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README.Rmd

@@ -55,6 +55,7 @@ The script ```run_kraken.r``` is included for convenience of running Kraken2Uniq
 * ```--Kraken2Uniq_path``` path to Kraken2 main 'kraken2' function
 * ```--kraken_database_path``` path to kraken database
 * ```--kreport2mpa_path``` path to kreport2mpa.py function (included in SAHMI/functions)
+* ```--paired``` are fastq files paired end (T) or single-end/unpaired (F). Default is T. 
 
 
 The output includes fastq files with Kraken NCBI taxonomic assignments for each read, an output file containing k-mer level taxonomic data, and Kraken standard, uniq, and MPA style reports. 
@@ -83,7 +84,7 @@ The outputs are fasta files for microbiome reads and a microbiome output file.
 
 
 ## 3. Single-cell k-mer analysis
-The next step is tabulating k-mer statistics across individual barcodes using the script ```sckmer.r```. This function counts the number of k-mers and unique k-mers assigned to a taxon across barcodes. The cell barcode and unique molecular identifier (UMI) are used to identify unique barcodes and reads. Data is reported for taxa of pre-specified ranks (default genus + species) taking into account all subsequently higher resolution ranks. Reads with any k-mers mapped to the host (e.g. human) are discarded. Reads with >50% of the k-mers map outside the taxon's lineage are also discarded. The output is a table of barcodes, taxonomic IDs, number of k-mers, and number of unique k-mers. 
+The next step is tabulating k-mer statistics across individual barcodes using the script ```sckmer.r``` for paired end data and ```sckmer_unpaired.r``` for unpaired/single-end sequence data. These functions count the number of k-mers and unique k-mers assigned to a taxon across barcodes. The cell barcode and unique molecular identifier (UMI) are used to identify unique barcodes and reads. Data is reported for taxa of pre-specified ranks (default genus + species) taking into account all subsequently higher resolution ranks. Reads with any k-mers mapped to the host (e.g. human) are discarded. Reads with >50% of the k-mers map outside the taxon's lineage are also discarded. The output is a table of barcodes, taxonomic IDs, number of k-mers, and number of unique k-mers. 
 
 ```sckmer.r```
 
@@ -101,6 +102,7 @@ The next step is tabulating k-mer statistics across individual barcodes using th
 * ```min_frac``` minimum fraction of k-mers directly assigned to taxon ID or its lineage to use read. 
 * ```nsample``` max number of barcodes to sample per taxon ID
 
+Note that parameters for ```sckmer_unpared.r``` are the same but do not include ```fa2```. 
 
 ## 4. Barcode level signal denoising (barcode k-mer correlation test)
 True taxa are detected on multiple barcodes and with a proprotional number of total and unique k-mer sequences across barcodes, measured as a significant Spearman correlation between the number of total and unique k-mers across barcodes. We demonstrate this using example data from Zhang et al., Cell Reports 2019 for a gastric metaplasia sample positive for Helicobacter pylori. Running SAHMI steps 1-3 generates the Kraken report and sckmer.txt. 

README.md

@@ -51,6 +51,7 @@ The script `run_kraken.r` is included for convenience of running Kraken2Uniq and
 -   `--Kraken2Uniq_path` path to Kraken2 main 'kraken2' function
 -   `--kraken_database_path` path to kraken database
 -   `--kreport2mpa_path` path to kreport2mpa.py function (included in SAHMI/functions)
+-   `--paired` are fastq files paired end (T) or single-end/unpaired (F). Default is T. 
 
 
 The output includes fastq files with Kraken NCBI taxonomic assignments for each read, an output file containing k-mer level taxonomic data, and Kraken standard, uniq, and MPA style reports.
@@ -79,7 +80,7 @@ The outputs are fasta files for microbiome reads and a microbiome output file.
 
 ## 3. Single-cell k-mer analysis
 
-The next step is tabulating k-mer statistics across individual barcodes using the script `sckmer.r`. This function counts the number of k-mers and unique k-mers assigned to a taxon across barcodes. The cell barcode and unique molecular identifier (UMI) are used to identify unique barcodes and reads. Data is reported for taxa of pre-specified ranks (default genus + species) taking into account all subsequently higher resolution ranks. Reads with any k-mers mapped to the host (e.g. human) are discarded. Reads with >50% of the k-mers map outside the taxon's lineage are also discarded. The output is a table of barcodes, taxonomic IDs, number of k-mers, and number of unique k-mers.
+The next step is tabulating k-mer statistics across individual barcodes using the script `sckmer.r` for paired end data and `sckmer_unpaired.r` for unpaired/single-end sequence data. These functions count the number of k-mers and unique k-mers assigned to a taxon across barcodes. The cell barcode and unique molecular identifier (UMI) are used to identify unique barcodes and reads. Data is reported for taxa of pre-specified ranks (default genus + species) taking into account all subsequently higher resolution ranks. Reads with any k-mers mapped to the host (e.g. human) are discarded. Reads with >50% of the k-mers map outside the taxon's lineage are also discarded. The output is a table of barcodes, taxonomic IDs, number of k-mers, and number of unique k-mers.
 
 `sckmer.r`
 
@@ -97,6 +98,8 @@ The next step is tabulating k-mer statistics across individual barcodes using th
 -   `min_frac` minimum fraction of k-mers directly assigned to taxon ID or its lineage to use read.
 -   `nsample` max number of barcodes to sample per taxon ID
 
+Note that parameters for `sckmer_unpared.r` are the same but do not include `fa2`. 
+
 ## 4. Barcode level signal denoising (barcode k-mer correlation test)
 
 True taxa are detected on multiple barcodes and with a proprotional number of total and unique k-mer sequences across barcodes, measured as a significant Spearman correlation between the number of total and unique k-mers across barcodes. We demonstrate this using example data from Zhang et al., Cell Reports 2019 for a gastric metaplasia sample positive for Helicobacter pylori. Running SAHMI steps 1-3 generates the Kraken report and sckmer.txt.