused whether I can just simply merge data from one sample.
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